default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDGECCO 2018: Kyoto, Japan - Companion Material
- Hernán E. Aguirre, Keiki Takadama:
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2018, Kyoto, Japan, July 15-19, 2018. ACM 2018, ISBN 978-1-4503-5764-7
Competition entry: internet of things: online anomaly detection for drinking water quality
- Victor Henrique Alves Ribeiro
, Gilberto Reynoso-Meza:
Online anomaly detection for drinking water quality using a multi-objective machine learning approach. 1-2 - Xingguo Chen, Fan Feng, Jikai Wu, Wenyu Liu:
Anomaly detection for drinking water quality via deep biLSTM ensemble. 3-4 - Valerie Fehst, Huu Chuong La, Tri-Duc Nghiem, Ben E. Mayer, Paul Englert, Karl-Heinz Fiebig:
Automatic vs. manual feature engineering for anomaly detection of drinking-water quality. 5-6
Hot off the press
- Aitor Arrieta, Shuai Wang, Urtzi Markiegi, Goiuria Sagardui, Leire Etxeberria:
Employing multi-objective search to enhance reactive test generation and prioritization for testing industrial cyber-physical systems. 7-8 - Francisco Chávez de la O, Francisco Fernández de Vega, Josefa Díaz, Juan Ángel García, Francisco J. Rodríguez, Pedro A. Castillo:
Energy-consumption prediction of genetic programming algorithms using a fuzzy rule-based system. 9-10 - Dogan Corus, Pietro S. Oliveto:
Standard steady state genetic algorithms can hillclimb faster than evolutionary algorithms using standard bit mutation. 11-12 - Benjamin Doerr:
Better runtime guarantees via stochastic domination (hot-off-the-press track at GECCO 2018). 13-14 - Tome Eftimov, Peter Korosec, Barbara Korousic-Seljak:
Deep statistical comparison of meta-heuristic stochastic optimization algorithms. 15-16 - Michael Fenton, David Lynch, David Fagan, Stepán Kucera, Holger Claussen, Michael O'Neill:
Towards automation & augmentation of the design of schedulers for cellular communications networks. 17-18 - Kai-Cheng Hsu, Feng-Sheng Wang:
Detection of minimum biomarker features via bi-level optimization framework by nested hybrid differential evolution. 19-20 - Sara Khanchi, Ali Vahdat, Malcolm I. Heywood, Nur Zincir-Heywood:
On botnet detection with genetic programming under streaming data, label budgets and class imbalance. 21-22 - William G. La Cava, Sara Silva, Kourosh Danai, Lee Spector, Leonardo Vanneschi, Jason H. Moore:
A multidimensional genetic programming approach for identifying epsistatic gene interactions. 23-24 - Krzysztof Michalak:
ED-LS: a heuristic local search for the firefighter problem. 25-26 - Jakub Nalepa, Miroslaw Blocho:
Parameter-less (meta)heuristics for vehicle routing problems. 27-28 - Moshe Sipper, Weixuan Fu, Karuna Ahuja, Jason H. Moore:
Evolutionary computation: an investigation of parameter space. 29-30 - Dennis G. Wilson, Silvio Rodrigues, Carlos Segura, Ilya Loshchilov, Frank Hutter, Guillermo López Buenfil, Ahmed Kheiri, Ed Keedwell, Mario Ocampo-Pineda, Ender Özcan, Sergio Iwan Valdez Pea, Brian Goldman, Salvador Botello Rionda, Arturo Hernández Aguirre, Kalyan Veeramachaneni, Sylvain Cussat-Blanc:
Summary of evolutionary computation for wind farm layout optimization. 31-32
Late-breaking abstract
- Pei-Ling Chiu, Kai-Hui Lee:
Optimization based adaptive tagged visual cryptography. 33-34 - Hwi-Yeon Cho, Hye-Jin Kim, Yong-Hyuk Kim:
Parameter space analysis of genetic algorithm using support vector regression. 35-36 - David Dohan, David R. So, Quoc V. Le:
Evolving modular neural sequence architectures with genetic programming. 37-38 - Kousuke Fujimoto, Kei Ohnishi, Tomohiro Yoshikawa:
The human-based evolutionary computation system enabling us to follow the solution evolution. 39-40 - Masaki Fujiwara, Masaharu Munetomo:
A surrogate-assisted selection scheme for genetic algorithms employing multi-layer neural networks. 41-42 - Ryoichi Hasegawa, Hisashi Handa:
Investigation of kernel functions in EDA-GK. 43-44 - Thommen George Karimpanal:
A self-replication basis for designing complex agents. 45-46 - Jacob Krantz, Maxwell Dulin, Paul De Palma, Mark VanDam:
Syllabification by phone categorization. 47-48 - Junghwan Lee, Yong-Hyuk Kim:
Importance of finding a good basis in binary representation. 49-50 - Hyeon-Chang Lee, Dong-Pil Yu, Yong-Hyuk Kim:
On the hardness of parameter optimization of convolution neural networks using genetic algorithm and machine learning. 51-52 - Yong-Wook Nam, Yong-Hyuk Kim:
A geometric evolutionary search for melody composition. 53-54 - Hiro Ohtsuka, Misaki Kaidan, Tomohiro Harada, Ruck Thawonmas:
Evolutionary algorithm using surrogate assisted model for simultaneous design optimization benchmark problem of multiple car structures. 55-56 - Keiko Ono, Yoshiko Hanada:
Accelerating genetic programming using pycuda. 57-58 - Patryk Orzechowski, Moshe Sipper, Xiuzhen Huang, Jason H. Moore:
EBIC: a next-generation evolutionary-based parallel biclustering method. 59-60 - Evgenia Papavasileiou, Bart Jansen:
Configuring the parameters of artificial neural networks using neuroevoiution and automatic algorithm configuration. 61-62 - Krzysztof Pawelczyk, Michal Kawulok, Jakub Nalepa:
Genetically-trained deep neural networks. 63-64 - Anselmo C. Pontes, Charles Ofria:
Digital investigations on the evolution of prokaryote photosynthesis regulation: late-breaking abstract. 65-66 - Katya Rodríguez-Vázquez:
GA and entropy objective function for solving sudoku puzzle. 67-68 - Yuji Sato, Mikiko Sato, Minami Miyakawa:
Distributed NSGA-II sharing extreme non-dominated solutions. 69-70 - Mariko Tanaka, Yuki Yamagishi, Hidetoshi Nagai, Hiroyuki Sato:
Infeasible solution repair and MOEA/D sharing weight vectors for solving multi-objective set packing problems. 71-72 - Heng Xiao, Toshiharu Hatanaka:
Hybrid swarm of particle swarm with firefly for complex function optimization. 73-74 - Tao Xiong:
Forecasting soybean futures price using dynamic model averaging and particle swarm optimization. 75-76 - Dong-Pil Yu, Yong-Hyuk Kim:
Is it worth to approximate fitness by machine learning?: investigation on the extensibility according to problem size. 77-78 - Tanja Zerenner, Victor Venema, Petra Friederichs, Clemens Simmer:
Deterministic and stochastic precipitation downscaling using multi-objective genetic programming. 79-80
Poster: ant colony optimization and swarm intelligence
- Claus Aranha, Jair Pereira Junior, Hitoshi Kanoh:
Comparative study on discrete SI approaches to the graph coloring problem. 81-82 - Stephyn G. W. Butcher, John W. Sheppard, Brian K. Haberman:
Comparative performance and scaling of the pareto improving particle swarm optimization algorithm. 83-84 - Carlos M. Fernandes, Agostinho C. Rosa, Nuno Fachada, Juan Luis Jiménez Laredo, Juan Julián Merelo Guervós:
Particle swarm and population structure. 85-86 - Xin-Chi Han, Hao-Wen Ke, Yue-Jiao Gong, Ying Lin, Wei-Li Liu, Jun Zhang:
Multimodal optimization of traveling salesman problem: a niching ant colony system. 87-88 - Zainab Husain, Dymitr Ruta, Fabrice Saffre, Yousof Al-Hammadi, A. F. Isakovic:
Inverted ant colony optimization for search and rescue in an unknown maze-like indoor environment. 89-90 - Chengyu Lu, Jinghui Zhong:
An efficient ant colony system for coverage based test case prioritization. 91-92 - Hu Peng, Changshou Deng, Hui Wang, Wenjun Wang, Xinyu Zhou, Zhijian Wu:
Gaussian bare-bones cuckoo search algorithm. 93-94 - Ryo Takano, Hiroyuki Sato, Keiki Takadama:
Artificial bee colony algorithm based on adaptive local information sharing: approach for several dynamic changes. 95-96 - Yuta Umenai, Fumito Uwano, Hiroyuki Sato, Keiki Takadama:
Multiple swarm intelligence methods based on multiple population with sharing best solution for drastic environmental change. 97-98 - Jun Yu, Ying Tan, Hideyuki Takagi:
Scouting strategy for biasing fireworks algorithm search to promising directions. 99-100 - Asaduz Zaman, Seong Young Ko:
Improving the accuracy of 2D-3D registration of femur bone for bone fracture reduction robot using particle swarm optimization. 101-102
Poster: complex systems (artificial life/artificial immune systems/generative and developmental systems/evolutionary robotics/evolvable hardware)
