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[j94]Junfei Qiao, Fei Li, Shengxiang Yang, Cuili Yang, Wenjing Li, Ke Gu:
An adaptive hybrid evolutionary immune multi-objective algorithm based on uniform distribution selection. Inf. Sci. 512: 446-470 (2020)
2010 – today
- 2019
- [j93]Conor Fahy, Shengxiang Yang
:
Dynamic Feature Selection for Clustering High Dimensional Data Streams. IEEE Access 7: 127128-127140 (2019) - [j92]Junfei Qiao, Hongbiao Zhou, Cuili Yang, Shengxiang Yang:
A decomposition-based multiobjective evolutionary algorithm with angle-based adaptive penalty. Appl. Soft Comput. 74: 190-205 (2019) - [j91]He Xu, Weiwei Shen, Peng Li, Keith Mayes, Ruchuan Wang, Dashen Li, Shengxiang Yang:
Novel implementation of defence strategy of relay attack based on cloud in RFID systems. IJICS 11(2): 120-144 (2019) - [j90]Hui Bai, Jinhua Zheng, Guo Yu, Shengxiang Yang, Juan Zou:
A Pareto-based many-objective evolutionary algorithm using space partitioning selection and angle-based truncation. Inf. Sci. 478: 186-207 (2019) - [j89]Zhengping Liang, Shunxiang Zheng, Zexuan Zhu, Shengxiang Yang:
Hybrid of memory and prediction strategies for dynamic multiobjective optimization. Inf. Sci. 485: 200-218 (2019) - [j88]Renato Tinós, Shengxiang Yang:
A framework for inducing artificial changes in optimization problems. Inf. Sci. 485: 486-504 (2019) - [j87]Juan Zou, Liuwei Fu, Shengxiang Yang, Jinhua Zheng, Gan Ruan, Tingrui Pei, Lei Wang:
An adaptation reference-point-based multiobjective evolutionary algorithm. Inf. Sci. 488: 41-57 (2019) - [j86]Qingya Li, Juan Zou, Shengxiang Yang, Jinhua Zheng, Gan Ruan:
A predictive strategy based on special points for evolutionary dynamic multi-objective optimization. Soft Comput. 23(11): 3723-3739 (2019) - [j85]Jinglei Guo, Zhijian Li, Shengxiang Yang:
Accelerating differential evolution based on a subset-to-subset survivor selection operator. Soft Comput. 23(12): 4113-4130 (2019) - [j84]Qingyang Zhang, Ronggui Wang, Juan Yang, Andrew Lewis, Francisco Chiclana, Shengxiang Yang:
Biology migration algorithm: a new nature-inspired heuristic methodology for global optimization. Soft Comput. 23(16): 7333-7358 (2019) - [j83]Juan Zou, Qingya Li, Shengxiang Yang, Jinhua Zheng, Zhou Peng, Tingrui Pei:
A dynamic multiobjective evolutionary algorithm based on a dynamic evolutionary environment model. Swarm and Evolutionary Computation 44: 247-259 (2019) - [j82]Juan Zou, Chunhui Ji, Shengxiang Yang, Yuping Zhang, Jinhua Zheng, Ke Li:
A knee-point-based evolutionary algorithm using weighted subpopulation for many-objective optimization. Swarm and Evolutionary Computation 47: 33-43 (2019) - [j81]Yong Wang, Jian Yu, Shengxiang Yang, Shouyong Jiang, Shuang Zhao:
Evolutionary dynamic constrained optimization: Test suite construction and algorithm comparisons. Swarm and Evolutionary Computation 50 (2019) - [j80]Zhi-Zhong Liu, Yong Wang, Shengxiang Yang, Ke Tang:
An Adaptive Framework to Tune the Coordinate Systems in Nature-Inspired Optimization Algorithms. IEEE Trans. Cybernetics 49(4): 1403-1416 (2019) - [j79]Yong Wang, Da-Qing Yin, Shengxiang Yang, Guangyong Sun:
