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Hisao Ishibuchi
Person information
- affiliation: Southern University of Science and Technology, Shenzhen, China
- affiliation: Osaka Prefecture University, Japan
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2020 – today
- 2025
- [j185]Ruining Zhang, Jian Wang, Chanjuan Liu, Kaile Su, Hisao Ishibuchi, Yaochu Jin:
Synergistic integration of metaheuristics and machine learning: latest advances and emerging trends. Artif. Intell. Rev. 58(9): 268 (2025) - [j184]Chanjuan Liu, Guojing Zhang, Bingcai Chen, Hisao Ishibuchi:
A new EGO-driven memetic algorithm for solving flexible job shop scheduling problem. Inf. Sci. 717: 122298 (2025) - [j183]Xu Yang
, Rui Wang, Kaiwen Li, Hisao Ishibuchi
:
Meta-Black-Box optimization for evolutionary algorithms: Review and perspective. Swarm Evol. Comput. 93: 101838 (2025) - [j182]Yang Nan
, Tianye Shu
, Hisao Ishibuchi
, Ke Shang
:
Gradient-Guided Local Search for Large-Scale Hypervolume Subset Selection. IEEE Trans. Evol. Comput. 29(2): 519-533 (2025) - [j181]Yifan Wang
, Witold Pedrycz
, Hisao Ishibuchi
, Jihua Zhu
:
Fusion of Explainable Deep Learning Features Using Fuzzy Integral in Computer Vision. IEEE Trans. Fuzzy Syst. 33(1): 156-167 (2025) - [c400]Yiping Liu, Jiahao Yang, Xuanbai Ren, Xinyi Zhang, Yuansheng Liu, Bosheng Song, Xiangxiang Zeng, Hisao Ishibuchi:
Multi-Objective Molecular Design Through Learning Latent Pareto Set. AAAI 2025: 19006-19014 - [c399]Hisao Ishibuchi, Lie Meng Pang:
Visual Explanations of Some Problematic Search Behaviors of Frequently-Used EMO Algorithms. EMO (2) 2025: 3-16 - [c398]Tianye Shu, Hisao Ishibuchi, Yang Nan, Lie Meng Pang:
Numerical Analysis of Pareto Set Modeling. EMO (2) 2025: 17-30 - [c397]Yang Nan, Hisao Ishibuchi, Lie Meng Pang:
Performance Analysis of Constrained Evolutionary Multi-objective Optimization Algorithms on Artificial and Real-World Problems. EMO (2) 2025: 72-84 - [c396]Yang Nan, Hisao Ishibuchi, Lie Meng Pang:
Small Population Size is Enough in Many Cases with External Archives. EMO (2) 2025: 99-113 - [c395]Lie Meng Pang, Hisao Ishibuchi, Yang Nan:
Enhancing NSGA-II with a Knee Point for Constrained Multi-objective Optimization. EMO (1) 2025: 180-192 - [i44]Lie Meng Pang, Hisao Ishibuchi:
Large Language Model-Based Benchmarking Experiment Settings for Evolutionary Multi-Objective Optimization. CoRR abs/2502.21108 (2025) - [i43]Zhiji Cui, Zimin Liang, Lie Meng Pang, Hisao Ishibuchi, Miqing Li:
When to Truncate the Archive? On the Effect of the Truncation Frequency in Multi-Objective Optimisation. CoRR abs/2504.01332 (2025) - [i42]Hisao Ishibuchi, Lie Meng Pang:
Optimal Distribution of Solutions for Crowding Distance on Linear Pareto Fronts of Two-Objective Optimization Problems. CoRR abs/2504.17222 (2025) - 2024
- [j180]Naoki Masuyama
, Yusuke Nojima
, Yuichiro Toda
, Chu Kiong Loo
, Hisao Ishibuchi
, Naoyuki Kubota
:
Privacy-Preserving Continual Federated Clustering via Adaptive Resonance Theory. IEEE Access 12: 139692-139710 (2024) - [j179]Kangnian Lin, Genghui Li, Qingyan Li, Zhenkun Wang
, Hisao Ishibuchi
, Hu Zhang:
Multi-objective evolutionary algorithm with evolutionary-status-driven environmental selection. Inf. Sci. 669: 120551 (2024) - [j178]Ke Shang
, Tianye Shu
, Hisao Ishibuchi
:
Learning to Approximate: Auto Direction Vector Set Generation for Hypervolume Contribution Approximation. IEEE Trans. Evol. Comput. 28(1): 105-116 (2024) - [j177]Yiping Liu
, Liting Xu, Yuyan Han
, Xiangxiang Zeng
, Gary G. Yen
, Hisao Ishibuchi
:
Evolutionary Multimodal Multiobjective Optimization for Traveling Salesman Problems. IEEE Trans. Evol. Comput. 28(2): 516-530 (2024) - [j176]Lie Meng Pang
, Hisao Ishibuchi
, Linjun He
, Ke Shang
, Longcan Chen
:
Hypervolume-Based Cooperative Coevolution With Two Reference Points for Multiobjective Optimization. IEEE Trans. Evol. Comput. 28(4): 1054-1068 (2024) - [j175]Yifan Wang
, Hisao Ishibuchi
, Witold Pedrycz
, Jihua Zhu
, Xiangyong Cao
, Jun Wang
:
Convolutional Fuzzy Neural Networks With Random Weights for Image Classification. IEEE Trans. Emerg. Top. Comput. Intell. 8(5): 3279-3293 (2024) - [c394]Yang Nan, Hisao Ishibuchi, Tianye Shu:
Performance Evaluation of Evolutionary Multi-Objective Algorithms Using Real-World Problems with an Additional Total Constraint Violation Objective. CEC 2024: 1-6 - [c393]Cheng Gong
, Yang Nan, Tianye Shu, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang:
Interactive Final Solution Selection in Multi-Objective Optimization. CEC 2024: 1-9 - [c392]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Analysis of Algorithm Comparison Results on Real-World Multi-Objective Problems. CEC 2024: 1-9 - [c391]Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi:
Last-X-Generation Archiving Strategy for Multi-Objective Evolutionary Algorithms. CEC 2024: 1-8 - [c390]Yang Nan
, Hisao Ishibuchi
, Tianye Shu
, Ke Shang
:
Analysis of Real-World Constrained Multi-Objective Problems and Performance Comparison of Multi-Objective Algorithms. GECCO 2024 - [c389]Yang Nan
, Hisao Ishibuchi
, Tianye Shu
, Ke Shang
:
Gradient-Guided Local Search for IGD/IGDPlus Subset Selection. GECCO 2024 - [c388]Longcan Chen
, Lie Meng Pang
, Qingfu Zhang
, Hisao Ishibuchi
:
Enhancing the Convergence Ability of Evolutionary Multi-objective Optimization Algorithms with Momentum. GECCO 2024 - [c387]Cheng Gong
, Yang Nan
, Lie Meng Pang
, Hisao Ishibuchi
, Qingfu Zhang
:
Heuristic Initialization and Knowledge-based Mutation for Large-Scale Multi-Objective 0-1 Knapsack Problems. GECCO 2024 - [c386]Cheng Gong
, Yang Nan
, Lie Meng Pang
, Hisao Ishibuchi
, Qingfu Zhang
:
Performance of NSGA-III on Multi-objective Combinatorial Optimization Problems Heavily Depends on Its Implementations. GECCO 2024 - [c385]Hisao Ishibuchi
, Lie Meng Pang
, Ke Shang
:
New Framework of Multi-Objective Evolutionary Algorithms with Unbounded External Archive. GECCO Companion 2024: 883-902 - [c384]Rongguang Ye
, Longcan Chen
, Jinyuan Zhang
, Hisao Ishibuchi
:
Evolutionary Preference Sampling for Pareto Set Learning. GECCO 2024 - [c383]Tianye Shu, Ke Shang, Cheng Gong, Yang Nan, Hisao Ishibuchi:
Learning Pareto Set for Multi-Objective Continuous Robot Control. IJCAI 2024: 4920-4928 - [c382]Weiduo Liao
, Ying Wei, Qirui Sun, Qingfu Zhang, Hisao Ishibuchi:
A Multi-objective Perspective Towards Improving Meta-Generalization. IJCNN 2024: 1-10 - [c381]Rongguang Ye, Lei Chen, Weiduo Liao, Jinyuan Zhang, Hisao Ishibuchi:
Data-Driven Preference Sampling for Pareto Front Learning. IJCNN 2024: 1-8 - [c380]Kenneth Zhang
, Angel E. Rodriguez-Fernandez
, Ke Shang
, Hisao Ishibuchi
, Oliver Schütze
:
Hypervolume Gradient Subspace Approximation. PPSN (4) 2024: 20-35 - [c379]Cheng Gong
, Ping Guo
, Tianye Shu
, Qingfu Zhang
, Hisao Ishibuchi
:
LTR-HSS: A Learning-to-Rank Based Framework for Hypervolume Subset Selection. PPSN (4) 2024: 36-51 - [c378]Cheng Gong
, Lie Meng Pang
, Qingfu Zhang
, Hisao Ishibuchi
:
Three Objectives Degrade the Convergence Ability of Dominance-Based Multi-objective Evolutionary Algorithms. PPSN (4) 2024: 52-67 - [c377]Rongguang Ye
, Longcan Chen
, Jinyuan Zhang
, Hisao Ishibuchi
:
An Unbounded Archive-Based Inverse Model in Evolutionary Multi-objective Optimization. PPSN (4) 2024: 186-201 - [c376]Lie Meng Pang
, Hisao Ishibuchi
, Yang Nan
, Cheng Gong
:
Reliability of Indicator-Based Comparison Results of Evolutionary Multi-objective Algorithms. PPSN (4) 2024: 285-298 - [c375]Hiroki Shiraishi
, Rongguang Ye
, Hisao Ishibuchi
, Masaya Nakata
:
A Variable-Length Fuzzy Set Representation for Learning Fuzzy-Classifier Systems. PPSN (3) 2024: 386-402 - [c374]Lie Meng Pang, Hisao Ishibuchi:
Distance-Based Subset Selection With a Knee Point for Multi-Objective Optimization. SCIS/ISIS 2024: 1-5 - [c373]Rongguang Ye, Longcan Chen, Wei-Bin Kou, Jinyuan Zhang, Hisao Ishibuchi:
Pareto Front Shape-Agnostic Pareto Set Learning in Multi-Objective Optimization. SMC 2024: 4730-4736 - [c372]Yang Nan, Hisao Ishibuchi, Tianye Shu, Cheng Gong
:
On the use of the Total Constraint Violation as an Additional Objective in Evolutionary Multi-Objective Optimization. SMC 2024: 5048-5055 - [c371]Guotong Wu, Yang Nan, Ke Shang, Hisao Ishibuchi:
GHVC-Net: Hypervolume Contribution Approximation Based on Graph Neural Network. SMC 2024: 5339-5346 - [i41]Chanjuan Liu, Shike Ge, Zhihan Chen, Wenbin Pei, Enqiang Zhu, Yi Mei, Hisao Ishibuchi:
Improving Critical Node Detection Using Neural Network-based Initialization in a Genetic Algorithm. CoRR abs/2402.00404 (2024) - [i40]Rongguang Ye, Lei Chen, Weiduo Liao, Jinyuan Zhang, Hisao Ishibuchi:
Data-Driven Preference Sampling for Pareto Front Learning. CoRR abs/2404.08397 (2024) - [i39]Rongguang Ye, Longcan Chen, Jinyuan Zhang, Hisao Ishibuchi:
Evolutionary Preference Sampling for Pareto Set Learning. CoRR abs/2404.08414 (2024) - [i38]Tianye Shu, Ke Shang, Cheng Gong, Yang Nan, Hisao Ishibuchi:
Learning Pareto Set for Multi-Objective Continuous Robot Control. CoRR abs/2406.18924 (2024) - [i37]Javier Poyatos, Javier Del Ser, Salvador García, Hisao Ishibuchi, Daniel Molina, Isaac Triguero, Bing Xue, Xin Yao, Francisco Herrera:
Evolutionary Computation for the Design and Enrichment of General-Purpose Artificial Intelligence Systems: Survey and Prospects. CoRR abs/2407.08745 (2024) - [i36]Rongguang Ye, Longcan Chen, Wei-Bin Kou, Jinyuan Zhang, Hisao Ishibuchi:
Pareto Front Shape-Agnostic Pareto Set Learning in Multi-Objective Optimization. CoRR abs/2408.05778 (2024) - 2023
- [j174]Takato Kinoshita, Naoki Masuyama
, Yiping Liu
, Yusuke Nojima
, Hisao Ishibuchi
:
Reference Vector Adaptation and Mating Selection Strategy via Adaptive Resonance Theory-Based Clustering for Many-Objective Optimization. IEEE Access 11: 126066-126086 (2023) - [j173]Yifan Wang, Hisao Ishibuchi
, Meng Joo Er, Jihua Zhu:
Unsupervised multilayer fuzzy neural networks for image clustering. Inf. Sci. 622: 682-709 (2023) - [j172]Ke Shang, Tianye Shu, Hisao Ishibuchi
, Yang Nan, Lie Meng Pang:
Benchmarking large-scale subset selection in evolutionary multi-objective optimization. Inf. Sci. 622: 755-770 (2023) - [j171]Naoki Masuyama
, Yusuke Nojima
, Chu Kiong Loo
, Hisao Ishibuchi
:
Multi-Label Classification via Adaptive Resonance Theory-Based Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 45(7): 8696-8712 (2023) - [j170]Linjun He
, Auraham Camacho, Yang Nan
, Anupam Trivedi, Hisao Ishibuchi
, Dipti Srinivasan:
Effects of corner weight vectors on the performance of decomposition-based multiobjective algorithms. Swarm Evol. Comput. 79: 101305 (2023) - [j169]Jesús Guillermo Falcón-Cardona
, Edgar Covantes Osuna
, Carlos A. Coello Coello, Hisao Ishibuchi
:
On the utilization of pair-potential energy functions in multi-objective optimization. Swarm Evol. Comput. 79: 101308 (2023) - [j168]Lie Meng Pang
, Hisao Ishibuchi
, Ke Shang
:
Use of Two Penalty Values in Multiobjective Evolutionary Algorithm Based on Decomposition. IEEE Trans. Cybern. 53(11): 7174-7186 (2023) - [j167]Tianye Shu
, Ke Shang
, Hisao Ishibuchi
, Yang Nan
:
Effects of Archive Size on Computation Time and Solution Quality for Multiobjective Optimization. IEEE Trans. Evol. Comput. 27(4): 1145-1153 (2023) - [j166]Ke Shang
, Weiyu Chen
, Weiduo Liao
, Hisao Ishibuchi
:
HV-Net: Hypervolume Approximation Based on DeepSets. IEEE Trans. Evol. Comput. 27(4): 1154-1160 (2023) - [j165]Linjun He
, Ke Shang
, Yang Nan
, Hisao Ishibuchi
, Dipti Srinivasan
:
Relation Between Objective Space Normalization and Weight Vector Scaling in Decomposition-Based Multiobjective Evolutionary Algorithms. IEEE Trans. Evol. Comput. 27(5): 1177-1191 (2023) - [j164]Wei Liu
, Rui Wang
, Tao Zhang
, Kaiwen Li
, Wenhua Li
, Hisao Ishibuchi
, Xiangke Liao:
Hybridization of Evolutionary Algorithm and Deep Reinforcement Learning for Multiobjective Orienteering Optimization. IEEE Trans. Evol. Comput. 27(5): 1260-1274 (2023) - [j163]Jinyuan Zhang
, Linjun He
, Hisao Ishibuchi
:
Dual-Fuzzy-Classifier-Based Evolutionary Algorithm for Expensive Multiobjective Optimization. IEEE Trans. Evol. Comput. 27(6): 1575-1589 (2023) - [j162]Yang Nan
, Ke Shang
, Hisao Ishibuchi
, Linjun He
:
An Improved Local Search Method for Large-Scale Hypervolume Subset Selection. IEEE Trans. Evol. Comput. 27(6): 1690-1704 (2023) - [j161]Rui Wang
, Lining Xing
, Maoguo Gong
, Ponnuthurai Nagaratnam Suganthan
, Hisao Ishibuchi
:
Guest Editorial Special Issue on Deep Reinforcement Learning for Optimization: Methods and Application. IEEE Trans. Emerg. Top. Comput. Intell. 7(4): 981-982 (2023) - [c370]Yang Nan, Tianye Shu, Hisao Ishibuchi:
Effects of External Archives on the Performance of Multi-Objective Evolutionary Algorithms on Real-World Problems. CEC 2023: 1-8 - [c369]Jinyuan Zhang, Linjun He, Hisao Ishibuchi:
An Improved Fuzzy Classifier-Based Evolutionary Algorithm for Expensive Multiobjective Optimization Problems with Complicated Pareto Sets. EMO 2023: 231-246 - [c368]Lie Meng Pang, Yang Nan, Hisao Ishibuchi:
Partially Degenerate Multi-objective Test Problems. EMO 2023: 277-290 - [c367]Hisao Ishibuchi, Yang Nan, Lie Meng Pang:
Performance Evaluation of Multi-objective Evolutionary Algorithms Using Artificial and Real-world Problems. EMO 2023: 333-347 - [c366]Yang Nan, Hisao Ishibuchi, Tianye Shu, Ke Shang:
Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems. EMO 2023: 391-404 - [c365]Linjun He, Yang Nan, Hisao Ishibuchi, Dipti Srinivasan:
Preference-Based Nonlinear Normalization for Multiobjective Optimization. EMO 2023: 563-577 - [c364]Yusuke Nojima
, Koyo Kawano, Hajime Shimahara, Eric Vernon, Naoki Masuyama, Hisao Ishibuchi:
Fuzzy Classifiers with a Two-Stage Reject Option. FUZZ 2023: 1-6 - [c363]Yusuke Nojima
, Yuto Fujii
, Naoki Masuyama
, Yiping Liu
, Hisao Ishibuchi
:
A Decomposition-based Multi-modal Multi-objective Evolutionary Algorithm with Problem Transformation into Two-objective Subproblems. GECCO Companion 2023: 399-402 - [c362]Guangyan An
, Ziyu Wu
, Zhilong Shen
, Ke Shang
, Hisao Ishibuchi
:
Evolutionary Multi-Objective Deep Reinforcement Learning for Autonomous UAV Navigation in Large-Scale Complex Environments. GECCO 2023: 633-641 - [c361]Cheng Gong
, Yang Nan
, Lie Meng Pang
, Qingfu Zhang
, Hisao Ishibuchi
:
Effects of Including Optimal Solutions into Initial Population on Evolutionary Multiobjective Optimization. GECCO 2023: 661-669 - [c360]Linjun He
, Yang Nan
, Hisao Ishibuchi
, Dipti Srinivasan
:
Effects of Objective Space Normalization in Multi-Objective Evolutionary Algorithms on Real-World Problems. GECCO 2023: 670-678 - [c359]Hisao Ishibuchi
, Lie Meng Pang
, Ke Shang
:
Effects of Dominance Modification on Hypervolume-based and IGD-based Performance Evaluation Results of NSGA-II. GECCO 2023: 679-687 - [c358]Tianye Shu
, Yang Nan
, Ke Shang
, Hisao Ishibuchi
:
Two-Phase Procedure for Efficiently Removing Dominated Solutions From Large Solution Sets. GECCO 2023: 740-748 - [c357]Han Zhu
, Ke Shang
, Hisao Ishibuchi
:
STHV-Net: Hypervolume Approximation based on Set Transformer. GECCO 2023: 804-812 - [c356]Weiduo Liao, Ying Wei, Mingchen Jiang, Qingfu Zhang, Hisao Ishibuchi:
Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework. NeurIPS 2023 - [c355]Yang Nan, Tianye Shu, Hisao Ishibuchi:
Two-Stage Lazy Greedy Inclusion Hypervolume Subset Selection for Large-Scale Problem. SMC 2023: 1154-1161 - [c354]Cheng Gong
, Lie Meng Pang, Yang Nan, Hisao Ishibuchi, Qingfu Zhang:
Effects of Initialization Methods on the Performance of Multi-Objective Evolutionary Algorithms. SMC 2023: 1168-1175 - [c353]Lie Meng Pang, Yang Nan, Hisao Ishibuchi:
How to Find a Large Solution Set to Cover the Entire Pareto Front in Evolutionary Multi-Objective Optimization. SMC 2023: 1188-1194 - [c352]Ke Shang, Tianye Shu, Guotong Wu, Yang Nan, Lie Meng Pang, Hisao Ishibuchi:
Empirical Hypervolume Optimal µ-Distributions on Complex Pareto Fronts. SSCI 2023: 433-440 - [c351]Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi:
Analysis of Partition Methods for Dominated Solution Removal from Large Solution Sets. SSCI 2023: 441-448 - [c350]Guotong Wu, Tianye Shu, Ke Shang, Hisao Ishibuchi:
Normalization in R2-Based Hypervolume and Hypervolume Contribution Approximation. SSCI 2023: 449-456 - [c349]Jinyuan Zhang, Hisao Ishibuchi, Linjun He, Yang Nan:
Effects of Initialization Methods on the Performance of Surrogate-Based Multiobjective Evolutionary Algorithms. SSCI 2023: 933-940 - [c348]Cheng Gong
, Yang Nan, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang:
Initial Populations with a Few Heuristic Solutions Significantly Improve Evolutionary Multi-Objective Combinatorial Optimization. SSCI 2023: 1398-1405 - [c347]Guotong Wu, Tianye Shu, Yang Nan, Ke Shang, Hisao Ishibuchi:
Ensemble R2-based Hypervolume Contribution Approximation. SSCI 2023: 1503-1510 - [c346]Cheng Gong
, Yang Nan, Lie Meng Pang, Hisao Ishibuchi, Qingfu Zhang:
Examination of the Multimodal Nature of Multi-Objective Neural Architecture Search. SSCI 2023: 1821-1828 - [i35]Naoki Masuyama, Takanori Takebayashi, Yusuke Nojima
, Chu Kiong Loo, Hisao Ishibuchi, Stefan Wermter:
A Parameter-free Adaptive Resonance Theory-based Topological Clustering Algorithm Capable of Continual Learning. CoRR abs/2305.01507 (2023) - [i34]Naoki Masuyama, Yusuke Nojima
, Yuichiro Toda, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota:
Privacy-preserving Continual Federated Clustering via Adaptive Resonance Theory. CoRR abs/2309.03487 (2023) - 2022
- [j160]Naoki Masuyama
, Narito Amako, Yuna Yamada, Yusuke Nojima
, Hisao Ishibuchi
:
Adaptive Resonance Theory-Based Topological Clustering With a Divisive Hierarchical Structure Capable of Continual Learning. IEEE Access 10: 68042-68056 (2022) - [j159]Bin Qin
, Fulai Chung, Yusuke Nojima
, Hisao Ishibuchi
, Shitong Wang:
Fuzzy rule dropout with dynamic compensation for wide learning algorithm of TSK fuzzy classifier. Appl. Soft Comput. 127: 109410 (2022) - [j158]Jose Maria Alonso-Moral
, Corrado Mencar, Hisao Ishibuchi
:
Explainable and Trustworthy Artificial Intelligence [Guest Editorial]. IEEE Comput. Intell. Mag. 17(1): 14-15 (2022) - [j157]Hisao Ishibuchi
, Lie Meng Pang, Ke Shang:
Difficulties in Fair Performance Comparison of Multi-Objective Evolutionary Algorithms [Research Frontier]. IEEE Comput. Intell. Mag. 17(1): 86-101 (2022) - [j156]Jinyuan Zhang
, Hisao Ishibuchi
, Linjun He
:
A classification-assisted environmental selection strategy for multiobjective optimization. Swarm Evol. Comput. 71: 101074 (2022) - [j155]Ke Shang
, Hisao Ishibuchi
, Weiyu Chen
, Yang Nan
, Weiduo Liao
:
Hypervolume-Optimal μ-Distributions on Line/Plane-Based Pareto Fronts in Three Dimensions. IEEE Trans. Evol. Comput. 26(2): 349-363 (2022) - [j154]Xinye Cai
, Yushun Xiao
, Zhenhua Li, Qi Sun, Hanchuan Xu
, Miqing Li
, Hisao Ishibuchi
:
A Kernel-Based Indicator for Multi/Many-Objective Optimization. IEEE Trans. Evol. Comput. 26(4): 602-615 (2022) - [j153]Weiyu Chen
, Hisao Ishibuchi
, Ke Shang
:
Fast Greedy Subset Selection From Large Candidate Solution Sets in Evolutionary Multiobjective Optimization. IEEE Trans. Evol. Comput. 26(4): 750-764 (2022) - [j152]Yiming Peng
, Hisao Ishibuchi
:
A Diversity-Enhanced Subset Selection Framework for Multimodal Multiobjective Optimization. IEEE Trans. Evol. Comput. 26(5): 886-900 (2022) - [j151]Kaiwen Li
, Tao Zhang
, Rui Wang
, Ling Wang
, Hisao Ishibuchi
:
An Evolutionary Multiobjective Knee-Based Lower Upper Bound Estimation Method for Wind Speed Interval Forecast. IEEE Trans. Evol. Comput. 26(5): 1030-1042 (2022) - [j150]Mengjun Ming
, Rui Wang
, Hisao Ishibuchi
, Tao Zhang
:
A Novel Dual-Stage Dual-Population Evolutionary Algorithm for Constrained Multiobjective Optimization. IEEE Trans. Evol. Comput. 26(5): 1129-1143 (2022) - [j149]Lie Meng Pang
, Hisao Ishibuchi
, Ke Shang
:
Counterintuitive Experimental Results in Evolutionary Large-Scale Multiobjective Optimization. IEEE Trans. Evol. Comput. 26(6): 1609-1616 (2022) - [j148]Xiongtao Zhang
, Yusuke Nojima
, Hisao Ishibuchi
, Wenjun Hu
, Shitong Wang
:
Prediction by Fuzzy Clustering and KNN on Validation Data With Parallel Ensemble of Interpretable TSK Fuzzy Classifiers. IEEE Trans. Syst. Man Cybern. Syst. 52(1): 400-414 (2022) - [c345]Takato Kinoshita
, Naoki Masuyama
, Yusuke Nojima
, Hisao Ishibuchi
:
Analytical Methods to Separately Evaluate Convergence and Diversity for Multi-objective Optimization. MIC 2022: 172-186 - [c344]Hisao Ishibuchi
, Yiming Peng, Lie Meng Pang:
Multi-Modal Multi-Objective Test Problems with an Infinite Number of Equivalent Pareto Sets. CEC 2022: 1-8 - [c343]Yuichi Omozaki, Naoki Masuyama, Yusuke Nojima
, Hisao Ishibuchi
:
Evolutionary Multi-Objective Multi-Tasking for Fuzzy Genetics-Based Machine Learning in Multi-Label Classification. FUZZ-IEEE 2022: 1-8 - [c342]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Difficulties in fair performance comparison of multiobjective evolutionary algorithms. GECCO Companion 2022: 937-957 - [c341]Naoki Masuyama, Yusuke Nojima
, Hisao Ishibuchi
, Zongying Liu:
Adaptive Resonance Theory-based Clustering for Handling Mixed Data. IJCNN 2022: 1-8 - [c340]Tianye Shu, Ke Shang, Yang Nan, Hisao Ishibuchi
:
Direction Vector Selection for R2-Based Hypervolume Contribution Approximation. PPSN (2) 2022: 110-123 - [c339]Yiming Peng, Hisao Ishibuchi
:
Dynamic Multi-modal Multi-objective Optimization: A Preliminary Study. PPSN (2) 2022: 138-150 - [c338]Longcan Chen, Lie Meng Pang, Hisao Ishibuchi
:
New Solution Creation Operator in MOEA/D for Faster Convergence. PPSN (2) 2022: 234-246 - [c337]Ke Shang, Weiduo Liao
, Hisao Ishibuchi
:
HVC-Net: Deep Learning Based Hypervolume Contribution Approximation. PPSN (1) 2022: 414-426 - [e7]Hisao Ishibuchi, Chee-Keong Kwoh, Ah-Hwee Tan, Dipti Srinivasan, Chunyan Miao, Anupam Trivedi, Keeley A. Crockett:
IEEE Symposium Series on Computational Intelligence, SSCI 2022, Singapore, December 4-7, 2022. IEEE 2022, ISBN 978-1-6654-8768-9 [contents] - [i33]Ke Shang, Tianye Shu, Hisao Ishibuchi, Yang Nan, Lie Meng Pang:
Benchmarking Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization. CoRR abs/2201.06700 (2022) - [i32]Ke Shang, Tianye Shu, Hisao Ishibuchi:
Learning to Approximate: Auto Direction Vector Set Generation for Hypervolume Contribution Approximation. CoRR abs/2201.06707 (2022) - [i31]Naoki Masuyama, Narito Amako, Yuna Yamada, Yusuke Nojima, Hisao Ishibuchi:
Adaptive Resonance Theory-based Topological Clustering with a Divisive Hierarchical Structure Capable of Continual Learning. CoRR abs/2201.10713 (2022) - [i30]Ke Shang, Weiyu Chen, Weiduo Liao, Hisao Ishibuchi:
HV-Net: Hypervolume Approximation based on DeepSets. CoRR abs/2203.02185 (2022) - [i29]Naoki Masuyama, Itsuki Tsubota, Yusuke Nojima
, Hisao Ishibuchi:
Class-wise Classifier Design Capable of Continual Learning using Adaptive Resonance Theory-based Topological Clustering. CoRR abs/2203.09879 (2022) - [i28]Takato Kinoshita, Naoki Masuyama, Yiping Liu, Yusuke Nojima
, Hisao Ishibuchi:
Reference Vector Adaptation and Mating Selection Strategy via Adaptive Resonance Theory-based Clustering for Many-objective Optimization. CoRR abs/2204.10756 (2022) - [i27]Wei Liu, Rui Wang
, Tao Zhang
, Kaiwen Li, Wenhua Li
, Hisao Ishibuchi:
Hybridization of evolutionary algorithm and deep reinforcement learning for multi-objective orienteering optimization. CoRR abs/2206.10464 (2022) - [i26]Tianye Shu, Ke Shang, Hisao Ishibuchi, Yang Nan:
Effects of Archive Size on Computation Time and Solution Quality for Multi-Objective Optimization. CoRR abs/2209.03100 (2022) - 2021
- [j147]Ke Shang
, Hisao Ishibuchi
, Linjun He, Lie Meng Pang
:
A Survey on the Hypervolume Indicator in Evolutionary Multiobjective Optimization. IEEE Trans. Evol. Comput. 25(1): 1-20 (2021) - [j146]Xinye Cai
, Yushun Xiao
, Miqing Li
, Han Hu, Hisao Ishibuchi
, Xiaoping Li
:
A Grid-Based Inverted Generational Distance for Multi/Many-Objective Optimization. IEEE Trans. Evol. Comput. 25(1): 21-34 (2021) - [j145]Jesús Guillermo Falcón-Cardona
, Hisao Ishibuchi
, Carlos A. Coello Coello
, Michael Emmerich
:
On the Effect of the Cooperation of Indicator-Based Multiobjective Evolutionary Algorithms. IEEE Trans. Evol. Comput. 25(4): 681-695 (2021) - [j144]Linjun He
, Hisao Ishibuchi
, Anupam Trivedi
, Handing Wang
, Yang Nan
, Dipti Srinivasan
:
A Survey of Normalization Methods in Multiobjective Evolutionary Algorithms. IEEE Trans. Evol. Comput. 25(6): 1028-1048 (2021) - [j143]Wenhua Li
, Tao Zhang
, Rui Wang
, Hisao Ishibuchi
:
Weighted Indicator-Based Evolutionary Algorithm for Multimodal Multiobjective Optimization. IEEE Trans. Evol. Comput. 25(6): 1064-1078 (2021) - [j142]Suhang Gu
, Yusuke Nojima
, Hisao Ishibuchi
, Shitong Wang
:
Fuzzy Style K-Plane Clustering. IEEE Trans. Fuzzy Syst. 29(6): 1518-1532 (2021) - [j141]Te Zhang
, Zhaohong Deng
, Hisao Ishibuchi
, Lie Meng Pang
:
Robust TSK Fuzzy System Based on Semisupervised Learning for Label Noise Data. IEEE Trans. Fuzzy Syst. 29(8): 2145-2157 (2021) - [j140]Bin Qin
, Yusuke Nojima
, Hisao Ishibuchi
, Shitong Wang
:
Realizing Deep High-Order TSK Fuzzy Classifier by Ensembling Interpretable Zero-Order TSK Fuzzy Subclassifiers. IEEE Trans. Fuzzy Syst. 29(11): 3441-3455 (2021) - [c336]Lie Meng Pang, Hisao Ishibuchi
, Ke Shang:
Using a Genetic Algorithm-based Hyper-heuristic to Tune MOEA/D for a Set of Various Test Problems. CEC 2021: 1486-1494 - [c335]Longcan Chen, Lie Meng Pang, Hisao Ishibuchi
, Ke Shang:
Periodical Generation Update using an Unbounded External Archive for Multi-Objective Optimization. CEC 2021: 1912-1920 - [c334]Yang Nan, Ke Shang, Hisao Ishibuchi
, Linjun He
:
A Two-stage Hypervolume Contribution Approximation Method Based on R2 Indicator. CEC 2021: 2468-2475 - [c333]Qite Yang
, Zhenkun Wang
, Hisao Ishibuchi:
It Is Hard to Distinguish Between Dominance Resistant Solutions and Extremely Convex Pareto Optimal Solutions. EMO 2021: 3-14 - [c332]Ke Shang, Hisao Ishibuchi, Longcan Chen, Weiyu Chen, Lie Meng Pang:
Improving the Efficiency of R2HCA-EMOA. EMO 2021: 115-125 - [c331]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Using a Genetic Algorithm-Based Hyper-Heuristic to Tune MOEA/D for a Set of Benchmark Test Problems. EMO 2021: 164-177 - [c330]Yiming Peng, Hisao Ishibuchi:
Niching Diversity Estimation for Multi-modal Multi-objective Optimization. EMO 2021: 323-334 - [c329]Jinyuan Zhang, Hisao Ishibuchi:
Multiobjective Optimization with Fuzzy Classification-Assisted Environmental Selection. EMO 2021: 580-592 - [c328]Yifan Wang, Hisao Ishibuchi
, Jihua Zhu, Yaxiong Wang, Tao Dai:
Unsupervised Fuzzy Neural Network for Image Clustering. FUZZ-IEEE 2021: 1-6 - [c327]Linjun He
, Hisao Ishibuchi
, Dipti Srinivasan:
Metric for evaluating normalization methods in multiobjective optimization. GECCO 2021: 403-411 - [c326]Ke Shang, Hisao Ishibuchi
, Yang Nan:
Distance-based subset selection revisited. GECCO 2021: 439-447 - [c325]Ke Shang, Hisao Ishibuchi
, Weiyu Chen:
Greedy approximated hypervolume subset selection for many-objective optimization. GECCO 2021: 448-456 - [c324]Jinyuan Zhang, Hisao Ishibuchi
, Ke Shang, Linjun He
, Lie Meng Pang, Yiming Peng:
Environmental selection using a fuzzy classifier for multiobjective evolutionary algorithms. GECCO 2021: 485-492 - [c323]Yiming Peng, Hisao Ishibuchi
:
A Decomposition-based Hybrid Evolutionary Algorithm for Multi-modal Multi-objective Optimization. SMC 2021: 160-167 - [c322]Ke Shang, Hisao Ishibuchi
, Lie Meng Pang, Yang Nan:
Reference Point Specification for Greedy Hypervolume Subset Selection. SMC 2021: 168-175 - [c321]Weiyu Chen, Hisao Ishibuchi
, Ke Shang:
Clustering-Based Subset Selection in Evolutionary Multiobjective Optimization. SMC 2021: 468-475 - [c320]Lie Meng Pang, Ke Shang, Longcan Chen, Hisao Ishibuchi
, Weiyu Chen:
Proposal of a New Test Problem for Large-Scale Multi- and Many-Objective Optimization. SMC 2021: 484-491 - [c319]Yang Nan, Ke Shang, Hisao Ishibuchi
, Linjun He:
Improving Local Search Hypervolume Subset Selection in Evolutionary Multi-objective Optimization. SMC 2021: 751-757 - [c318]Yiping Liu, Liting Xu, Yuyan Han, Naoki Masuyama, Yusuke Nojima
, Hisao Ishibuchi
, Gary G. Yen:
Multi-Modal Multi-Objective Traveling Salesman Problem and its Evolutionary Optimizer. SMC 2021: 770-777 - [c317]Longcan Chen, Lie Meng Pang, Hisao Ishibuchi
, Ke Shang:
Periodical Weight Vector Update Using an Unbounded External Archive for Decomposition-Based Evolutionary Multi-Objective Optimization. SSCI 2021: 1-8 - [c316]Cheng Gong, Lie Meng Pang, Hisao Ishibuchi
:
Initial Population Generation Method and its Effects on MOEA/D. SSCI 2021: 1-8 - [e6]Hisao Ishibuchi
, Qingfu Zhang
, Ran Cheng
, Ke Li
, Hui Li, Handing Wang
, Aimin Zhou:
Evolutionary Multi-Criterion Optimization - 11th International Conference, EMO 2021, Shenzhen, China, March 28-31, 2021, Proceedings. Lecture Notes in Computer Science 12654, Springer 2021, ISBN 978-3-030-72061-2 [contents] - [i25]Yiming Peng, Hisao Ishibuchi:
Niching Diversity Estimation for Multi-modal Multi-objective Optimization. CoRR abs/2102.00383 (2021) - [i24]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Fast Greedy Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization. CoRR abs/2102.00941 (2021) - [i23]Naoki Masuyama, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi:
Multi-label Classification via Adaptive Resonance Theory-based Clustering. CoRR abs/2103.01511 (2021) - [i22]Ke Shang, Hisao Ishibuchi, Weiyu Chen, Yang Nan, Weiduo Liao:
Hypervolume-Optimal μ-Distributions on Line/Plane-based Pareto Fronts in Three Dimensions. CoRR abs/2104.09736 (2021) - [i21]Rahul Kumar Sevakula, Nishchal Kumar Verma, Hisao Ishibuchi:
On fine-tuning of Autoencoders for Fuzzy rule classifiers. CoRR abs/2106.11182 (2021) - [i20]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Clustering-Based Subset Selection in Evolutionary Multiobjective Optimization. CoRR abs/2108.08453 (2021) - 2020
- [j139]Yang Nan
, Ke Shang
, Hisao Ishibuchi
, Linjun He:
Reverse Strategy for Non-Dominated Archiving. IEEE Access 8: 119458-119469 (2020) - [j138]Lie Meng Pang
, Kai Meng Tay
, Chee Peng Lim
, Hisao Ishibuchi
:
A New Monotone Fuzzy Rule Relabeling Framework With Application to Failure Mode and Effect Analysis Methodology. IEEE Access 8: 144908-144930 (2020) - [j137]Lie Meng Pang
, Hisao Ishibuchi
, Ke Shang
:
Decomposition-Based Multi-Objective Evolutionary Algorithm Design Under Two Algorithm Frameworks. IEEE Access 8: 163197-163208 (2020) - [j136]Lie Meng Pang
, Hisao Ishibuchi
, Ke Shang
:
NSGA-II With Simple Modification Works Well on a Wide Variety of Many-Objective Problems. IEEE Access 8: 190240-190250 (2020) - [j135]Ryoji Tanabe
, Hisao Ishibuchi
:
An easy-to-use real-world multi-objective optimization problem suite. Appl. Soft Comput. 89: 106078 (2020) - [j134]Linjun He
, Ke Shang, Hisao Ishibuchi
:
Simultaneous use of two normalization methods in decomposition-based multi-objective evolutionary algorithms. Appl. Soft Comput. 92: 106316 (2020) - [j133]Jian Xiong
, Chao Zhang, Gang Kou
, Rui Wang
, Hisao Ishibuchi
, Fawaz E. Alsaadi:
Optimizing Long-Term Bank Financial Products Portfolio Problems with a Multiobjective Evolutionary Approach. Complex. 2020: 3106097:1-3106097:18 (2020) - [j132]Bach Hoai Nguyen
, Bing Xue
, Peter Andreae, Hisao Ishibuchi
, Mengjie Zhang
:
Multiple Reference Points-Based Decomposition for Multiobjective Feature Selection in Classification: Static and Dynamic Mechanisms. IEEE Trans. Evol. Comput. 24(1): 170-184 (2020) - [j131]Ke Shang
, Hisao Ishibuchi
, Xizi Ni
:
R2-Based Hypervolume Contribution Approximation. IEEE Trans. Evol. Comput. 24(1): 185-192 (2020) - [j130]Ryoji Tanabe
, Hisao Ishibuchi
:
A Review of Evolutionary Multimodal Multiobjective Optimization. IEEE Trans. Evol. Comput. 24(1): 193-200 (2020) - [j129]Yiping Liu
, Hisao Ishibuchi
, Naoki Masuyama
, Yusuke Nojima
:
Adapting Reference Vectors and Scalarizing Functions by Growing Neural Gas to Handle Irregular Pareto Fronts. IEEE Trans. Evol. Comput. 24(3): 439-453 (2020) - [j128]Yiping Liu
, Hisao Ishibuchi
, Gary G. Yen
, Yusuke Nojima
, Naoki Masuyama
:
Handling Imbalance Between Convergence and Diversity in the Decision Space in Evolutionary Multimodal Multiobjective Optimization. IEEE Trans. Evol. Comput. 24(3): 551-565 (2020) - [j127]Ryoji Tanabe
, Hisao Ishibuchi
:
A Framework to Handle Multimodal Multiobjective Optimization in Decomposition-Based Evolutionary Algorithms. IEEE Trans. Evol. Comput. 24(4): 720-734 (2020) - [j126]Ke Shang
, Hisao Ishibuchi
, Xizi Ni
:
Erratum to "R2-Based Hypervolume Contribution Approximation". IEEE Trans. Evol. Comput. 24(4): 807 (2020) - [j125]Ke Shang
, Hisao Ishibuchi
:
A New Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization. IEEE Trans. Evol. Comput. 24(5): 839-852 (2020) - [j124]Ryoji Tanabe
, Hisao Ishibuchi
:
An Analysis of Quality Indicators Using Approximated Optimal Distributions in a 3-D Objective Space. IEEE Trans. Evol. Comput. 24(5): 853-867 (2020) - [j123]Suhang Gu
, Yusuke Nojima
, Hisao Ishibuchi
, Shitong Wang
:
A Novel Classification Method From the Perspective of Fuzzy Social Networks Based on Physical and Implicit Style Features of Data. IEEE Trans. Fuzzy Syst. 28(2): 361-375 (2020) - [c315]Yuna Yamada, Naoki Masuyama, Narito Amako, Yusuke Nojima
, Chu Kiong Loo, Hisao Ishibuchi
:
Divisive Hierarchical Clustering Based on Adaptive Resonance Theory. CcS 2020: 1-6 - [c314]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Modified Distance-based Subset Selection for Evolutionary Multi-objective Optimization Algorithms. CEC 2020: 1-8 - [c313]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Lazy Greedy Hypervolume Subset Selection from Large Candidate Solution Sets. CEC 2020: 1-8 - [c312]Jesús Guillermo Falcón-Cardona
, Hisao Ishibuchi, Carlos A. Coello Coello:
Riesz s-energy-based Reference Sets for Multi-Objective optimization. CEC 2020: 1-8 - [c311]Ryuichi Hashimoto, Toshiki Urita, Naoki Masuyama, Yusuke Nojima
, Hisao Ishibuchi
:
Effects of Local Mating in Inter-task Crossover on the Performance of Decomposition-based Evolutionary Multiobjective Multitask optimization Algorithms. CEC 2020: 1-8 - [c310]Linjun He, Hisao Ishibuchi, Anupam Trivedi, Dipti Srinivasan:
Dynamic Normalization in MOEA/D for Multiobjective optimization. CEC 2020: 1-8 - [c309]Yiping Liu, Hisao Ishibuchi
, Gary G. Yen, Yusuke Nojima
, Naoki Masuyama, Yuyan Han:
On the Normalization in Evolutionary Multi-Modal Multi-Objective Optimization. CEC 2020: 1-8 - [c308]Yiming Peng, Hisao Ishibuchi:
A Decomposition-based Large-scale Multi-modal Multi-objective optimization Algorithm. CEC 2020: 1-8 - [c307]Hisao Ishibuchi
, Lie Meng Pang, Ke Shang:
A New Framework of Evolutionary Multi-Objective Algorithms with an Unbounded External Archive. ECAI 2020: 283-290 - [c306]Hisao Ishibuchi
, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima
:
Many-Objective Problems Are Not Always Difficult for Pareto Dominance-Based Evolutionary Algorithms. ECAI 2020: 291-298 - [c305]Yuichi Omozaki, Naoki Masuyama, Yusuke Nojima
, Hisao Ishibuchi
:
Multiobjective Fuzzy Genetics-Based Machine Learning for Multi-Label Classification. FUZZ-IEEE 2020: 1-8 - [c304]Hisao Ishibuchi, Hiroyuki Sato:
Evolutionary many-objective optimization. GECCO Companion 2020: 428-457 - [c303]Linjun He, Auraham Camacho, Hisao Ishibuchi
:
Another difficulty of inverted triangular pareto fronts for decomposition-based multi-objective algorithms. GECCO 2020: 498-506 - [c302]Hisao Ishibuchi
, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima
:
Effects of dominance resistant solutions on the performance of evolutionary multi-objective and many-objective algorithms. GECCO 2020: 507-515 - [c301]Yang Nan, Ke Shang, Hisao Ishibuchi
:
What is a good direction vector set for the R2-based hypervolume contribution approximation. GECCO 2020: 524-532 - [c300]Narito Amako, Naoki Masuyama, Chu Kiong Loo, Yusuke Nojima
, Yiping Liu, Hisao Ishibuchi
:
Multilayer Clustering Based on Adaptive Resonance Theory for Noisy Environments. IJCNN 2020: 1-8 - [c299]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Proposal of a Realistic Many-Objective Test Suite. PPSN (1) 2020: 201-214 - [c298]Ke Shang, Hisao Ishibuchi, Weiyu Chen, Lukás Adam
:
Hypervolume Optimal μ-Distributions on Line-Based Pareto Fronts in Three Dimensions. PPSN (2) 2020: 257-270 - [c297]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Algorithm Configurations of MOEA/D with an Unbounded External Archive. SMC 2020: 1087-1094 - [c296]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Population Size Specification for Fair Comparison of Multi-objective Evolutionary Algorithms. SMC 2020: 1095-1102 - [c295]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Numerical Analysis on Optimal Distributions of Solutions for Hypervolume Maximization. SMC 2020: 1103-1110 - [c294]Weiduo Liao
, Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Parallel Implementation of MOEA/D with Parallel Weight Vectors for Feature Selection. SMC 2020: 1524-1531 - [c293]Jesús Guillermo Falcón-Cardona
, Hisao Ishibuchi, Carlos A. Coello Coello:
Exploiting the Trade-off between Convergence and Diversity Indicators. SSCI 2020: 141-148 - [c292]Ke Shang, Hisao Ishibuchi, Yang Nan, Weiyu Chen:
Transformation-based Hypervolume Indicator: A Framework for Designing Hypervolume Variants. SSCI 2020: 157-164 - [c291]Naoki Masuyama, Yusuke Nojima
, Chu Kiong Loo, Hisao Ishibuchi:
Multi-label Classification Based on Adaptive Resonance Theory. SSCI 2020: 1913-1920 - [c290]Longcan Chen, Ke Shang, Hisao Ishibuchi:
Performance Comparison of Multi-Objective Evolutionary Algorithms on Simple and Difficult Many-Objective Test Problems. SSCI 2020: 2461-2468 - [i19]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Effects of Discretization of Decision and Objective Spaces on the Performance of Evolutionary Multiobjective Optimization Algorithms. CoRR abs/2003.09917 (2020) - [i18]Yiming Peng, Hisao Ishibuchi:
A Decomposition-based Large-scale Multi-modal Multi-objective Optimization Algorithm. CoRR abs/2004.09838 (2020) - [i17]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Solution Subset Selection for Final Decision Making in Evolutionary Multi-Objective Optimization. CoRR abs/2006.08156 (2020) - [i16]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Lazy Greedy Hypervolume Subset Selection from Large Candidate Solution Sets. CoRR abs/2007.02050 (2020) - [i15]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Algorithm Configurations of MOEA/D with an Unbounded External Archive. CoRR abs/2007.13352 (2020) - [i14]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Decomposition-Based Multi-Objective Evolutionary Algorithm Design under Two Algorithm Frameworks. CoRR abs/2008.07094 (2020) - [i13]Ryoji Tanabe, Hisao Ishibuchi:
An Analysis of Quality Indicators Using Approximated Optimal Distributions in a Three-dimensional Objective Space. CoRR abs/2009.12788 (2020) - [i12]Ryoji Tanabe, Hisao Ishibuchi:
An Easy-to-use Real-world Multi-objective Optimization Problem Suite. CoRR abs/2009.12867 (2020) - [i11]Ryoji Tanabe, Hisao Ishibuchi:
A Review of Evolutionary Multi-modal Multi-objective Optimization. CoRR abs/2009.13347 (2020) - [i10]Ryoji Tanabe, Hisao Ishibuchi:
A Framework to Handle Multi-modal Multi-objective Optimization in Decomposition-based Evolutionary Algorithms. CoRR abs/2009.14700 (2020) - [i9]Ryoji Tanabe, Hisao Ishibuchi:
Non-elitist Evolutionary Multi-objective Optimizers Revisited. CoRR abs/2009.14717 (2020) - [i8]Ryoji Tanabe, Hisao Ishibuchi:
A Niching Indicator-Based Multi-modal Many-objective Optimizer. CoRR abs/2010.00236 (2020) - [i7]Ryoji Tanabe, Hisao Ishibuchi:
Review and Analysis of Three Components of Differential Evolution Mutation Operator in MOEA/D-DE. CoRR abs/2010.00265 (2020) - [i6]Ryoji Tanabe, Hisao Ishibuchi:
An Analysis of Control Parameters of MOEA/D Under Two Different Optimization Scenarios. CoRR abs/2010.00818 (2020) - [i5]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Evolutionary Multi-Objective Optimization Algorithm Framework with Three Solution Sets. CoRR abs/2012.07319 (2020)
2010 – 2019
- 2019
- [j122]Muhammad Atif
, Siddique Latif
, Rizwan Ahmad
, Adnan Khalid Kiani
, Junaid Qadir
, Adeel Baig
, Hisao Ishibuchi
, Waseem Abbas:
Soft Computing Techniques for Dependable Cyber-Physical Systems. IEEE Access 7: 72030-72049 (2019) - [j121]Naoki Masuyama
, Chu Kiong Loo
, Hisao Ishibuchi
, Naoyuki Kubota
, Yusuke Nojima
, Yiping Liu:
Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning. IEEE Access 7: 76920-76936 (2019) - [j120]Hisao Ishibuchi:
Prof. Lotfi A. Zadeh [Editor's Remarks]. IEEE Comput. Intell. Mag. 14(1): 2 (2019) - [j119]Hisao Ishibuchi
:
Cashless Society [Editor's Remarks]. IEEE Comput. Intell. Mag. 14(2): 2 (2019) - [j118]Hisao Ishibuchi
:
AI and CI [Editor's Remarks]. IEEE Comput. Intell. Mag. 14(3): 2 (2019) - [j117]Hisao Ishibuchi
:
Last Editor's Remarks [Editor's Remarks]. IEEE Comput. Intell. Mag. 14(4): 2 (2019) - [j116]Ryoji Tanabe, Hisao Ishibuchi
:
Review and analysis of three components of the differential evolution mutation operator in MOEA/D-DE. Soft Comput. 23(23): 12843-12857 (2019) - [j115]Ryoji Tanabe, Hisao Ishibuchi
:
A niching indicator-based multi-modal many-objective optimizer. Swarm Evol. Comput. 49: 134-146 (2019) - [j114]Zhenkun Wang
, Yew-Soon Ong
, Hisao Ishibuchi
:
On Scalable Multiobjective Test Problems With Hardly Dominated Boundaries. IEEE Trans. Evol. Comput. 23(2): 217-231 (2019) - [j113]Wenjing Hong, Ke Tang, Aimin Zhou, Hisao Ishibuchi
, Xin Yao
:
A Scalable Indicator-Based Evolutionary Algorithm for Large-Scale Multiobjective Optimization. IEEE Trans. Evol. Comput. 23(3): 525-537 (2019) - [j112]Zekang Bian, Hisao Ishibuchi
, Shitong Wang
:
Joint Learning of Spectral Clustering Structure and Fuzzy Similarity Matrix of Data. IEEE Trans. Fuzzy Syst. 27(1): 31-44 (2019) - [c289]Hisao Ishibuchi, Yiming Peng, Ke Shang:
A Scalable Multimodal Multiobjective Test Problem. CEC 2019: 310-317 - [c288]Yiping Liu, Hisao Ishibuchi
, Yusuke Nojima
, Naoki Masuyama, Yuyan Han:
Searching for Local Pareto Optimal Solutions: A Case Study on Polygon-Based Problems. CEC 2019: 896-903 - [c287]Kanzhen Wan, Cheng He
, Auraham Camacho
, Ke Shang, Ran Cheng
, Hisao Ishibuchi
:
A Hybrid Surrogate-Assisted Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization. CEC 2019: 2018-2025 - [c286]Hisao Ishibuchi
, Linjun He
, Ke Shang:
Regular Pareto Front Shape is not Realistic. CEC 2019: 2034-2041 - [c285]Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima
, Hisao Ishibuchi
:
A Multiobjective Test Suite with Hexagon Pareto Fronts and Various Feasible Regions. CEC 2019: 2058-2065 - [c284]Hisao Ishibuchi
, Ryo Imada, Naoki Masuyama, Yusuke Nojima
:
Two-Layered Weight Vector Specification in Decomposition-Based Multi-Objective Algorithms for Many-Objective Optimization Problems. CEC 2019: 2434-2441 - [c283]Auraham Camacho, Gregorio Toscano Pulido, Ricardo Landa Becerra, Hisao Ishibuchi:
Indicator-Based Weight Adaptation for Solving Many-Objective Optimization Problems. EMO 2019: 216-228 - [c282]Hisao Ishibuchi, Ryo Imada, Naoki Masuyama, Yusuke Nojima
:
Comparison of Hypervolume, IGD and IGD+ from the Viewpoint of Optimal Distributions of Solutions. EMO 2019: 332-345 - [c281]Yusuke Nojima
, Takafumi Fukase, Yiping Liu, Naoki Masuyama, Hisao Ishibuchi
:
Constrained multiobjective distance minimization problems. GECCO 2019: 586-594 - [c280]Ryoji Tanabe, Hisao Ishibuchi
:
Non-elitist evolutionary multi-objective optimizers revisited. GECCO 2019: 612-619 - [c279]Hisao Ishibuchi, Hiroyuki Sato:
Evolutionary many-objective optimization. GECCO (Companion) 2019: 614-661 - [c278]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Effects of Discretization of Decision and Objective Spaces on the Performance of Evolutionary Multi-objective Optimization Algorithms. SSCI 2019: 1826-1833 - [c277]Linjun He, Yang Nan, Ke Shang, Hisao Ishibuchi:
A Study of the Naïve Objective Space Normalization Method in MOEA/D. SSCI 2019: 1834-1840 - [c276]Weiduo Liao
, Ke Shang, Lie Meng Pang, Hisao Ishibuchi:
Weak Convergence Detection-based Dynamic Reference Point Specification in SMS-EMOA. SSCI 2019: 1841-1848 - [c275]Hisao Ishibuchi, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima
:
Optimal Distributions of Solutions for Hypervolume Maximization on Triangular and Inverted Triangular Pareto Fronts of Four-Objective Problems. SSCI 2019: 1857-1864 - [c274]Yiming Peng, Hisao Ishibuchi, Ke Shang:
Multi-modal Multi-objective Optimization: Problem Analysis and Case Studies. SSCI 2019: 1865-1872 - [c273]Mengjun Ming, Rui Wang
, Tao Zhang
, Hisao Ishibuchi
:
A dual-grid dual-phase strategy for constrained multi-objective optimization. SSCI 2019: 1881-1888 - [c272]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Offline Automatic Parameter Tuning of MOEA/D Using Genetic Algorithm. SSCI 2019: 1889-1897 - [c271]Naoki Masuyama, Narito Amako, Yusuke Nojima
, Yiping Liu, Chu Kiong Loo, Hisao Ishibuchi
:
Fast Topological Adaptive Resonance Theory Based on Correntropy Induced Metric. SSCI 2019: 2215-2221 - [c270]Ryuichi Hashimoto, Naoki Masuyama, Yusuke Nojima
, Hisao Ishibuchi:
Effect of Solution Information Sharing between Tasks on the Search Ability of Evolutionary Multiobjective Multitasking Algorithms. SSCI 2019: 2671-2678 - 2018
- [j111]Kaiwen Li
, Rui Wang
, Tao Zhang
, Hisao Ishibuchi
:
Evolutionary Many-Objective Optimization: A Comparative Study of the State-of-the-Art. IEEE Access 6: 26194-26214 (2018) - [j110]Bin Xin
, Lu Chen, Jie Chen, Hisao Ishibuchi
, Kaoru Hirota, Bo Liu
:
Interactive Multiobjective Optimization: A Review of the State-of-the-Art. IEEE Access 6: 41256-41279 (2018) - [j109]Ryoji Tanabe, Hisao Ishibuchi
:
An analysis of control parameters of MOEA/D under two different optimization scenarios. Appl. Soft Comput. 70: 22-40 (2018) - [j108]Hisao Ishibuchi:
Father of Fuzzy Logic [Editor's Remarks]. IEEE Comput. Intell. Mag. 13(1): 2 (2018) - [j107]Hisao Ishibuchi:
IEEE CIM Survey Results [Editor's Remarks]. IEEE Comput. Intell. Mag. 13(2): 2 (2018) - [j106]Hisao Ishibuchi:
One Year in China [Editor's Remarks]. IEEE Comput. Intell. Mag. 13(3): 2 (2018) - [j105]Hisao Ishibuchi:
CIS Sponsored Conferences in 2019 [Editor's Remarks]. IEEE Comput. Intell. Mag. 13(4): 2 (2018) - [j104]Hisao Ishibuchi
, Ryo Imada, Yu Setoguchi, Yusuke Nojima
:
How to Specify a Reference Point in Hypervolume Calculation for Fair Performance Comparison. Evol. Comput. 26(3) (2018) - [j103]Rui Wang
, Shiming Lai, Guohua Wu
, Lining Xing, Ling Wang
, Hisao Ishibuchi
:
Multi-clustering via evolutionary multi-objective optimization. Inf. Sci. 450: 128-140 (2018) - [j102]Yaochu Jin
, Kaisa Miettinen
, Hisao Ishibuchi
:
Guest Editorial Evolutionary Many-Objective Optimization. IEEE Trans. Evol. Comput. 22(1): 1-2 (2018) - [j101]Rui Wang
, Zhongbao Zhou, Hisao Ishibuchi
, Tianjun Liao, Tao Zhang
:
Localized Weighted Sum Method for Many-Objective Optimization. IEEE Trans. Evol. Comput. 22(1): 3-18 (2018) - [j100]Heiner Zille
, Hisao Ishibuchi
, Sanaz Mostaghim
, Yusuke Nojima
:
A Framework for Large-Scale Multiobjective Optimization Based on Problem Transformation. IEEE Trans. Evol. Comput. 22(2): 260-275 (2018) - [j99]Manuel Chica
, Raymond Chiong
, Michael Kirley
, Hisao Ishibuchi
:
A Networked N-Player Trust Game and Its Evolutionary Dynamics. IEEE Trans. Evol. Comput. 22(6): 866-878 (2018) - [j98]Hisao Ishibuchi
, Ryo Imada, Yu Setoguchi, Yusuke Nojima
:
Reference Point Specification in Inverted Generational Distance for Triangular Linear Pareto Front. IEEE Trans. Evol. Comput. 22(6): 961-975 (2018) - [j97]Yuanpeng Zhang
, Hisao Ishibuchi
, Shitong Wang
:
Deep Takagi-Sugeno-Kang Fuzzy Classifier With Shared Linguistic Fuzzy Rules. IEEE Trans. Fuzzy Syst. 26(3): 1535-1549 (2018) - [j96]Ta Zhou
, Hisao Ishibuchi
, Shitong Wang
:
Stacked Blockwise Combination of Interpretable TSK Fuzzy Classifiers by Negative Correlation Learning. IEEE Trans. Fuzzy Syst. 26(6): 3327-3341 (2018) - [c269]Hisao Ishibuchi
, Ryo Imada, Naoki Masuyama, Yusuke Nojima
:
Dynamic Specification of a Reference Point for Hypervolume Calculation in SMS-EMOA. CEC 2018: 1-8 - [c268]Hisao Ishibuchi
, Takefumi Fukase, Naoki Masuyama, Yusuke Nojima
:
Dual-grid model of MOEA/D for evolutionary constrained multiobjective optimization. GECCO 2018: 665-672 - [c267]Ke Shang, Hisao Ishibuchi
, Min-Ling Zhang
, Yiping Liu:
A new R2 indicator for better hypervolume approximation. GECCO 2018: 745-752 - [c266]Ryuichi Hashimoto, Hisao Ishibuchi, Naoki Masuyama, Yusuke Nojima
:
Analysis of evolutionary multi-tasking as an island model. GECCO (Companion) 2018: 1894-1897 - [c265]Chenxu Hu, Hisao Ishibuchi:
Incorporation of a decision space diversity maintenance mechanism into MOEA/D for multi-modal multi-objective optimization. GECCO (Companion) 2018: 1898-1901 - [c264]Xizi Ni, Hisao Ishibuchi, Kanzhen Wan, Ke Shang, Chukun Zhuang:
Weight vector grid with new archive update mechanism for multi-objective optimization. GECCO (Companion) 2018: 1906-1909 - [c263]Ryoji Tanabe, Hisao Ishibuchi
:
A Decomposition-Based Evolutionary Algorithm for Multi-modal Multi-objective Optimization. PPSN (1) 2018: 249-261 - [c262]Yiping Liu, Hisao Ishibuchi
, Yusuke Nojima
, Naoki Masuyama, Ke Shang:
A Double-Niched Evolutionary Algorithm and Its Behavior on Polygon-Based Problems. PPSN (1) 2018: 262-273 - [c261]Yiping Liu, Hisao Ishibuchi
, Yusuke Nojima
, Naoki Masuyama, Ke Shang:
Improving 1by1EA to Handle Various Shapes of Pareto Fronts. PPSN (1) 2018: 311-322 - [c260]Hisao Ishibuchi
, Ryo Imada, Naoki Masuyama, Yusuke Nojima
:
Use of Two Reference Points in Hypervolume-Based Evolutionary Multiobjective Optimization Algorithms. PPSN (1) 2018: 384-396 - [c259]Naoki Masuyama, Yuki Tanigaki, Yusuke Nojima
, Hisao Ishibuchi
:
Multiobjective Evolutionary Data Mining for Performance Improvement of Evolutionary Multiobjective Optimization. SMC 2018: 745-750 - [c258]Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima
, Hisao Ishibuchi
:
Performance Comparison of Multiobjective Evolutionary Algorithms on Problems with Partially Different Properties from Popular Test Suites. SMC 2018: 769-774 - [c257]Naoki Masuyama, Chu Kiong Loo, Hisao Ishibuchi
, Yusuke Nojima
, Yiping Lin:
Topological Kernel Bayesian ARTMAP. WAC 2018: 1-5 - [i4]Muhammad Atif, Siddique Latif, Rizwan Ahmad, Adnan Khalid Kiani, Junaid Qadir, Adeel Baig, Hisao Ishibuchi, Waseem Abbas:
Soft Computing Techniques for Dependable Cyber-Physical Systems. CoRR abs/1801.10472 (2018) - 2017
- [j95]Ryoji Tanabe
, Hisao Ishibuchi
, Akira Oyama:
Benchmarking Multi- and Many-Objective Evolutionary Algorithms Under Two Optimization Scenarios. IEEE Access 5: 19597-19619 (2017) - [j94]Rui Wang
, Jian Xiong, Hisao Ishibuchi
, Guohua Wu
, Tao Zhang
:
On the effect of reference point in MOEA/D for multi-objective optimization. Appl. Soft Comput. 58: 25-34 (2017) - [j93]Hisao Ishibuchi:
New Journal, New Editor-in-Chief and New VP for Publications [Editor's Remarks]. IEEE Comput. Intell. Mag. 12(1): 2 (2017) - [j92]Hisao Ishibuchi:
Smart World [Editor's Remarks]. IEEE Comput. Intell. Mag. 12(2): 2 (2017) - [j91]Hisao Ishibuchi:
After 30 Years of Work in Osaka [Editor's Remarks]. IEEE Comput. Intell. Mag. 12(3): 2 (2017) - [j90]Hisao Ishibuchi:
End of Second Term as Editor-in-Chief [Editor's Remarks]. IEEE Comput. Intell. Mag. 12(4): 3 (2017) - [j89]Zhenkun Wang, Qingfu Zhang
, Hui Li, Hisao Ishibuchi
, Licheng Jiao
:
On the use of two reference points in decomposition based multiobjective evolutionary algorithms. Swarm Evol. Comput. 34: 89-102 (2017) - [j88]Hisao Ishibuchi
, Yu Setoguchi, Hiroyuki Masuda, Yusuke Nojima
:
Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes. IEEE Trans. Evol. Comput. 21(2): 169-190 (2017) - [j87]Ta Zhou, Hisao Ishibuchi
, Shitong Wang
:
Stacked-Structure-Based Hierarchical Takagi-Sugeno-Kang Fuzzy Classification Through Feature Augmentation. IEEE Trans. Emerg. Top. Comput. Intell. 1(6): 421-436 (2017) - [j86]Antoaneta Serguieva, Hisao Ishibuchi
, Ronald R. Yager, Vasile Palade:
Guest Editorial Special Issue on Fuzzy Techniques in Financial Modeling and Simulation. IEEE Trans. Fuzzy Syst. 25(2): 245-248 (2017) - [j85]Xiaoqing Gu
, Fu-Lai Chung
, Hisao Ishibuchi
, Shitong Wang:
Imbalanced TSK Fuzzy Classifier by Cross-Class Bayesian Fuzzy Clustering and Imbalance Learning. IEEE Trans. Syst. Man Cybern. Syst. 47(8): 2005-2020 (2017) - [c256]Hisao Ishibuchi, Ryo Imada, Yu Setoguchi, Yusuke Nojima
:
Hypervolume Subset Selection for Triangular and Inverted Triangular Pareto Fronts of Three-Objective Problems. FOGA 2017: 95-110 - [c255]Yusuke Nojima
, Koki Arahari, Shuji Takemura, Hisao Ishibuchi
:
Multiobjective fuzzy genetics-based machine learning based on MOEA/D with its modifications. FUZZ-IEEE 2017: 1-6 - [c254]Bach Hoai Nguyen, Bing Xue, Hisao Ishibuchi
, Peter Andreae, Mengjie Zhang:
Multiple reference points MOEA/D for feature selection. GECCO (Companion) 2017: 157-158 - [c253]Hisao Ishibuchi
, Ryo Imada, Yu Setoguchi, Yusuke Nojima
:
Reference point specification in hypervolume calculation for fair comparison and efficient search. GECCO 2017: 585-592 - [c252]Yusuke Nojima
, Yuki Tanigaki, Hisao Ishibuchi
:
Multiobjective data mining from solutions by evolutionary multiobjective optimization. GECCO 2017: 617-624 - [c251]Yusuke Nojima
, Shuji Takemura, Kazuhiro Watanabe, Hisao Ishibuchi
:
Michigan-style fuzzy GBML with (1+1)-ES generation update and multi-pattern rule generation. IFSA-SCIS 2017: 1-6 - [c250]Yuki Tanigaki, Yusuke Nojima
, Hisao Ishibuchi
:
Performance comparison of EMO algorithms on test problems with different search space shape. IFSA-SCIS 2017: 1-6 - [c249]Ken Doi, Ryo Imada, Yusuke Nojima
, Hisao Ishibuchi:
Use of Inverted Triangular Weight Vectors in Decomposition-Based Many-Objective Algorithms. SEAL 2017: 321-333 - [c248]Hisao Ishibuchi
, Ryo Imada, Ken Doi, Yusuke Nojima
:
Use of inverted triangular weight vectors in decomposition-based multiobjective algorithms. SMC 2017: 373-378 - [i3]Yuan Yuan, Yew-Soon Ong, Liang Feng, A. Kai Qin, Abhishek Gupta, Bingshui Da, Qingfu Zhang, Kay Chen Tan, Yaochu Jin, Hisao Ishibuchi:
Evolutionary Multitasking for Multiobjective Continuous Optimization: Benchmark Problems, Performance Metrics and Baseline Results. CoRR abs/1706.02766 (2017) - 2016
- [j84]Hisao Ishibuchi:
Second Term as Editor-in-Chief [Editor's Remarks]. IEEE Comput. Intell. Mag. 11(1): 2 (2016) - [j83]Hisao Ishibuchi:
CIS Distinguished Lecturers Program Editor's Remarks. IEEE Comput. Intell. Mag. 11(2): 2 (2016) - [j82]Hisao Ishibuchi:
Power of a Single Photo in the Big Data Era [Editor's Remarks]. IEEE Comput. Intell. Mag. 11(3): 2 (2016) - [j81]Hisao Ishibuchi:
IEEE Standards [Editor's Remarks]. IEEE Comput. Intell. Mag. 11(4): 2 (2016) - [j80]Kaname Narukawa, Yu Setoguchi, Yuki Tanigaki, Markus Olhofer, Bernhard Sendhoff
, Hisao Ishibuchi
:
Preference representation using Gaussian functions on a hyperplane in evolutionary multi-objective optimization. Soft Comput. 20(7): 2733-2757 (2016) - [j79]Hisao Ishibuchi
, Hiroyuki Masuda, Yusuke Nojima
:
Pareto Fronts of Many-Objective Degenerate Test Problems. IEEE Trans. Evol. Comput. 20(5): 807-813 (2016) - [j78]Zhaohong Deng, Yizhang Jiang, Fu-Lai Chung
, Hisao Ishibuchi
, Kup-Sze Choi
, Shitong Wang:
Transfer Prototype-Based Fuzzy Clustering. IEEE Trans. Fuzzy Syst. 24(5): 1210-1232 (2016) - [j77]Zhaohong Deng, Yizhang Jiang, Hisao Ishibuchi
, Kup-Sze Choi
, Shitong Wang:
Enhanced Knowledge-Leverage-Based TSK Fuzzy System Modeling for Inductive Transfer Learning. ACM Trans. Intell. Syst. Technol. 8(1): 11:1-11:21 (2016) - [c247]Takahiko Sudo, Kazushi Goto, Yusuke Nojima
, Hisao Ishibuchi
:
Further analysis on strange evolution behavior of 7-bit binary string strategies in iterated prisoner's dilemma game. CEC 2016: 335-342 - [c246]Hisao Ishibuchi
, Hiroyuki Masuda, Yusuke Nojima
:
Sensitivity of performance evaluation results by inverted generational distance to reference points. CEC 2016: 1107-1114 - [c245]Hisao Ishibuchi
, Ken Doi, Yusuke Nojima
:
Characteristics of many-objective test problems and penalty parameter specification in MOEA/D. CEC 2016: 1115-1122 - [c244]Hisao Ishibuchi
, Yu Setoguchi, Hiroyuki Masuda, Yusuke Nojima
:
How to compare many-objective algorithms under different settings of population and archive sizes. CEC 2016: 1149-1156 - [c243]Yusuke Nojima
, Hisao Ishibuchi
:
Effects of parallel distributed implementation on the search performance of Pittsburgh-style genetics-based machine learning algorithms. CEC 2016: 2193-2200 - [c242]Yuki Tanigaki, Yusuke Nojima
, Hisao Ishibuchi
:
Meta-optimization based multi-objective test problem generation using WFG toolkit. CEC 2016: 2768-2775 - [c241]Hiroyuki Masuda, Yusuke Nojima
, Hisao Ishibuchi
:
Common properties of scalable multiobjective problems and a new framework of test problems. CEC 2016: 3011-3018 - [c240]Hisao Ishibuchi
, Ryo Imada, Yu Setoguchi, Yusuke Nojima
:
Performance comparison of NSGA-II and NSGA-III on various many-objective test problems. CEC 2016: 3045-3052 - [c239]Yusuke Nojima
, Hisao Ishibuchi
:
Multiobjective fuzzy genetics-based machine learning with a reject option. FUZZ-IEEE 2016: 1405-1412 - [c238]Heiner Zille, Hisao Ishibuchi
, Sanaz Mostaghim
, Yusuke Nojima
:
Weighted Optimization Framework for Large-scale Multi-objective Optimization. GECCO (Companion) 2016: 83-84 - [c237]Binhui Chen, Rong Qu
, Ruibin Bai
, Hisao Ishibuchi
:
An Investigation on Compound Neighborhoods for VRPTW. ICORES (Selected Papers) 2016: 3-19 - [c236]Binhui Chen, Rong Qu, Ruibin Bai
, Hisao Ishibuchi:
A Variable Neighbourhood Search Algorithm with Compound Neighbourhoods for VRPTW. ICORES 2016: 25-35 - [c235]Hisao Ishibuchi
, Ken Doi, Yusuke Nojima
:
Use of Piecewise Linear and Nonlinear Scalarizing Functions in MOEA/D. PPSN 2016: 503-513 - [c234]Takahiro Funakoshi, Yusuke Nojima
, Hisao Ishibuchi:
Effects of Different Implementations of a Real Random Number Generator on the Search Behavior of Multiobjective Evolutionary Algorithms. SCIS&ISIS 2016: 172-177 - [c233]Hisao Ishibuchi
, Ken Doi, Yusuke Nojima
:
Reference point specification in MOEA/D for multi-objective and many-objective problems. SMC 2016: 4015-4020 - [c232]Rui Wang
, Hisao Ishibuchi
, Yan Zhang, Xiaojun Zheng, Tao Zhang
:
On the effect of localized PBI method in MOEA/D for multi-objective optimization. SSCI 2016: 1-8 - [c231]Heiner Zille, Hisao Ishibuchi
, Sanaz Mostaghim
, Yusuke Nojima
:
Mutation operators based on variable grouping for multi-objective large-scale optimization. SSCI 2016: 1-8 - 2015
- [j76]Hisao Ishibuchi
:
Top Three News Stories on IEEE CIM in 2014 [Editor's Remarks]. IEEE Comput. Intell. Mag. 10(1): 2 (2015) - [j75]Hisao Ishibuchi
:
Traveling with My Laptop [Editor's Remarks]. IEEE Comput. Intell. Mag. 10(2): 2 (2015) - [j74]Hisao Ishibuchi:
WCCI 2006 and WCCI 2016 in Vancouver [Editor's Remarks]. IEEE Comput. Intell. Mag. 10(3): 2 (2015) - [j73]Hisao Ishibuchi:
Talking with Young Researchers [Editor's Remarks]. IEEE Comput. Intell. Mag. 10(4): 2 (2015) - [j72]Yizhang Jiang, Korris Fu-Lai Chung
, Hisao Ishibuchi
, Zhaohong Deng, Shitong Wang:
Multitask TSK Fuzzy System Modeling by Mining Intertask Common Hidden Structure. IEEE Trans. Cybern. 45(3): 548-561 (2015) - [j71]Xin Gu, Fu-Lai Chung
, Hisao Ishibuchi
, Shitong Wang:
Multitask Coupled Logistic Regression and its Fast Implementation for Large Multitask Datasets. IEEE Trans. Cybern. 45(9): 1953-1966 (2015) - [j70]Hisao Ishibuchi
, Naoya Akedo, Yusuke Nojima
:
Behavior of Multiobjective Evolutionary Algorithms on Many-Objective Knapsack Problems. IEEE Trans. Evol. Comput. 19(2): 264-283 (2015) - [c230]Yusuke Nojima
, Yuji Takahashi, Hisao Ishibuchi
:
Application of Parallel Distributed Implementation to Multiobjective Fuzzy Genetics-Based Machine Learning. ACIIDS (1) 2015: 462-471 - [c229]Yuji Takahashi, Yusuke Nojima
, Hisao Ishibuchi
:
Rotation effects of objective functions in parallel distributed multiobjective fuzzy genetics-based machine learning. ASCC 2015: 1-6 - [c228]Yuki Tanigaki, Hiroyuki Masuda, Yu Setoguchi, Yusuke Nojima
, Hisao Ishibuchi
:
Algorithm structure optimization by choosing operators in multiobjective genetic local search. CEC 2015: 854-861 - [c227]Takahiko Sudo, Kazushi Goto, Yusuke Nojima
, Hisao Ishibuchi
:
Effects of ensemble action selection with different usage of player's memory resource on the evolution of cooperative strategies for iterated prisoner's dilemma game. CEC 2015: 1505-1512 - [c226]Hisao Ishibuchi
, Hiroyuki Masuda, Yusuke Nojima
:
Comparing solution sets of different size in evolutionary many-objective optimization. CEC 2015: 2859-2866 - [c225]Yusuke Nojima
, Kazuhiro Watanabe, Hisao Ishibuchi
:
Effects of heuristic rule generation from multiple patterns in multiobjective fuzzy genetics-Based machine learning. CEC 2015: 2996-3003 - [c224]Takahiko Sudo, Kazushi Goto, Yusuke Nojima
, Hisao Ishibuchi
:
Strange evolution behavior of 7-bit binary string strategies in iterated prisoner's dilemma game. CEC 2015: 3346-3353 - [c223]Hisao Ishibuchi
, Hiroyuki Masuda, Yuki Tanigaki, Yusuke Nojima
:
Modified Distance Calculation in Generational Distance and Inverted Generational Distance. EMO (2) 2015: 110-125 - [c222]Yu Setoguchi, Kaname Narukawa, Hisao Ishibuchi
:
A Knee-Based EMO Algorithm with an Efficient Method to Update Mobile Reference Points. EMO (1) 2015: 202-217 - [c221]Hisao Ishibuchi
, Yusuke Nojima
:
Handling a training dataset as a black-box model for privacy preserving in fuzzy GBML algorithms. FUZZ-IEEE 2015: 1-8 - [c220]Yusuke Nojima
, Kazuhiro Watanabe, Hisao Ishibuchi
:
Simple modifications on heuristic rule generation and rule evaluation in Michigan-style fuzzy genetics-based machine learning. FUZZ-IEEE 2015: 1-8 - [c219]Hisao Ishibuchi
, Hiroyuki Masuda, Yusuke Nojima
:
A Study on Performance Evaluation Ability of a Modified Inverted Generational Distance Indicator. GECCO 2015: 695-702 - [c218]Hisao Ishibuchi
, Ken Doi, Hiroyuki Masuda, Yusuke Nojima
:
Relation Between Weight Vectors and Solutions in MOEA/D. SSCI 2015: 861-868 - [c217]Yusuke Nojima
, Kazuhiro Watanabe, Hisao Ishibuchi
:
Variants of heuristic rule generation from multiple patterns in Michigan-style fuzzy genetics-based machine learning. TAAI 2015: 427-432 - [p15]Hisao Ishibuchi
, Yusuke Nojima
:
Multiobjective Genetic Fuzzy Systems. Handbook of Computational Intelligence 2015: 1479-1498 - [e5]Adnan Yazici, Nikhil R. Pal, Uzay Kaymak, Trevor Martin, Hisao Ishibuchi, Chin-Teng Lin, João M. C. Sousa, Bülent Tütmez:
2015 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015, Istanbul, Turkey, August 2-5, 2015. IEEE 2015, ISBN 978-1-4673-7428-6 [contents] - 2014
- [j69]Huynh Thi Thanh Binh, Lam Thu Bui
, Nguyen Sy Thai Ha, Hisao Ishibuchi
:
A multi-objective approach for solving the survivable network design problem with simultaneous unicast and anycast flows. Appl. Soft Comput. 24: 1145-1154 (2014) - [j68]Hisao Ishibuchi
:
Message from the New Editor-in-Chief [Editor's Remarks]. IEEE Comput. Intell. Mag. 9(1): 2 (2014) - [j67]Hisao Ishibuchi
:
Big Data Era [Editor's Remarks]. IEEE Comput. Intell. Mag. 9(3): 2-11 (2014) - [j66]Min Xu, Hisao Ishibuchi
, Xin Gu, Shitong Wang:
Dm-KDE: dynamical kernel density estimation by sequences of KDE estimators with fixed number of components over data streams. Frontiers Comput. Sci. 8(4): 563-580 (2014) - [j65]Chin Hooi Tan, Keem Siah Yap
, Hisao Ishibuchi
, Yusuke Nojima
, Hwa Jen Yap
:
Application of Fuzzy Inference Rules to Early Semi-automatic Estimation of Activity Duration in Software Project Management. IEEE Trans. Hum. Mach. Syst. 44(5): 678-688 (2014) - [c216]Giovanni Acampora
, Hisao Ishibuchi
, Autilia Vitiello
:
A comparison of multi-objective evolutionary algorithms for the ontology meta-matching problem. IEEE Congress on Evolutionary Computation 2014: 413-420 - [c215]Takahiko Sudo, Yusuke Nojima
, Hisao Ishibuchi
:
Effects of ensemble action selection on the evolution of iterated prisoner's dilemma game strategies. IEEE Congress on Evolutionary Computation 2014: 1195-1201 - [c214]Hiroyuki Masuda, Yusuke Nojima
, Hisao Ishibuchi
:
Visual examination of the behavior of EMO algorithms for many-objective optimization with many decision variables. IEEE Congress on Evolutionary Computation 2014: 2633-2640 - [c213]Hisao Ishibuchi
, Hiroyuki Masuda, Yuki Tanigaki, Yusuke Nojima
:
Difficulties in specifying reference points to calculate the inverted generational distance for many-objective optimization problems. MCDM 2014: 170-177 - [c212]Hisao Ishibuchi
, Hiroyuki Masuda, Yuki Tanigaki, Yusuke Nojima
:
Review of coevolutionary developments of evolutionary multi-objective and many-objective algorithms and test problems. MCDM 2014: 178-184 - [c211]Yuji Takahashi, Yusuke Nojima
, Hisao Ishibuchi
:
Hybrid fuzzy genetics-based machine learning with entropy-based inhomogeneous interval discretization. FUZZ-IEEE 2014: 1512-1517 - [c210]Hisao Ishibuchi
, Hiroyuki Masuda, Yusuke Nojima
:
Meta-level multi-objective formulations of set optimization for multi-objective optimization problems: multi-reference point approach to hypervolume maximization. GECCO (Companion) 2014: 89-90 - [c209]Kaname Narukawa, Yuki Tanigaki, Hisao Ishibuchi
:
Evolutionary many-objective optimization using preference on hyperplane. GECCO (Companion) 2014: 91-92 - [c208]Hisao Ishibuchi
, Takahiko Sudo, Yusuke Nojima
:
Archive Management in Interactive Evolutionary Computation with Minimum Requirement for Human User's Fitness Evaluation Ability. ICAISC (1) 2014: 360-371 - [c207]Hisao Ishibuchi
, Yuki Tanigaki, Hiroyuki Masuda, Yusuke Nojima
:
Distance-Based Analysis of Crossover Operators for Many-Objective Knapsack Problems. PPSN 2014: 600-610 - [c206]Yuki Tanigaki, Kaname Narukawa, Yusuke Nojima
, Hisao Ishibuchi
:
Preference-based NSGA-II for many-objective knapsack problems. SCIS&ISIS 2014: 637-642 - [c205]Yusuke Nojima
, Yuji Takahashi, Hisao Ishibuchi
:
Genetic lateral tuning of membership functions as post-processing for hybrid fuzzy genetics-based machine learning. SCIS&ISIS 2014: 667-672 - [c204]Hisao Ishibuchi
, Hiroyuki Masuda, Yusuke Nojima
:
Selecting a small number of non-dominated solutions to be presented to the decision maker. SMC 2014: 3816-3821 - [e4]Grant Dick, Will N. Browne, Peter A. Whigham, Mengjie Zhang, Lam Thu Bui, Hisao Ishibuchi, Yaochu Jin, Xiaodong Li, Yuhui Shi, Pramod Singh, Kay Chen Tan, Ke Tang:
Simulated Evolution and Learning - 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, 2014. Proceedings. Lecture Notes in Computer Science 8886, Springer 2014, ISBN 978-3-319-13562-5 [contents] - 2013
- [j64]Rafael Alcalá
, Yusuke Nojima
, Hisao Ishibuchi
, Francisco Herrera:
Special Issue on "Evolutionary Fuzzy Systems" EFSs. Knowl. Based Syst. 54: 1-2 (2013) - [j63]Hisao Ishibuchi
, Yusuke Nojima
:
Repeated double cross-validation for choosing a single solution in evolutionary multi-objective fuzzy classifier design. Knowl. Based Syst. 54: 22-31 (2013) - [j62]Michela Fazzolari, Rafael Alcalá
, Yusuke Nojima
, Hisao Ishibuchi
, Francisco Herrera
:
A Review of the Application of Multiobjective Evolutionary Fuzzy Systems: Current Status and Further Directions. IEEE Trans. Fuzzy Syst. 21(1): 45-65 (2013) - [j61]Hisao Ishibuchi
, Shingo Mihara, Yusuke Nojima
:
Parallel Distributed Hybrid Fuzzy GBML Models With Rule Set Migration and Training Data Rotation. IEEE Trans. Fuzzy Syst. 21(2): 355-368 (2013) - [j60]Zhaohong Deng, Yizhang Jiang, Fu-Lai Chung
, Hisao Ishibuchi
, Shitong Wang:
Knowledge-Leverage-Based Fuzzy System and Its Modeling. IEEE Trans. Fuzzy Syst. 21(4): 597-609 (2013) - [c203]Hisao Ishibuchi
, Masakazu Yamane, Yusuke Nojima
:
Learning from multiple data sets with different missing attributes and privacy policies: Parallel distributed fuzzy genetics-based machine learning approach. IEEE BigData 2013: 63-70 - [c202]Hisao Ishibuchi