Global and Local Surrogate-Assisted Differential Evolution for Expensive Constrained Optimization Problems With Inequality Constraints. IEEE Trans. Cybernetics 49(5): 1642-1656 (2019) - [j78]Conor Fahy, Shengxiang Yang, Mario Gongora:
Ant Colony Stream Clustering: A Fast Density Clustering Algorithm for Dynamic Data Streams. IEEE Trans. Cybernetics 49(6): 2215-2228 (2019) - [j77]Wei Fang, Lingzhi Zhang, Shengxiang Yang, Jun Sun, Xiaojun Wu:
A Multiobjective Evolutionary Algorithm Based on Coordinate Transformation. IEEE Trans. Cybernetics 49(7): 2732-2743 (2019) - [c108]Zedong Zheng, Shengxiang Yang:
A Two-layer Optimization Management Method for the Microgrid with Electric Vehicles. CEC 2019: 1102-1109 - [c107]Yiya Diao, Changhe Li, Sanyou Zeng, Michalis Mavrovouniotis, Shengxiang Yang:
Memory-based multi-population genetic learning for dynamic shortest path problems. CEC 2019: 2276-2283 - [i3]Shouyong Jiang, Marcus Kaiser, Shengxiang Yang, Stefanos Kollias, Natalio Krasnogor:
A Scalable Test Suite for Continuous Dynamic Multiobjective Optimisation. CoRR abs/1903.02510 (2019) - [i2]Shouyong Jiang, Hongru Li, Jinglei Guo, Mingjun Zhong, Shengxiang Yang, Marcus Kaiser, Natalio Krasnogor:
AREA: Adaptive Reference-set Based Evolutionary Algorithm for Multiobjective Optimisation. CoRR abs/1910.07491 (2019) - 2018
- [j76]Juan Zou, Yuping Zhang, Shengxiang Yang, Yuan Liu, Jinhua Zheng:
Adaptive neighborhood selection for many-objective optimization problems. Appl. Soft Comput. 64: 186-198 (2018) - [j75]Juan Zou, Liuwei Fu, Jinhua Zheng, Shengxiang Yang, Guo Yu, Yaru Hu:
A many-objective evolutionary algorithm based on rotated grid. Appl. Soft Comput. 67: 596-609 (2018) - [j74]Muhanad Tahrir Younis, Shengxiang Yang:
Hybrid meta-heuristic algorithms for independent job scheduling in grid computing. Appl. Soft Comput. 72: 498-517 (2018) - [j73]Kang Wang, Xiaoli Li, Chao Jia, Shengxiang Yang, Miqing Li, Yang Li:
Multiobjective optimization of the production process for ground granulated blast furnace slags. Soft Comput. 22(24): 8177-8186 (2018) - [j72]Miqing Li, Crina Grosan, Shengxiang Yang, Xiaohui Liu, Xin Yao:
Multiline Distance Minimization: A Visualized Many-Objective Test Problem Suite. IEEE Trans. Evolutionary Computation 22(1): 61-78 (2018) - [j71]Shouyong Jiang, Shengxiang Yang, Yong Wang, Xiaobin Liu:
Scalarizing Functions in Decomposition-Based Multiobjective Evolutionary Algorithms. IEEE Trans. Evolutionary Computation 22(2): 296-313 (2018) - [j70]Yong Wang, Hao Liu, Huan Long, Zijun Zhang, Shengxiang Yang:
Differential Evolution With a New Encoding Mechanism for Optimizing Wind Farm Layout. IEEE Trans. Industrial Informatics 14(3): 1040-1054 (2018) - [c106]Shouyong Jiang, Marcus Kaiser, Shuzhen Wan, Jinglei Guo, Shengxiang Yang, Natalio Krasnogor:
An Empirical Study of Dynamic Triobjective Optimisation Problems. CEC 2018: 1-8 - [c105]Muhanad Tahrir Younis, Shengxiang Yang, Benjamin N. Passow:
A Loosely Coupled Hybrid Meta-Heuristic Algorithm for the Static Independent Task Scheduling Problem in Grid Computing. CEC 2018: 1-8 - [c104]Shouyong Jiang, Marcus Kaiser, Jinglei Guo, Shengxiang Yang, Natalio Krasnogor:
Less detectable environmental changes in dynamic multiobjective optimisation. GECCO 2018: 673-680 - [c103]Zhanglu Hou, Shengxiang Yang, Juan Zou, Jinhua Zheng, Guo Yu, Gan Ruan:
A Performance Indicator for Reference-Point-Based Multiobjective Evolutionary Optimization. SSCI 2018: 1571-1578 - [c102]Jianwei Zhou, Juan Zou, Shengxiang Yang, Gan Ruan, Junwei Ou, Jinhua Zheng:
An Evolutionary Dynamic Multi-objective Optimization Algorithm Based on Center-point Prediction and Sub-population Autonomous Guidance. SSCI 2018: 2148-2154 - 2017
- [j69]Gan Ruan, Guo Yu, Jinhua Zheng, Juan Zou, Shengxiang Yang:
The effect of diversity maintenance on prediction in dynamic multi-objective optimization. Appl. Soft Comput. 58: 631-647 (2017) - [j68]Juan Zou, Qingya Li, Shengxiang Yang, Hui Bai, Jinhua Zheng:
A prediction strategy based on center points and knee points for evolutionary dynamic multi-objective optimization. Appl. Soft Comput. 61: 806-818 (2017) - [j67]Xingwei Wang, Jinhong Zhang, Min Huang, Shengxiang Yang:
A green intelligent routing algorithm supporting flexible QoS for many-to-many multicast. Computer Networks 126: 229-245 (2017) - [j66]Shengxiang Yang, Shouyong Jiang, Yong Jiang:
Improving the multiobjective evolutionary algorithm based on decomposition with new penalty schemes. Soft Comput. 21(16): 4677-4691 (2017) - [j65]Michalis Mavrovouniotis, Changhe Li, Shengxiang Yang:
A survey of swarm intelligence for dynamic optimization: Algorithms and applications. Swarm and Evolutionary Computation 33: 1-17 (2017) - [j64]Shouyong Jiang, Shengxiang Yang:
Evolutionary Dynamic Multiobjective Optimization: Benchmarks and Algorithm Comparisons. IEEE Trans. Cybernetics 47(1): 198-211 (2017) - [j63]Michalis Mavrovouniotis, Felipe Martins Müller, Shengxiang Yang:
Ant Colony Optimization With Local Search for Dynamic Traveling Salesman Problems. IEEE Trans. Cybernetics 47(7): 1743-1756 (2017) - [j62]Shouyong Jiang, Shengxiang Yang:
A Steady-State and Generational Evolutionary Algorithm for Dynamic Multiobjective Optimization. IEEE Trans. Evolutionary Computation 21(1): 65-82 (2017) - [j61]Shouyong Jiang, Shengxiang Yang:
A Strength Pareto Evolutionary Algorithm Based on Reference Direction for Multiobjective and Many-Objective Optimization. IEEE Trans. Evolutionary Computation 21(3): 329-346 (2017) - [j60]Yong Wang, Biao Xu, Guangyong Sun, Shengxiang Yang:
A Two-Phase Differential Evolution for Uniform Designs in Constrained Experimental Domains. IEEE Trans. Evolutionary Computation 21(5): 665-680 (2017) - [j59]Wenyin Gong, Yong Wang, Zhihua Cai, Shengxiang Yang:
A Weighted Biobjective Transformation Technique for Locating Multiple Optimal Solutions of Nonlinear Equation Systems. IEEE Trans. Evolutionary Computation 21(5): 697-713 (2017) - [j58]Jayne Eaton, Shengxiang Yang, Mario Gongora:
Ant Colony Optimization for Simulated Dynamic Multi-Objective Railway Junction Rescheduling. IEEE Trans. Intelligent Transportation Systems 18(11): 2980-2992 (2017) - [c101]Conor Fahy, Shengxiang Yang, Mario Gongora:
Finding Multi-Density Clusters in non-stationary data streams using an Ant Colony with adaptive parameters. CEC 2017: 673-680 - [c100]Michalis Mavrovouniotis, Anastasia Ioannou, Shengxiang Yang:
Pre-scheduled Colony Size Variation in Dynamic Environments. EvoApplications (2) 2017: 128-139 - [c99]Muhanad Tahrir Younis, Shengxiang Yang, Benjamin N. Passow:
Meta-Heuristically Seeded Genetic Algorithm for Independent Job Scheduling in Grid Computing. EvoApplications (1) 2017: 177-189 - [c98]Darren M. Chitty, Shengxiang Yang, Mario Gongora:
Robustness and Evolutionary Dynamic Optimisation of Airport Security Schedules. MENDEL 2017: 27-39 - [c97]Darren M. Chitty, Shengxiang Yang, Mario Gongora:
Considering flexibility in the evolutionary dynamic optimisation of airport security lane schedules. SSCI 2017: 1-8 - [c96]Liuwei Fu, Juan Zou, Shengxiang Yang, Gan Ruan, Zhongwei Ma, Jinhua Zheng:
A proportion-based selection scheme for multi-objective optimization. SSCI 2017: 1-7 - [c95]Michalis Mavrovouniotis, Mien Van, Shengxiang Yang:
Pheromone modification strategy for the dynamic travelling salesman problem with weight changes. SSCI 2017: 1-8 - [i1]Zhi-Zhong Liu, Yong Wang, Shengxiang Yang, Ke Tang:
An Adaptive Framework to Tune the Coordinate Systems in Evolutionary Algorithms. CoRR abs/1703.06263 (2017) - 2016
- [j57]Yuan Zhang, Mao Peng, Shengxiang Yang:
A clique-based online algorithm for constructing optical orthogonal codes. Appl. Soft Comput. 47: 21-32 (2016) - [j56]Zhijian Li, Jinglei Guo, Shengxiang Yang:
Improving the JADE algorithm by clustering successful parameters. IJWMC 11(3): 190-197 (2016) - [j55]Jayne Eaton, Shengxiang Yang, Michalis Mavrovouniotis:
Ant colony optimization with immigrants schemes for the dynamic railway junction rescheduling problem with multiple delays. Soft Comput. 20(8): 2951-2966 (2016) - [j54]Shouyong Jiang, Shengxiang Yang:
An Improved Multiobjective Optimization Evolutionary Algorithm Based on Decomposition for Complex Pareto Fronts. IEEE Trans. Cybernetics 46(2): 421-437 (2016) - [j53]Changhe Li, Trung Thanh Nguyen, Ming Yang, Michalis Mavrovouniotis, Shengxiang Yang:
An Adaptive Multipopulation Framework for Locating and Tracking Multiple Optima. IEEE Trans. Evolutionary Computation 20(4): 590-605 (2016) - [j52]Miqing Li, Shengxiang Yang, Xiaohui Liu:
Pareto or Non-Pareto: Bi-Criterion Evolution in Multiobjective Optimization. IEEE Trans. Evolutionary Computation 20(5): 645-665 (2016) - [c94]Michalis Mavrovouniotis, Shengxiang Yang:
Empirical study on the effect of population size on MAX-MIN ant system in dynamic environments. CEC 2016: 853-860 - [c93]Jinglei Guo, Shengxiang Yang, Shouyong Jiang:
An adaptive penalty-based boundary intersection approach for multiobjective evolutionary algorithm based on decomposition. CEC 2016: 2145-2152 - [c92]Zhi-Zhong Liu, Yong Wang, Shengxiang Yang, Zixing Cai:
Differential evolution with a two-stage optimization mechanism for numerical optimization. CEC 2016: 3170-3177 - [c91]Jia-Peng Li, Yong Wang, Shengxiang Yang, Zixing Cai:
A comparative study of constraint-handling techniques in evolutionary constrained multiobjective optimization. CEC 2016: 4175-4182 - [c90]Michalis Mavrovouniotis, Shengxiang Yang:
Direct Memory Schemes for Population-Based Incremental Learning in Cyclically Changing Environments. EvoApplications (2) 2016: 233-247 - [c89]Renato Tinós, Shengxiang Yang:
Artificially Inducing Environmental Changes in Evolutionary Dynamic Optimization. PPSN 2016: 225-236 - [c88]Shouyong Jiang, Shengxiang Yang:
Convergence Versus Diversity in Multiobjective Optimization. PPSN 2016: 984-993 - [c87]Darren M. Chitty, Mario Gongora, Shengxiang Yang:
Evolutionary dynamic optimisation of airport security lane schedules. SSCI 2016: 1-8 - [c86]Jayne Eaton, Shengxiang Yang:
Railway platform reallocation after dynamic perturbations using ant colony optimisation. SSCI 2016: 1-8 - [c85]Shouyong Jiang, Shengxiang Yang, Miqing Li:
On the use of hypervolume for diversity measurement of Pareto front approximations. SSCI 2016: 1-8 - [c84]Conor Fahy, Shengxiang Yang:
Dynamic Stream Clustering Using Ants. UKCI 2016: 495-508 - 2015
- [j51]Miqing Li, Shengxiang Yang, Xiaohui Liu:
Bi-goal evolution for many-objective optimization problems. Artif. Intell. 228: 45-65 (2015) - [j50]Michalis Mavrovouniotis, Shengxiang Yang:
Ant algorithms with immigrants schemes for the dynamic vehicle routing problem. Inf. Sci. 294: 456-477 (2015) - [j49]Changhe Li, Trung Thanh Nguyen, Ming Yang, Shengxiang Yang, Sanyou Zeng:
Multi-population methods in unconstrained continuous dynamic environments: The challenges. Inf. Sci. 296: 95-118 (2015) - [j48]Michalis Mavrovouniotis, Shengxiang Yang:
Training neural networks with ant colony optimization algorithms for pattern classification. Soft Comput. 19(6): 1511-1522 (2015) - [j47]Wei Fang, Shengxiang Yang, Xin Yao:
A Survey on Problem Models and Solution Approaches to Rescheduling in Railway Networks. IEEE Trans. Intelligent Transportation Systems 16(6): 2997-3016 (2015) - [c83]Michalis Mavrovouniotis, Ferrante Neri, Shengxiang Yang:
An adaptive local search algorithm for real-valued dynamic optimization. CEC 2015: 1388-1395 - [c82]Michalis Mavrovouniotis, Shengxiang Yang:
Applying Ant Colony Optimization to Dynamic Binary-Encoded Problems. EvoApplications 2015: 845-856 - [c81]Michalis Mavrovouniotis, Felipe Martins Müller, Shengxiang Yang:
An Ant Colony Optimization Based Memetic Algorithm for the Dynamic Travelling Salesman Problem. GECCO 2015: 49-56 - [c80]Shengxiang Yang:
Evolutionary Computation for Dynamic Optimization Problems. GECCO (Companion) 2015: 629-649 - [c79]Miqing Li, Shengxiang Yang, Xiaohui Liu:
A Performance Comparison Indicator for Pareto Front Approximations in Many-Objective Optimization. GECCO 2015: 703-710 - [c78]Michalis Mavrovouniotis, Shengxiang Yang:
Population-Based Incremental Learning with Immigrants Schemes in Changing Environments. SSCI 2015: 1444-1451 - [c77]Jun Qi, Liming Chen, Wolfgang Leister, Shengxiang Yang:
Towards Knowledge Driven Decision Support for Personalized Home-Based Self-Management of Chronic Diseases. UIC/ATC/ScalCom 2015: 1724-1729 - 2014
- [j46]Miqing Li, Shengxiang Yang, Jinhua Zheng, Xiaohui Liu:
ETEA: A Euclidean Minimum Spanning Tree-Based Evolutionary Algorithm for Multi-Objective Optimization. Evolutionary Computation 22(2): 189-230 (2014) - [j45]Changhe Li, Shengxiang Yang, Ming Yang:
An Adaptive Multi-Swarm Optimizer for Dynamic Optimization Problems. Evolutionary Computation 22(4): 559-594 (2014) - [j44]Renato Tinós, Shengxiang Yang:
Analysis of fitness landscape modifications in evolutionary dynamic optimization. Inf. Sci. 282: 214-236 (2014) - [j43]Weijian Kong, Tianyou Chai, Jinliang Ding, Shengxiang Yang:
Multifurnace Optimization in Electric Smelting Plants by Load Scheduling and Control. IEEE Trans. Automation Science and Engineering 11(3): 850-862 (2014) - [j42]Miqing Li, Shengxiang Yang, Ke Li, Xiaohui Liu:
Evolutionary Algorithms With Segment-Based Search for Multiobjective Optimization Problems. IEEE Trans. Cybernetics 44(8): 1295-1313 (2014) - [j41]Miqing Li, Shengxiang Yang, Xiaohui Liu:
Diversity Comparison of Pareto Front Approximations in Many-Objective Optimization. IEEE Trans. Cybernetics 44(12): 2568-2584 (2014) - [j40]Miqing Li, Shengxiang Yang, Xiaohui Liu:
Shift-Based Density Estimation for Pareto-Based Algorithms in Many-Objective Optimization. IEEE Trans. Evolutionary Computation 18(3): 348-365 (2014) - [c76]Shouyong Jiang, Shengxiang Yang:
An improved quantum-behaved particle swarm optimization algorithm based on linear interpolation. IEEE Congress on Evolutionary Computation 2014: 769-775 - [c75]Michalis Mavrovouniotis, Shengxiang Yang:
Interactive and non-interactive hybrid immigrants schemes for ant algorithms in dynamic environments. IEEE Congress on Evolutionary Computation 2014: 1542-1549 - [c74]Michalis Mavrovouniotis, Shengxiang Yang:
Elitism-based immigrants for ant colony optimization in dynamic environments: Adapting the replacement rate. IEEE Congress on Evolutionary Computation 2014: 1752-1759 - [c73]Miqing Li, Shengxiang Yang, Xiaohui Liu:
A test problem for visual investigation of high-dimensional multi-objective search. IEEE Congress on Evolutionary Computation 2014: 2140-2147 - [c72]Michalis Mavrovouniotis, Shengxiang Yang, Xin Yao:
Multi-colony ant algorithms for the dynamic travelling salesman problem. CIDUE 2014: 9-16 - [c71]Shouyong Jiang, Shengxiang Yang:
A framework of scalable dynamic test problems for dynamic multi-objective optimization. CIDUE 2014: 32-39 - [c70]Michalis Mavrovouniotis, Shengxiang Yang:
Ant colony optimization with self-adaptive evaporation rate in dynamic environments. CIDUE 2014: 47-54 - [c69]Jayne Eaton, Shengxiang Yang:
Dynamic railway junction rescheduling using population based ant colony optimisation. UKCI 2014: 1-8 - [c68]Shouyong Jiang, Shengxiang Yang:
A benchmark generator for dynamic multi-objective optimization problems. UKCI 2014: 1-8 - 2013
- [j39]Weijian Kong, Tianyou Chai, Shengxiang Yang, Jinliang Ding:
A hybrid evolutionary multiobjective optimization strategy for the dynamic power supply problem in magnesia grain manufacturing. Appl. Soft Comput. 13(5): 2960-2969 (2013) - [j38]Michalis Mavrovouniotis, Shengxiang Yang:
Ant colony optimization with immigrants schemes for the dynamic travelling salesman problem with traffic factors. Appl. Soft Comput. 13(10): 4023-4037 (2013) - [j37]Hui Cheng, Shengxiang Yang, Jiannong Cao:
Dynamic genetic algorithms for the dynamic load balanced clustering problem in mobile ad hoc networks. Expert Syst. Appl. 40(4): 1381-1392 (2013) - [j36]Yan Cui, Min Huang, Shengxiang Yang, Loo Hay Lee, Xingwei Wang:
Fourth party logistics routing problem model with fuzzy duration time and cost discount. Knowl.-Based Syst. 50: 14-24 (2013) - [j35]Shengxiang Yang, Miqing Li, Xiaohui Liu, Jinhua Zheng:
A Grid-Based Evolutionary Algorithm for Many-Objective Optimization. IEEE Trans. Evolutionary Computation 17(5): 721-736 (2013) - [c67]Michalis Mavrovouniotis, Shengxiang Yang:
Genetic algorithms with adaptive immigrants for dynamic environments. IEEE Congress on Evolutionary Computation 2013: 2130-2137 - [c66]Weijian Kong, Jinliang Ding, Tianyou Chai, Xiuping Zheng, Shengxiang Yang:
A multiobjective particle swarm optimization algorithm for load scheduling in electric smelting furnaces. CIES 2013: 188-195 - [c65]Miqing Li, Shengxiang Yang, Xiaohui Liu, Kang Wang:
IPESA-II: Improved Pareto Envelope-Based Selection Algorithm II. EMO 2013: 143-155 - [c64]Miqing Li, Shengxiang Yang, Xiaohui Liu, Ruimin Shen:
A Comparative Study on Evolutionary Algorithms for Many-Objective Optimization. EMO 2013: 261-275 - [c63]Michalis Mavrovouniotis, Shengxiang Yang:
Adapting the Pheromone Evaporation Rate in Dynamic Routing Problems. EvoApplications 2013: 606-615 - [c62]Shengxiang Yang:
Evolutionary computation for dynamic optimization problems. GECCO (Companion) 2013: 667-682 - [c61]Michalis Mavrovouniotis, Shengxiang Yang:
Evolving neural networks using ant colony optimization with pheromone trail limits. UKCI 2013: 16-23 - [p4]Hendrik Richter, Shengxiang Yang:
Dynamic Optimization Using Analytic and Evolutionary Approaches: A Comparative Review. Handbook of Optimization 2013: 1-28 - [p3]Michalis Mavrovouniotis, Shengxiang Yang:
Dynamic Vehicle Routing: A Memetic Ant Colony Optimization Approach. Automated Scheduling and Planning 2013: 283-301 - 2012
- [j34]Hui Cheng, Shengxiang Yang, Xingwei Wang:
Immigrants-Enhanced Multi-Population Genetic Algorithms for Dynamic Shortest Path Routing Problems in Mobile Ad Hoc Networks. Applied Artificial Intelligence 26(7): 673-695 (2012) - [j33]Hongfeng Wang, Shengxiang Yang, W. H. Ip, Dingwei Wang:
A memetic particle swarm optimisation algorithm for dynamic multi-modal optimisation problems. Int. J. Systems Science 43(7): 1268-1283 (2012) - [j32]Lili Liu, Shengxiang Yang, Dingwei Wang:
Force-imitated particle swarm optimization using the near-neighbor effect for locating multiple optima. Inf. Sci. 182(1): 139-155 (2012) - [j31]Hongfeng Wang, Ilkyeong Moon, Shengxiang Yang, Dingwei Wang:
A memetic particle swarm optimization algorithm for multimodal optimization problems. Inf. Sci. 197: 38-52 (2012) - [j30]Trung Thanh Nguyen, Shengxiang Yang, Jürgen Branke:
Evolutionary dynamic optimization: A survey of the state of the art. Swarm and Evolutionary Computation 6: 1-24 (2012) - [j29]