, Takahiko Sudo, Koichiro Hoshino, Yusuke Nojima
:
Evolution of cooperative strategies for iterated prisoner's dilemma on networks. CASoN 2013: 32-37 - [c201]Hisao Ishibuchi
, Masakazu Yamane, Naoya Akedo, Yusuke Nojima
:
Many-objective and many-variable test problems for visual examination of multiobjective search. IEEE Congress on Evolutionary Computation 2013: 1491-1498 - [c200]Hisao Ishibuchi
, Yuki Tanigaki, Naoya Akedo, Yusuke Nojima
:
How to strike a balance between local search and global search in multiobjective memetic algorithms for multiobjective 0/1 knapsack problems. IEEE Congress on Evolutionary Computation 2013: 1643-1650 - [c199]Hisao Ishibuchi
, Masakazu Yamane, Yusuke Nojima
:
Effects of duplicated objectives in many-objective optimization problems on the search behavior of hypervolume-based evolutionary algorithms. MCDM 2013: 25-32 - [c198]Hisao Ishibuchi
, Masakazu Yamane, Yusuke Nojima
:
Difficulty in Evolutionary Multiobjective Optimization of Discrete Objective Functions with Different Granularities. EMO 2013: 230-245 - [c197]Hisao Ishibuchi
, Naoya Akedo, Yusuke Nojima
:
Relation between Neighborhood Size and MOEA/D Performance on Many-Objective Problems. EMO 2013: 459-474 - [c196]Hisao Ishibuchi
, Masakazu Yamane, Yusuke Nojima
:
Rule weight update in parallel distributed fuzzy genetics-based machine learning with data rotation. FUZZ-IEEE 2013: 1-8 - [c195]Michela Fazzolari, Rafael Alcalá
, Yusuke Nojima
, Hisao Ishibuchi
, Francisco Herrera:
Improving a fuzzy association rule-based classification model by granularity learning based on heuristic measures over multiple granularities. GEFS 2013: 44-51 - [c194]Yusuke Nojima
, Hisao Ishibuchi
:
Multiobjective genetic fuzzy rule selection with fuzzy relational rules. GEFS 2013: 60-67 - [c193]Hisao Ishibuchi
, Yusuke Nojima
:
Difficulties in choosing a single final classifier from non-dominated solutions in multiobjective fuzzy genetics-based machine learning. IFSA/NAFIPS 2013: 1203-1208 - [c192]Hisao Ishibuchi
, Koichiro Hoshino, Yusuke Nojima
:
Neighborhood Specification for Game Strategy Evolution in a Spatial Iterated Prisoner's Dilemma Game. LION 2013: 215-230 - [c191]Hisao Ishibuchi
, Naoya Akedo, Yusuke Nojima
:
A Study on the Specification of a Scalarizing Function in MOEA/D for Many-Objective Knapsack Problems. LION 2013: 231-246 - [c190]Hisao Ishibuchi
, Takahiko Sudo, Koichiro Hoshino, Yusuke Nojima
:
Effects of the Number of Opponents on the Evolution of Cooperation in the Iterated Prisoner's Dilemma. SMC 2013: 2001-2006 - 2012
- [j59]Rafael Alcalá
, Yusuke Nojima
, Hisao Ishibuchi
, Francisco Herrera
:
Special Issue on Evolutionary Fuzzy Systems. Int. J. Comput. Intell. Syst. 5(2): 209-211 (2012) - [c189]Hisao Ishibuchi
, Koichiro Hoshino, Yusuke Nojima
:
Strategy evolution in a spatial IPD game where each agent is not allowed to play against itself. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c188]Hisao Ishibuchi
, Koichiro Hoshino, Yusuke Nojima
:
Evolution of strategies in a spatial IPD game with a number of different representation schemes. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c187]Yusuke Nojima
, Shingo Mihara, Hisao Ishibuchi
:
Application of parallel distributed genetics-based machine learning to imbalanced data sets. FUZZ-IEEE 2012: 1-6 - [c186]Hisao Ishibuchi
, Masakazu Yamane, Yusuke Nojima
:
Effects of discrete objective functions with different granularities on the search behavior of EMO algorithms. GECCO 2012: 481-488 - [c185]Hisao Ishibuchi
, Naoya Akedo, Yusuke Nojima
:
Recombination of Similar Parents in SMS-EMOA on Many-Objective 0/1 Knapsack Problems. PPSN (2) 2012: 132-142 - [c184]Masakazu Yamane, Akihito Ueda, Naoshi Tadokoro, Yusuke Nojima
, Hisao Ishibuchi
:
Comparison of different fitness functions in genetic fuzzy rule selection. SCIS&ISIS 2012: 1046-1051 - [c183]Hisao Ishibuchi
, Masakazu Yamane, Naoya Akedo, Yusuke Nojima
:
Two-objective solution set optimization to maximize hypervolume and decision space diversity in multiobjective optimization. SCIS&ISIS 2012: 1871-1876 - [c182]Hisao Ishibuchi
, Masakazu Yamane, Yusuke Nojima
:
Ensemble Fuzzy Rule-Based Classifier Design by Parallel Distributed Fuzzy GBML Algorithms. SEAL 2012: 93-103 - [p14]Andrzej Jaszkiewicz
, Hisao Ishibuchi
, Qingfu Zhang
:
Multiobjective Memetic Algorithms. Handbook of Memetic Algorithms 2012: 201-217 - [e3]Lam Thu Bui, Yew-Soon Ong, Nguyen Xuan Hoai, Hisao Ishibuchi, Ponnuthurai Nagaratnam Suganthan:
Simulated Evolution and Learning - 9th International Conference, SEAL 2012, Hanoi, Vietnam, December 16-19, 2012. Proceedings. Lecture Notes in Computer Science 7673, Springer 2012, ISBN 978-3-642-34858-7 [contents] - 2011
- [j58]Hisao Ishibuchi, Yutaka Kaisho, Yusuke Nojima:
Design of Linguistically Interpretable Fuzzy Rule-Based Classifiers: A Short Review and Open Questions. J. Multiple Valued Log. Soft Comput. 17(2-3): 101-134 (2011) - [j57]Hisao Ishibuchi
, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima
:
Implementation of cellular genetic algorithms with two neighborhood structures for single-objective and multi-objective optimization. Soft Comput. 15(9): 1749-1767 (2011) - [j56]Yusuke Nojima
, Rafael Alcalá
, Hisao Ishibuchi
, Francisco Herrera
:
Special issue on evolutionary fuzzy systems. Soft Comput. 15(12): 2299-2301 (2011) - [j55]Rafael Alcalá
, Yusuke Nojima
, Francisco Herrera
, Hisao Ishibuchi
:
Multiobjective genetic fuzzy rule selection of single granularity-based fuzzy classification rules and its interaction with the lateral tuning of membership functions. Soft Comput. 15(12): 2303-2318 (2011) - [j54]Hisao Ishibuchi
, Yusuke Nakashima, Yusuke Nojima
:
Performance evaluation of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning. Soft Comput. 15(12): 2415-2434 (2011) - [j53]Hisao Ishibuchi
, Hiroyuki Ohyanagi, Yusuke Nojima
:
Evolution of Strategies With Different Representation Schemes in a Spatial Iterated Prisoner's Dilemma Game. IEEE Trans. Comput. Intell. AI Games 3(1): 67-82 (2011) - [c181]Hisao Ishibuchi
, Naoya Akedo, Hiroyuki Ohyanagi, Yusuke Nojima
:
Behavior of EMO algorithms on many-objective optimization problems with correlated objectives. IEEE Congress on Evolutionary Computation 2011: 1465-1472 - [c180]Hisao Ishibuchi
, Keisuke Takahashi, Kouichirou Hoshino, Junpei Maeda, Yusuke Nojima
:
Effects of configuration of agents with different strategy representations on the evolution of cooperative behavior in a spatial IPD game. CIG 2011: 313-320 - [c179]Hisao Ishibuchi
, Naoya Akedo, Hiroyuki Ohyanagi, Yasuhiro Hitotsuyanagi, Yusuke Nojima
:
Many-objective test problems with multiple Pareto optimal regions in a decision space. MCDM 2011: 113-120 - [c178]Hisao Ishibuchi
, Yasuhiro Hitotsuyanagi, Hiroyuki Ohyanagi, Yusuke Nojima
:
Effects of the Existence of Highly Correlated Objectives on the Behavior of MOEA/D. EMO 2011: 166-181 - [c177]Yusuke Nojima
, Shinya Nishikawa, Hisao Ishibuchi
:
A meta-fuzzy classifier for specifying appropriate fuzzy partitions by genetic fuzzy rule selection with data complexity measures. FUZZ-IEEE 2011: 264-271 - [c176]Hisao Ishibuchi
, Yusuke Nojima
:
Toward quantitative definition of explanation ability of fuzzy rule-based classifiers. FUZZ-IEEE 2011: 549-556 - [c175]Hisao Ishibuchi
, Naoya Akedo, Yusuke Nojima
:
A many-objective test problem for visually examining diversity maintenance behavior in a decision space. GECCO 2011: 649-656 - [c174]Hisao Ishibuchi
, Yusuke Nakashima, Yusuke Nojima
:
Double cross-validation for performance evaluation of multi-objective genetic fuzzy systems. GEFS 2011: 31-38 - [c173]Yusuke Nojima
, Hisao Ishibuchi
:
Mobile Robot Controller Design by Evolutionary Multiobjective Optimization in Multiagent Environments. ICIRA (2) 2011: 515-524 - [c172]Hisao Ishibuchi
, Shingo Mihara, Yusuke Nojima
:
Training Data Subdivision and Periodical Rotation in Hybrid Fuzzy Genetics-Based Machine Learning. ICMLA (1) 2011: 229-234 - [e2]Xue-wen Chen, Tharam S. Dillon, Hisao Ishibuchi, Jian Pei, Haixun Wang, M. Arif Wani:
10th International Conference on Machine Learning and Applications and Workshops, ICMLA 2011, Honolulu, Hawaii, USA, December 18-21, 2011. Volume 1: Main Conference. IEEE Computer Society 2011, ISBN 978-0-7695-4607-0 [contents] - [e1]Xue-wen Chen, Tharam S. Dillon, Hisao Ishibuchi, Jian Pei, Haixun Wang, M. Arif Wani:
10th International Conference on Machine Learning and Applications and Workshops, ICMLA 2011, Honolulu, Hawaii, USA, December 18-21, 2011. Volume 2: Special Sessions and Workshop. IEEE Computer Society 2011 [contents] - 2010
- [j52]Hisao Ishibuchi
:
IEEE CIS VP-Technical Activities Vision Statement [Society Briefs]. IEEE Comput. Intell. Mag. 5(2): 6 (2010) - [j51]Ke Tang, Kay Chen Tan, Hisao Ishibuchi
:
Guest editorial: Memetic Algorithms for Evolutionary Multi-Objective Optimization. Memetic Comput. 2(1): 1 (2010) - [j50]Hisao Ishibuchi
, Noritaka Tsukamoto, Yusuke Nojima
:
Diversity Improvement by Non-Geometric Binary Crossover in Evolutionary Multiobjective Optimization. IEEE Trans. Evol. Comput. 14(6): 985-998 (2010) - [c171]Yusuke Nojima
, Shingo Mihara, Hisao Ishibuchi
:
Ensemble classifier design by parallel distributed implementation of genetic fuzzy rule selection for large data sets. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c170]Hisao Ishibuchi
, Yusuke Nakashima, Yusuke Nojima
:
Effects of fine fuzzy partitions on the generalization ability of evolutionary multi-objective fuzzy rule-based classifiers. FUZZ-IEEE 2010: 1-8 - [c169]Yusuke Nojima
, Yutaka Kaisho, Hisao Ishibuchi
:
Accuracy improvement of genetic fuzzy rule selection with candidate rule addition and membership tuning. FUZZ-IEEE 2010: 1-8 - [c168]Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima
:
Simultaneous use of different scalarizing functions in MOEA/D. GECCO 2010: 519-526 - [c167]Hisao Ishibuchi
, Noritaka Tsukamoto, Yuji Sakane, Yusuke Nojima
:
Indicator-based evolutionary algorithm with hypervolume approximation by achievement scalarizing functions. GECCO 2010: 527-534 - [c166]Hisao Ishibuchi
, Yusuke Nakashima, Yusuke Nojima
:
Simple changes in problem formulations make a difference in multiobjective genetic fuzzy systems. GEFS 2010: 3-8 - [c165]Yusuke Nojima
, Hisao Ishibuchi
, Shingo Mihara:
Use of very small training data subsets in parallel distributed genetic fuzzy rule selection. GEFS 2010: 27-32 - [c164]Hisao Ishibuchi
, Yasuhiro Hitotsuyanagi, Yusuke Nakashima, Yusuke Nojima
:
Multiobjectivization from two objectives to four objectives in evolutionary multi-objective optimization algorithms. NaBIC 2010: 502-507 - [c163]Shinya Nishikawa, Yusuke Nojima
, Hisao Ishibuchi
:
Appropriate granularity specification for fuzzy classifier design by data complexity measures. NaBIC 2010: 691-696 - [c162]Hisao Ishibuchi
, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima
:
Many-Objective Test Problems to Visually Examine the Behavior of Multiobjective Evolution in a Decision Space. PPSN (2) 2010: 91-100 - [c161]Hisao Ishibuchi
, Yasuhiro Hitotsuyanagi, Yoshihiko Wakamatsu, Yusuke Nojima
:
How to Choose Solutions for Local Search in Multiobjective Combinatorial Memetic Algorithms. PPSN (1) 2010: 516-525 - [c160]Yusuke Nojima
, Shingo Mihara, Hisao Ishibuchi
:
Parallel Distributed Implementation of Genetics-Based Machine Learning for Fuzzy Classifier Design. SEAL 2010: 309-318
2000 – 2009
- 2009
- [j49]Noritaka Tsukamoto, Yusuke Nojima
, Hisao Ishibuchi
:
Effects of nongeometric binary crossover on multiobjective 0/1 knapsack problems. Artif. Life Robotics 13(2): 434-437 (2009) - [j48]Yoshihiro Hamada, Yusuke Nojima
, Hisao Ishibuchi
:
Use of multi-objective genetic rule selection for examining the effectiveness of inter-vehicle communication in traffic simulations. Artif. Life Robotics 14(3): 410-413 (2009) - [j47]Hiroyuki Ohyanagi, Yoshihiko Wakamatsu, Yusuke Nakashima, Yusuke Nojima
, Hisao Ishibuchi
:
Evolution of cooperative behavior among heterogeneous agents with different strategy representations in an iterated prisoner's dilemma game. Artif. Life Robotics 14(3): 414-417 (2009) - [j46]Yusuke Nojima
, Hisao Ishibuchi
:
Incorporation of user preference into multi-objective genetic fuzzy rule selection for pattern classification problems. Artif. Life Robotics 14(3): 418-421 (2009) - [j45]Yusuke Nojima
, Hisao Ishibuchi
, Isao Kuwajima:
Parallel distributed genetic fuzzy rule selection. Soft Comput. 13(5): 511-519 (2009) - [j44]Yew-Soon Ong
, Meng-Hiot Lim, Ferrante Neri
, Hisao Ishibuchi
:
Special issue on emerging trends in soft computing: memetic algorithms. Soft Comput. 13(8-9): 739-740 (2009) - [j43]Hisao Ishibuchi
, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima
:
Use of biased neighborhood structures in multiobjective memetic algorithms. Soft Comput. 13(8-9): 795-810 (2009) - [c159]Hisao Ishibuchi
, Noritaka Tsukamoto, Yuji Sakane, Yusuke Nojima
:
Hypervolume approximation using achievement scalarizing functions for evolutionary many-objective optimization. IEEE Congress on Evolutionary Computation 2009: 530-537 - [c158]Hisao Ishibuchi
, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima
:
Effects of using two neighborhood structures on the performance of cellular evolutionary algorithms for many-objective optimization. IEEE Congress on Evolutionary Computation 2009: 2508-2515 - [c157]Yusuke Nojima
, Hisao Ishibuchi
:
Interactive genetic fuzzy rule selection through evolutionary multiobjective optimization with user preference. MCDM 2009: 141-148 - [c156]Hisao Ishibuchi
, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima
:
Adaptation of Scalarizing Functions in MOEA/D: An Adaptive Scalarizing Function-Based Multiobjective Evolutionary Algorithm. EMO 2009: 438-452 - [c155]Hisao Ishibuchi, Yusuke Nojima:
Discussions on Interpretability of Fuzzy Systems using Simple Examples. IFSA/EUSFLAT Conf. 2009: 1649-1654 - [c154]Yusuke Nojima, Hisao Ishibuchi:
Interactive Fuzzy Modeling by Evolutionary Multiobjective Optimization with User Preference. IFSA/EUSFLAT Conf. 2009: 1839-1844 - [c153]Hisao Ishibuchi
, Hiroyuki Ohyanagi, Yusuke Nojima
:
Evolution of cooperative behavior in a spatial iterated prisoner's dilemma game with different representation schemes of game strategies. FUZZ-IEEE 2009: 1568-1573 - [c152]Hisao Ishibuchi
, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima
:
Selecting a small number of representative non-dominated solutions by a hypervolume-based solution selection approach. FUZZ-IEEE 2009: 1609-1614 - [c151]Rafael Alcalá
, Yusuke Nojima
, Francisco Herrera, Hisao Ishibuchi
:
Generating single granularity-based fuzzy classification rules for multiobjective genetic fuzzy rule selection. FUZZ-IEEE 2009: 1718-1723 - [c150]Hisao Ishibuchi
, Yusuke Nakashima, Yusuke Nojima
:
Search ability of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning. FUZZ-IEEE 2009: 1724-1729 - [c149]Hisao Ishibuchi
, Yutaka Kaisho, Yusuke Nojima
:
Complexity, interpretability and explanation capability of fuzzy rule-based classifiers. FUZZ-IEEE 2009: 1730-1735 - [c148]Hisao Ishibuchi
, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima
:
Single-objective and multi-objective formulations of solution selection for hypervolume maximization. GECCO 2009: 1831-1832 - [c147]Yusuke Nojima
, Hisao Ishibuchi
:
Effects of Data Reduction on the Generalization Ability of Parallel Distributed Genetic Fuzzy Rule Selection. ISDA 2009: 96-101 - [c146]Hisao Ishibuchi
, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima
:
Evolutionary Many-Objective Optimization by NSGA-II and MOEA/D with Large Populations. SMC 2009: 1758-1763 - [c145]Yusuke Nojima
, Yusuke Nakashima, Hisao Ishibuchi
:
Effects of the Use of Multiple Fuzzy Partitions on the Search Ability of Multiobjective Fuzzy Genetics-Based Machine Learning. SoCPaR 2009: 341-346 - [c144]Yuki Tsujimoto, Yasuhiro Hitotsuyanagi, Yusuke Nojima
, Hisao Ishibuchi
:
Effects of Including Single-Objective Optimal Solutions in an Initial Population on Evolutionary Multiobjective Optimization. SoCPaR 2009: 352-357 - [c143]Hisao Ishibuchi
, Noritaka Tsukamoto, Yusuke Nojima
:
Empirical Analysis of Using Weighted Sum Fitness Functions in NSGA-II for Many-Objective 0/1 Knapsack Problems. UKSim 2009: 71-76 - [p13]Gerald Schaefer, Tomoharu Nakashima
, Hisao Ishibuchi
:
Gene Expression Analysis by Fuzzy and Hybrid Fuzzy Classification. Fuzzy Systems in Bioinformatics and Computational Biology 2009: 127-140 - [i2]Matthias Ehrgott, Jussi Hakanen, Hisao Ishibuchi, Andreas Löhne, Mariano Luque, Kaisa Miettinen, Wlodzimierz Ogryczak, Olexandr Romanko, Theodor J. Stewart, Andrzej P. Wierzbicki:
09041 Working Group 4: MCDM and RIMO. Hybrid and Robust Approaches to Multiobjective Optimization 2009 - 2008
- [j42]Tomoharu Nakashima
, Yasuyuki Yokota, Hisao Ishibuchi
, Gerald Schaefer:
A cost-based fuzzy system for pattern classification with class importance. Artif. Life Robotics 12(1-2): 43-46 (2008) - [j41]Isao Kuwajima, Yusuke Nojima
, Hisao Ishibuchi
:
Effects of constructing fuzzy discretization from crisp discretization for rule-based classifiers. Artif. Life Robotics 13(1): 294-297 (2008) - [j40]Isao Kuwajima, Yusuke Nojima
, Hisao Ishibuchi
:
Obtaining accurate classifiers with Pareto-optimal and near Pareto-optimal rules. Artif. Life Robotics 13(1): 315-319 (2008) - [j39]Hisao Ishibuchi
, Kaname Narukawa, Noritaka Tsukamoto, Yusuke Nojima
:
An empirical study on similarity-based mating for evolutionary multiobjective combinatorial optimization. Eur. J. Oper. Res. 188(1): 57-75 (2008) - [c142]Hisao Ishibuchi, Yusuke Nojima
:
Evolutionary Multiobjective Fuzzy System Design. BIONETICS 2008: 30 - [c141]Hisao Ishibuchi
, Noritaka Tsukamoto, Yusuke Nojima
:
Evolutionary many-objective optimization: A short review. IEEE Congress on Evolutionary Computation 2008: 2419-2426 - [c140]Hisao Ishibuchi
, Yasuhiro Hitotsuyanagi, Yusuke Nojima
:
Scalability of multiobjective genetic local search to many-objective problems: Knapsack problem case studies. IEEE Congress on Evolutionary Computation 2008: 3586-3593 - [c139]Seiya Fujii, Tomoharu Nakashima
, Hisao Ishibuchi
:
A study on constructing fuzzy systems for high-level decision making in a car racing game. IEEE Congress on Evolutionary Computation 2008: 3626-3633 - [c138]El-Ghazali Talbi, Sanaz Mostaghim, Tatsuya Okabe, Hisao Ishibuchi, Günter Rudolph, Carlos A. Coello Coello:
Parallel Approaches for Multiobjective Optimization. Multiobjective Optimization 2008: 349-372 - [c137]Isao Kuwajima, Hisao Ishibuchi
, Yusuke Nojima
:
Effectiveness of designing fuzzy rule-based classifiers from Pareto-optimal rules. FUZZ-IEEE 2008: 1185-1192 - [c136]Seiya Fujii, Tomoharu Nakashima
, Hisao Ishibuchi
:
A study on constructing fuzzy systems for high-level decision making in a car racing game. FUZZ-IEEE 2008: 2299-2306 - [c135]Hisao Ishibuchi, Noritaka Tsukamoto, Yasuhiro Hitotsuyanagi, Yusuke Nojima
:
Effectiveness of scalability improvement attempts on the performance of NSGA-II for many-objective problems. GECCO 2008: 649-656 - [c134]Hisao Ishibuchi, Noritaka Tsukamoto, Yusuke Nojima:
Maintaining the diversity of solutions by non-geometric binary crossover: a worst one-max solver competition case study. GECCO 2008: 1111-1112 - [c133]Hisao Ishibuchi
, Yutaka Kaisho, Yusuke Nojima
:
Designing fuzzy rule-based classifiers that can visually explain their classification results to human users. GEFS 2008: 5-10 - [c132]Hisao Ishibuchi
, Noritaka Tsukamoto, Yusuke Nojima
:
Evolutionary many-objective optimization. GEFS 2008: 47-52 - [c131]Yusuke Nojima
, Hisao Ishibuchi
:
Effects of Diversity Measures on the Design of Ensemble Classifiers by Multiobjective Genetic Fuzzy Rule Selection with a Multi-classifier Coding Scheme. HAIS 2008: 755-763 - [c130]Hisao Ishibuchi
, Noritaka Tsukamoto, Yusuke Nojima
:
Examining the Effect of Elitism in Cellular Genetic Algorithms Using Two Neighborhood Structures. PPSN 2008: 458-467 - [c129]Hisao Ishibuchi
, Yasuhiro Hitotsuyanagi, Noritaka Tsukamoto, Yusuke Nojima
:
Use of Heuristic Local Search for Single-Objective Optimization in Multiobjective Memetic Algorithms. PPSN 2008: 743-752 - [c128]Hisao Ishibuchi
, Noritaka Tsukamoto, Yusuke Nojima
:
Use of Local Ranking in Cellular Genetic Algorithms with Two Neighborhood Structures. SEAL 2008: 309-318 - [c127]Hisao Ishibuchi
, Noritaka Tsukamoto, Yusuke Nojima
:
Behavior of Evolutionary Many-Objective Optimization. UKSim 2008: 266-271 - [c126]Hisao Ishibuchi
:
Evolutionary multiobjective optimization and multiobjective fuzzy system design. CSTST 2008: 3-4 - [p12]Hisao Ishibuchi, Isao Kuwajima, Yusuke Nojima
:
Multiobjective Classification Rule Mining. Multiobjective Problem Solving from Nature 2008: 219-240 - [p11]Hisao Ishibuchi
, Isao Kuwajima, Yusuke Nojima
:
Evolutionary Multi-objective Rule Selection for Classification Rule Mining. Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases 2008: 47-70 - [p10]Hisao Ishibuchi
, Yusuke Nojima
, Isao Kuwajima:
Evolutionary Multiobjective Design of Fuzzy Rule-Based Classifiers. Computational Intelligence: A Compendium 2008: 641-685 - [p9]Hisao Ishibuchi
, Yusuke Nojima
:
Pattern Classification with Linguistic Rules. Fuzzy Sets and Their Extensions: Representation, Aggregation and Models 2008: 377-395 - 2007
- [j38]Tomoharu Nakashima
, Yasuyuki Yokota, Yukio Shoji, Hisao Ishibuchi
:
A genetic approach to the design of autonomous agents for futures trading. Artif. Life Robotics 11(2): 145-148 (2007) - [j37]Tomoharu Nakashima
, Gerald Schaefer, Yasuyuki Yokota, Hisao Ishibuchi
:
A weighted fuzzy classifier and its application to image processing tasks. Fuzzy Sets Syst. 158(3): 284-294 (2007) - [j36]Hisao Ishibuchi
, Yusuke Nojima
:
Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning. Int. J. Approx. Reason. 44(1): 4-31 (2007) - [j35]Yusuke Nojima, Hisao Ishibuchi:
Genetic rule selection with a multi-classifier coding scheme for ensemble classifier design. Int. J. Hybrid Intell. Syst. 4(3): 157-169 (2007) - [j34]Tomoharu Nakashima, Yasuyuki Yokota, Hisao Ishibuchi, Gerald Schaefer, Ales Drastich, Michal Zavisek:
Constructing Cost-Sensitive Fuzzy-Rule-Based Systems for Pattern Classification Problems. J. Adv. Comput. Intell. Intell. Informatics 11(6): 546-553 (2007) - [j33]Yew-Soon Ong
, Natalio Krasnogor
, Hisao Ishibuchi
:
Special Issue on Memetic Algorithms. IEEE Trans. Syst. Man Cybern. Part B 37(1): 2-5 (2007) - [c125]Tomoharu Nakashima
, Hisao Ishibuchi
:
Mimicking Dribble Trajectories by Neural Networks for RoboCup Soccer Simulation. ISIC 2007: 658-663 - [c124]Ken Ohara, Yusuke Nojima
, Hisao Ishibuchi
:
A Study on Traffic Information Sharing Through Inter-Vehicle Communication. ISIC 2007: 670-675 - [c123]Hisao Ishibuchi
, Yasuhiro Hitotsuyanagi, Yusuke Nojima
:
An empirical study on the specification of the local search application probability in multiobjective memetic algorithms. IEEE Congress on Evolutionary Computation 2007: 2788-2795 - [c122]Hisao Ishibuchi
, Noritaka Tsukamoto, Yusuke Nojima
:
Iterative approach to indicator-based multiobjective optimization. IEEE Congress on Evolutionary Computation 2007: 3967-3974 - [c121]Ken Ohara, Yusuke Nojima
, Yumeka Kitano, Hisao Ishibuchi
:
Effects of spatial structures on evolution of iterated prisoner's dilemma game strategies with probabilistic decision making. IEEE Congress on Evolutionary Computation 2007: 4051-4058 - [c120]Gerald Schaefer, Tomoharu Nakashima
, Yasuyuki Yokota, Hisao Ishibuchi:
Cost-Sensitive Fuzzy Classification for Medical Diagnosis. CIBCB 2007: 312-316 - [c119]Hisao Ishibuchi
, Isao Kuwajima, Yusuke Nojima
:
Relation between Pareto-Optimal Fuzzy Rules and Pareto-Optimal Fuzzy Rule Sets. MCDM 2007: 42-49 - [c118]Hisao Ishibuchi, Yusuke Nojima
:
Optimization of Scalarizing Functions Through Evolutionary Multiobjective Optimization. EMO 2007: 51-65 - [c117]Hisao Ishibuchi
:
Evolutionary Multiobjective Design of Fuzzy Rule-Based Systems. FOCI 2007: 9-16 - [c116]Hisao Ishibuchi
:
Multiobjective Genetic Fuzzy Systems: Review and Future Research Directions. FUZZ-IEEE 2007: 1-6 - [c115]Tomoharu Nakashima
, Yasuyuki Yokota, Gerald Schaefer, Hisao Ishibuchi
:
Introducing Class-Based Classification Priority in Fuzzy Rule-Based Classification Systems. FUZZ-IEEE 2007: 1-6 - [c114]Yusuke Nojima
, Isao Kuwajima, Hisao Ishibuchi
:
Data Set Subdivision for Parallel Distributed Implementation of Genetic Fuzzy Rule Selection. FUZZ-IEEE 2007: 1-6 - [c113]Gerald Schaefer, Tomoharu Nakashima
, Yasuyuki Yokota, Hisao Ishibuchi
:
Fuzzy Classification of Gene Expression Data. FUZZ-IEEE 2007: 1-6 - [c112]Gerald Schaefer, Tomoharu Nakashima
, Michal Zavisek, Yasuyuki Yokota, Ales Drastich, Hisao Ishibuchi
:
Breast Cancer Classification Using Statistical Features and Fuzzy Classification of Thermograms. FUZZ-IEEE 2007: 1-5 - [c111]Hisao Ishibuchi
, Yusuke Nojima
, Noritaka Tsukamoto, Ken Ohara:
Effects of the use of non-geometric binary crossover on evolutionary multiobjective optimization. GECCO 2007: 829-836 - [c110]Hisao Ishibuchi
, Isao Kuwajima, Yusuke Nojima
:
Prescreening of Candidate Rules Using Association Rule Mining and Pareto-optimality in Genetic Rule Selection. KES (2) 2007: 509-516 - [c109]Hisao Ishibuchi
, Noritaka Tsukamoto, Yusuke Nojima
:
Choosing extreme parents for diversity improvement in evolutionary multiobjective optimization algorithms. SMC 2007: 1946-1951 - [p8]Hisao Ishibuchi
, Isao Kuwajima, Yusuke Nojima
:
Use of Pareto-Optimal and Near Pareto-Optimal Candidate Rules in Genetic Fuzzy Rule Selection. Analysis and Design of Intelligent Systems using Soft Computing Techniques 2007: 387-396 - 2006
- [j32]Hisao Ishibuchi, Yusuke Nojima:
Evolutionary multiobjective optimization for the design of fuzzy rule-based ensemble classifiers. Int. J. Hybrid Intell. Syst. 3(3): 129-145 (2006) - [j31]Hisao Ishibuchi
, Takashi Yamamoto, Tomoharu Nakashima
:
An approach to fuzzy default reasoning for function approximation. Soft Comput. 10(9): 850-864 (2006) - [c108]Hisao Ishibuchi, Naoki Namikawa, Ken Ohara:
Effects of Spatial Structures on Evolution of Iterated Prisoner's Dilemma Game Strategies in Single-Dimensional and Two-Dimensional Grids. IEEE Congress on Evolutionary Computation 2006: 976-983 - [c107]Hisao Ishibuchi, Yusuke Nojima, Tsutomu Doi:
Comparison between Single-Objective and Multi-Objective Genetic Algorithms: Performance Comparison and Performance Measures. IEEE Congress on Evolutionary Computation 2006: 1143-1150 - [c106]Tomoharu Nakashima, Masahiro Takatani, Naoki Namikawa, Hisao Ishibuchi, Manabu Nii:
Robust Evaluation of RoboCup Soccer Strategies by Using Match History. IEEE Congress on Evolutionary Computation 2006: 1195-1201 - [c105]Tomoharu Nakashima
, Hisao Ishibuchi
, Masahiro Takatani, Manabu Nii:
The Effect of Using Match History on the Evolution of RoboCup Soccer Team Strategies. CIG 2006: 60-66 - [c104]Tomoharu Nakashima
, Yasuyuki Yokota, Gerald Schaefer, Hisao Ishibuchi
:
A Cost-based Fuzzy Rule-based System for Pattern Classification Problems. FUZZ-IEEE 2006: 251-255 - [c103]Hisao Ishibuchi
, Yusuke Nojima
, Isao Kuwajima:
Fuzzy Data Mining by Heuristic Rule Extraction and Multiobjective Genetic Rule Selection. FUZZ-IEEE 2006: 1633-1640 - [c102]Hisao Ishibuchi, Yusuke Nojima
, Kaname Narukawa, Tsutomu Doi:
Incorporation of decision maker's preference into evolutionary multiobjective optimization algorithms. GECCO 2006: 741-742 - [c101]Hisao Ishibuchi, Yusuke Nojima
, Isao Kuwajima:
Multiobjective genetic rule selection as a data mining postprocessing procedure. GECCO 2006: 1591-1592 - [c100]Yusuke Nojima, Hisao Ishibuchi:
Designing Fuzzy Ensemble Classifiers by Evolutionary Multiobjective Optimization with an Entropy-Based Diversity Criterion. HIS 2006: 59 - [c99]Hisao Ishibuchi, Yusuke Nojima
, Isao Kuwajima:
Finding Simple Fuzzy Classification Systems with High Interpretability Through Multiobjective Rule Selection. KES (2) 2006: 86-93 - [c98]Hisao Ishibuchi, Tsutomu Doi, Yusuke Nojima
:
Incorporation of Scalarizing Fitness Functions into Evolutionary Multiobjective Optimization Algorithms. PPSN 2006: 493-502 - [c97]Hisao Ishibuchi, Tsutomu Doi, Yusuke Nojima
:
Effects of Using Two Neighborhood Structures in Cellular Genetic Algorithms for Function Optimization. PPSN 2006: 949-958 - [c96]Tomoharu Nakashima
, Yasuyuki Yokota, Gerald Schaefer, Hisao Ishibuchi
:
Examining the Effect of Cost Assignment on the Performance of Cost-Based Classification Systems. SMC 2006: 2772-2777 - [p7]Hisao Ishibuchi, Yusuke Nojima:
Fuzzy Ensemble Design through Multi-Objective Fuzzy Rule Selection. Multi-Objective Machine Learning 2006: 507-530 - 2005
- [b1]Hisao Ishibuchi, Tomoharu Nakashima, Manabu Nii:
Classification and modeling with linguistic information granules - advanced approaches to linguistic data mining. Advanced information processing, Springer 2005, ISBN 978-3-540-20767-2, pp. I-XI, 1-307 - [j30]Hisao Ishibuchi
, Naoki Namikawa:
Evolution of iterated prisoner's dilemma game strategies in structured demes under random pairing in game playing. IEEE Trans. Evol. Comput. 9(6): 552-561 (2005) - [j29]Hisao Ishibuchi
, Takashi Yamamoto:
Rule Weight Specification in Fuzzy Rule-Based Classification Systems. IEEE Trans. Fuzzy Syst. 13(4): 428-435 (2005) - [j28]Hisao Ishibuchi
, Takashi Yamamoto, Tomoharu Nakashima
:
Hybridization of fuzzy GBML approaches for pattern classification problems. IEEE Trans. Syst. Man Cybern. Part B 35(2): 359-365 (2005) - [c95]Satoshi Yokoyama, Naoki Namikawa, Tomoharu Nakashima, Masayo Udo, Hisao Ishibuchi:
Developing a Goal Keeper for Simulated RoboCup Soccer and its Performance Evaluation. AMiRE 2005: 75-80 - [c94]Hisao Ishibuchi, Naoki Namikawa:
Evolution of cooperative behavior in the iterated prisoner's dilemma under random pairing in game playing. Congress on Evolutionary Computation 2005: 2637-2644 - [c93]Hisao Ishibuchi, Kaname Narukawa:
Recombination of Similar Parents in EMO Algorithms. EMO 2005: 265-279 - [c92]Yusuke Nojima
, Kaname Narukawa, Shiori Kaige, Hisao Ishibuchi:
Effects of Removing Overlapping Solutions on the Performance of the NSGA-II Algorithm. EMO 2005: 341-354 - [c91]Hisao Ishibuchi, Shiori Kaige, Kaname Narukawa:
Comparison Between Lamarckian and Baldwinian Repair on Multiobjective 0/1 Knapsack Problems. EMO 2005: 370-385 - [c90]Hisao Ishibuchi, Yusuke Nojima:
Multiobjective Formulations of Fuzzy Rule-Based Classification System Design. EUSFLAT Conf. 2005: 285-290 - [c89]Tomoharu Nakashima, Yasuyuki Yokota, Hisao Ishibuchi, Gerald Schaefer:
Learning Fuzzy If-Then Rules for Pattern Classi cation with Weighted Training Patterns. EUSFLAT Conf. 2005: 1064-1069 - [c88]Hisao Ishibuchi, Yusuke Nojima:
Comparison between Fuzzy and Interval Partitions in Evolutionary Multiobjective Design of Rule-Based Classification Systems. FUZZ-IEEE 2005: 430-435 - [c87]Kaname Narukawa, Yusuke Nojima, Hisao Ishibuchi:
Modification of Evolutionary Multiobjective Optimization Algorithms for Multiobjective Design of Fuzzy Rule-Based Classification Systems. FUZZ-IEEE 2005: 809-814 - [c86]Hisao Ishibuchi
, Kaname Narukawa:
Comparison of evolutionary multiobjective optimization with rference solution-based single-objective approach. GECCO 2005: 787-794 - [c85]Hisao Ishibuchi
, Kaname Narukawa, Yusuke Nojima
:
An empirical study on the handling of overlapping solutions in evolutionary multiobjective optimization. GECCO 2005: 817-824 - [c84]Hisao Ishibuchi
, Kaname Narukawa:
Spatial Implementation of Evolutionary Multiobjective Algorithms with Partial Lamarckian Repair for Multiobjective Knapsack Problems. HIS 2005: 265-270 - [c83]Hisao Ishibuchi
, Yusuke Nojima
:
Performance Evaluation of Evolutionary Multiobjective Approaches to the Design of Fuzzy Rule-Based Ensemble Classifiers. HIS 2005: 271-276 - [c82]Tomoharu Nakashima
, Masahiro Takatani, Masayo Udo, Hisao Ishibuchi, Manabu Nii:
Performance Evaluation of an Evolutionary Method for RoboCup Soccer Strategies. RoboCup 2005: 616-623 - [c81]Hiroko Kitano, Tomoharu Nakashima, Hisao Ishibuchi:
Behavior Analysis of Futures Trading Agents Using Fuzzy Rule Extraction. SMC 2005: 1477-1481 - [p6]Tomoharu Nakashima, Hisao Ishibuchi:
Using Boosting Techniques to Improve the Performance of Fuzzy Classification Systems. Classification and Clustering for Knowledge Discovery 2005: 147-157 - [p5]Tomoharu Nakashima, Takanobu Ariyama, Hiroko Kitano, Hisao Ishibuchi:
A Fuzzy Rule-Based Trading Agent: Analysis and Knowledge Extraction. Computational Intelligence for Modelling and Prediction 2005: 265-277 - [i1]Hisao Ishibuchi:
Effects of Crossover Operations on the Performance of EMO Algorithms. Practical Approaches to Multi-Objective Optimization 2005 - 2004
- [j27]Hisao Ishibuchi
, Takashi Yamamoto:
Comparison of Heuristic Criteria for Fuzzy Rule Selection in Classification Problems. Fuzzy Optim. Decis. Mak. 3(2): 119-139 (2004) - [j26]Hisao Ishibuchi
, Takashi Yamamoto:
Fuzzy rule selection by multi-objective genetic local search algorithms and rule evaluation measures in data mining. Fuzzy Sets Syst. 141(1): 59-88 (2004) - [j25]Hisao Ishibuchi:
Book Review: "Genetic fuzzy systems: evolutionary tuning and learning of fuzzy knowledge bases" by Oscar Cordon, Francisco Herrera, Frank Hoffmann and Luis Magdalena; World Scientific, Singapore, New Jersey, London, Hong Kong, 2001, 462pp., ISBN 981-02-4016-3. Fuzzy Sets Syst. 141(1): 161-162 (2004) - [j24]Hisao Ishibuchi, Shiori Kaige:
Implementation of Simple Multiobjective Memetic Algorithms and Its Applications to Knapsack Problems. Int. J. Hybrid Intell. Syst. 1(1): 22-35 (2004) - [c80]Hisao Ishibuchi, Kiyoshi Narukawa:
Performance evaluation of simple multiobjective genetic local search algorithms on multiobjective 0/1 knapsack problems. IEEE Congress on Evolutionary Computation 2004: 441-448 - [c79]Hisao Ishibuchi
, Takashi Yamamoto:
Heuristic extraction of fuzzy classification rules using data mining techniques: an empirical study on benchmark data sets. FUZZ-IEEE 2004: 161-166 - [c78]Hisao Ishibuchi, Kaname Narukawa:
Some Issues on the Implementation of Local Search in Evolutionary Multiobjective Optimization. GECCO (1) 2004: 1246-1258 - [c77]Hisao Ishibuchi, Youhei Shibata:
Mating Scheme for Controlling the Diversity-Convergence Balance for Multiobjective Optimization. GECCO (1) 2004: 1259-1271 - [c76]Hisao Ishibuchi, Kaname Narukawa:
Comparison of Local Search Implementation Schemes in Hybrid Evolutionary Multiobjective Optimization Algorithms. HIS 2004: 404-409 - [c75]Tomoharu Nakashima
, Hisao Ishibuchi, Andrzej Bargiela:
A Study on Weighting Training Patterns for Fuzzy Rule-Based Classification Systems. MDAI 2004: 60-69 - [c74]Hisao Ishibuchi, Satoshi Namba:
Evolutionary Multiobjective Knowledge Extraction for High-Dimensional Pattern Classification Problems. PPSN 2004: 1123-1132 - [c73]Tomoharu Nakashima
, Masahiro Takatani, Masayo Udo, Hisao Ishibuchi
:
An evolutionary approach for strategy learning in RoboCup soccer. SMC (2) 2004: 2023-2028 - [c72]Tomoharu Nakashima
, Hiroko Kitano, Hisao Ishibuchi
:
Development of a fuzzy position controller for an autonomously trading agent. SMC (3) 2004: 2338-2343 - [c71]Hisao Ishibuchi
, Takashi Yamamoto:
Multi-objective evolutionary design of fuzzy rule-based systems. SMC (3) 2004: 2362-2367 - [c70]Tomoharu Nakashima
, Hisao Ishibuchi
, Andrzej Bargiela:
Constructing fuzzy classification systems from weighted training patterns. SMC (3) 2004: 2386-2391 - 2003
- [j23]Hisao Ishibuchi
, Ryoji Sakamoto, Tomoharu Nakashima
:
Learning fuzzy rules from iterative execution of games. Fuzzy Sets Syst. 135(2): 213-240 (2003) - [j22]Hisao Ishibuchi
, Tadashi Yoshida, Tadahiko Murata:
Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling. IEEE Trans. Evol. Comput. 7(2): 204-223 (2003) - [c69]Hisao Ishibuchi
, Shiori Kaige:
Effects of repair procedures on the performance of EMO algorithms for multiobjective 0/1 knapsack problems. IEEE Congress on Evolutionary Computation 2003: 2254-2261 - [c68]Tomoharu Nakashima
, Takanobu Ariyama, Takanori Yoshida, Hisao Ishibuchi:
Performance evaluation of combined cellular genetic algorithms for function optimization problems. CIRA 2003: 295-299 - [c67]Tomoharu Nakashima
, Gaku Nakai, Hisao Ishibuchi:
Credit assignment by fuzzy rule-based systems in fuzzy classifier ensembles. CIRA 2003: 664-669 - [c66]Tomoharu Nakashima
, Masayo Udo, Hisao Ishibuchi:
Acquiring the positioning skill in a soccer game using a fuzzy Q-learning. CIRA 2003: 1488-1491 - [c65]Hisao Ishibuchi, Youhei Shibata:
An Empirical Study on the Effect of Mating Restriction on the Search Ability of EMO Algorithms. EMO 2003: 433-447 - [c64]Tadahiko Murata, Hiroyuki Nozawa, Hisao Ishibuchi, Mitsuo Gen:
Modification of Local Search Directions for Non-dominated Solutions in CellularMultiobjective Genetic Algorithms forPattern Classification Problems. EMO 2003: 593-607 - [c63]Hisao Ishibuchi, Takashi Yamamoto:
Effects of Three-Objective Genetic Rule Selection on the Generalization Ability of Fuzzy Rule-Based Systems. EMO 2003: 608-622 - [c62]Takashi Yamamoto, Hisao Ishibuchi:
Performance evaluation of three-objective genetic rule selection. FUZZ-IEEE 2003: 149-154 - [c61]Tomoharu Nakashima, Masayo Udo, Hisao Ishibuchi:
Implementation of fuzzy Q-learning for a soccer agent. FUZZ-IEEE 2003: 533-536 - [c60]Tomoharu Nakashima, Gaku Nakai, Hisao Ishibuchi:
A boosting algorithm with subset selection of training patterns. FUZZ-IEEE 2003: 690-695 - [c59]Tomoharu Nakashima, Takanobu Ariyama, Hisao Ishibuchi:
Extracting linguistic knowledge and its use as decision support in a virtual futures market. FUZZ-IEEE 2003: 708-713 - [c58]Hisao Ishibuchi, Takashi Yamamoto:
Deriving fuzzy discretization from interval discretization. FUZZ-IEEE 2003: 749-754 - [c57]Hisao Ishibuchi, Youhei Shibata:
A Similarity-Based Mating Scheme for Evolutionary Multiobjective Optimization. GECCO 2003: 1065-1076 - [c56]Hisao Ishibuchi, Takashi Yamamoto:
Evolutionary Multiobjective Optimization for Generating an Ensemble of Fuzzy Rule-Based Classifiers. GECCO 2003: 1077-1088 - [c55]Tadahiko Murata, Shiori Kaige, Hisao Ishibuchi:
Generalization of Dominance Relation-Based Replacement Rules for Memetic EMO Algorithms. GECCO 2003: 1234-1245 - [c54]Hisao Ishibuchi, Shiori Kaige:
A Simple but Powerful Multiobjective Hybrid Genetic Algorithm. HIS 2003: 244-251 - [c53]Tomoharu Nakashima
, Masayo Udo, Hisao Ishibuchi:
A Fuzzy Reinforcement Learning for a Ball Interception Problem. RoboCup 2003: 559-567 - [c52]Shiori Kaige, Tadahiko Murata, Hisao Ishibuchi:
Performance evaluation of memetic EMO algorithms using dominance relation-based replacement rules on MOO test problems. SMC 2003: 14-19 - [c51]Tomoham Nakashima, Gaku Nakai, Hisao Ishibuchi:
Constructing fuzzy ensembles for pattern classification problems. SMC 2003: 3200-3205 - [c50]Tomoharu Nakashima, Masayo Udo, Hisao Ishibuchi:
Knowledge acquisition for a soccer agent by fuzzy reinforcement learning. SMC 2003: 4256-4261 - [p4]Hisao Ishibuchi, Takashi Yamamoto:
Interpretability Issues in Fuzzy Genetics-Based Machine Learning for Linguistic Modelling. Modelling with Words 2003: 209-228 - 2002
- [c49]Tadahiko Murata, Hiroyuki Nozawa, Yasuhiro Tsujimura, Mitsuo Gen, Hisao Ishibuchi
:
Effect of local search on the performance of cellular multiobjective genetic algorithms for designing fuzzy rule-based classification systems. IEEE Congress on Evolutionary Computation 2002: 663-668 - [c48]Hisao Ishibuchi
, Tadsahi Yoshida, Tadahiko Murata:
Selection of initial solutions for local search in multiobjective genetic local search. IEEE Congress on Evolutionary Computation 2002: 950-955 - [c47]Tomoharu Nakashima, Takanobu Ariyama, Hisao Ishibuchi:
On-Line Learning of a Fuzzy System for a Future Market. FSKD 2002: 54-58 - [c46]Tomoharu Nakashima, Gaku Nakai, Hisao Ishibuchi:
A Boosting Algorithm of Fuzzy Rule-Based Systems for Pattern Classification Problems. FSKD 2002: 155-158 - [c45]Tomoharu Nakashima
, Gaku Nakai, Hisao Ishibuchi:
Improving the performance of fuzzy classification systems by membership function learning and feature selection. FUZZ-IEEE 2002: 488-493 - [c44]Hisao Ishibuchi, Takashi Yamamoto:
Comparison of heuristic rule weight specification methods. FUZZ-IEEE 2002: 908-913 - [c43]Hisao Ishibuchi, Teppei Seguchi:
Successive adaptation of fuzzy rule-based systems in a multi-agent model. FUZZ-IEEE 2002: 1009-1014 - [c42]Hisao Ishibuchi, Takashi Yamamoto:
Performance evaluation of fuzzy partitions with different fuzzification grades. FUZZ-IEEE 2002: 1198-1203 - [c41]Tomoharu Nakashima
, Gaku Nakai, Hisao Ishibuchi:
A fuzzy rule-based system for ensembling classification systems. FUZZ-IEEE 2002: 1432-1437 - [c40]