- Zaineb Chelly Dagdia:
A distributed dendritic cell algorithm for big data. 103-104 - Emily L. Dolson, Charles Ofria:
Ecological theory provides insights about evolutionary computation. 105-106 - Stéphane Doncieux, Alexandre Coninx:
Open-ended evolution with multi-containers QD. 107-108 - Chrisantha Fernando, Jakub Sygnowski, Simon Osindero, Jane Wang, Tom Schaul, Denis Teplyashin, Pablo Sprechmann, Alexander Pritzel, Andrei A. Rusu:
Meta-learning by the baldwin effect. 109-110 - Chia-Feng Juang, Yu-Cheng Chang, I-Fang Chung:
Evolutionary hexapod robot gait control using a new recurrent neural network learned through group-based hybrid metaheuristic algorithm. 111-112 - Jared M. Moore, Anthony J. Clark:
Bend and flex: passive flexibility or active control in a quadruped animat. 113-114 - Olaf Witkowski, Geoff Nitschke:
The dynamics of cooperation versus competition. 115-116 - Sabre Didi, Geoff Nitschke:
Policy transfer methods in RoboCup keep-away. 117-118 - Joshua P. Powers, Sam Kriegman, Josh C. Bongard:
Embodiment can combat catastrophic forgetting. 119-120 - Zhenyue Qin, Tom Gedeon, Robert I. McKay:
Why don't the modules dominate? 121-122 - Eric O. Scott, Kenneth A. De Jong:
Toward learning neural network encodings for continuous optimization problems. 123-124
Poster: digital entertainment technologies and arts
- Makoto Fukumoto, Kota Nomura:
A proposal for distributed interactive differential evolution: in a case of creating sign sounds for multiple users. 125-126 - Pablo González de Prado Salas, Sebastian Risi:
Collaborative interactive evolution in minecraft. 127-128 - Man-Je Kim, Chang Wook Ahn:
Hybrid fighting game AI using a genetic algorithm and Monte Carlo tree search. 129-130 - Marco Scirea, Peter W. Eklund, Julian Togelius, Sebastian Risi:
Towards an experiment on perception of affective music generation using MetaCompose. 131-132 - Takuto Shigenobu, Takuya Ushinohama, Hiroshi Kawasaki, Satoshi Ono:
Silhouette-based three dimensional image registration using CMA-ES with joint scheme of partial restart and variable fixing. 133-134
Poster: evolutionary combinatorial optimization and metaheuristics
- Alexander E. I. Brownlee, John R. Woodward, Nadarajen Veerapen:
Relating training instances to automatic design of algorithms for bin packing via features. 135-136 - Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
Distance-based exponential probability models on constrained combinatorial optimization problems. 137-138 - Onur Kaya, Dogus Ozkok:
A network design problem with location, inventory and routing decisions. 139-140 - Yi Mei, Mengjie Zhang:
Genetic programming hyper-heuristic for multi-vehicle uncertain capacitated arc routing problem. 141-142 - Li-Tao Tan, Wei-Neng Chen, Jun Zhang:
A histogram estimation of distribution algorithm for resource scheduling. 143-144 - Mehmet Fatih Tasgetiren, Ugur Eliiyi, Hande Öztop, Damla Kizilay, Quan-Ke Pan:
An energy-efficient single machine scheduling with release dates and sequence-dependent setup times. 145-146 - Chen Wang, Hui Ma, Gang Chen:
EDA-based approach to comprehensive quality-aware automated semantic web service composition. 147-148 - Daniel Yska, Yi Mei, Mengjie Zhang:
Feature construction in genetic programming hyper-heuristic for dynamic flexible job shop scheduling. 149-150 - Hansang Yun, Byung-Ro Moon:
An efficient approximation to the barrier tree using the great deluge algorithm. 151-152 - Zhi-Wei Zeng, Xiao-Min Hu, Min Li, Yu Luo:
Local intensity in memetic algorithm: case study in CARP. 153-154
Poster: evolutionary machine learning
- Bassel Ali, Wasin Kalintha, Koichi Moriyama, Masayuki Numao, Ken-ichi Fukui:
Reinforcement learning for evolutionary distance metric learning systems improvement. 155-156 - Travis Desell:
Accelerating the evolution of convolutional neural networks with node-level mutations and epigenetic weight initialization. 157-158 - Jan-Benedikt Jagusch, Ivo Gonçalves, Mauro Castelli:
Neuroevolution under unimodal error landscapes: an exploration of the semantic learning machine algorithm. 159-160 - David Kadish:
Clustering sensory inputs using NeuroEvolution of augmenting topologies. 161-162 - Lukas Kammerer, Michael Affenzeller:
Confidence-based ensemble modeling in medical data mining. 163-164 - Saso Karakatic, Vili Podgorelec:
Building boosted classification tree ensemble with genetic programming. 165-166 - Dipanjyoti Paul, Sriparna Saha, Jimson Mathew:
Multiobjective optimization based subspace clustering using evolvable genome structure. 167-168 - Koki Shimada, Peter J. Bentley:
Learning how to flock: deriving individual behaviour from collective behaviour with multi-agent reinforcement learning and natural evolution strategies. 169-170 - Kuan-Wu Su, Min-Chieh Yu, Jenq-Shiou Leu:
A neuroevolution strategy using multi-agent incorporated hierarchical ensemble model. 171-172 - Shuwei Zhu, Lihong Xu, Leilei Cao:
A study of automatic clustering based on evolutionary many-objective optimization. 173-174
Poster: evolutionary multiobjective optimization
- Abdelhakim Cheriet, Roberto Santana:
Modeling dependencies between decision variables and objectives with copula models. 175-176 - Hiroaki Fukumoto, Akira Oyama:
Benchmarking multiobjective evolutionary algorithms and constraint handling techniques on a real-world car structure design optimization benchmark problem. 177-178 - Kousuke Izumiya, Masaharu Munetomo:
Introducing a linkage identification considering non-monotonicity to multi-objective evolutionary optimization with decomposition for real-valued functions. 179-180 - Francia Jiménez, Claudio Sanhueza, Regina Berretta, Pablo Moscato:
Accelerating a multi-objective memetic algorithm for feature selection using hierarchical k-means indexes. 181-182 - Takehisa Kohira, Hiromasa Kemmotsu, Akira Oyama, Tomoaki Tatsukawa:
Proposal of benchmark problem based on real-world car structure design optimization. 183-184 - William G. La Cava, Jason H. Moore:
An analysis of ϵ-lexicase selection for large-scale many-objective optimization. 185-186 - Longmei Li, Hao Chen, Jing Wu, Jun Li, Ning Jing, Michael Emmerich:
Preference-based evolutionary algorithms for many-objective mission planning of agile earth observation satellites. 187-188 - Yuri Marca, Hernán E. Aguirre, Saúl Zapotecas Martínez, Arnaud Liefooghe, Bilel Derbel, Sébastien Vérel, Kiyoshi Tanaka:
Pareto dominance-based MOEAs on problems with difficult pareto set topologies. 189-190 - Hugo Monzón, Hernán E. Aguirre, Sébastien Vérel, Arnaud Liefooghe, Bilel Derbel, Kiyoshi Tanaka:
Studying MOEAs dynamics and their performance using a three compartmental model. 191-192 - Miriam Pescador-Rojas, Carlos A. Coello Coello:
Studying the effect of techniques to generate reference vectors in many-objective optimization. 193-194 - Proteek Chandan Roy, Julian Blank, Rayan Hussein, Kalyanmoy Deb:
Trust-region based algorithms with low-budget for multi-objective optimization. 195-196 - Julian Schulte, Niclas Feldkamp, Sören Bergmann, Volker Nissen:
Bilevel innovization: knowledge discovery in scheduling systems using evolutionary bilevel optimization and visual analytics. 197-198 - Jianyong Sun, Hu Zhang, Qingfu Zhang, Huanhuan Chen:
Balancing exploration and exploitation in multiobjective evolutionary optimization. 199-200 - A. K. M. Khaled Ahsan Talukder, Kalyanmoy Deb, Julian Blank:
Visualization of the boundary solutions of high dimensional pareto front from a decision maker's perspective. 201-202 - Junchen Wang, Changhe Li, Yiya Diao, Sanyou Zeng, Hui Wang:
An efficient nondominated sorting algorithm. 203-204 - Ilya Yakupov, Maxim Buzdalov:
On asynchronous non-dominated sorting for steady-state multiobjective evolutionary algorithms. 205-206
Poster: evolutionary numerical optimization
- Tae Jong Choi, Chang Wook Ahn:
Accelerating differential evolution using multiple exponential cauchy mutation. 207-208 - Lee A. Christie, Alexander E. I. Brownlee, John R. Woodward:
Investigating benchmark correlations when comparing algorithms with parameter tuning. 209-210 - Yaodong He, Shiu Yin Yuen, Yang Lou:
Exploratory landscape analysis using algorithm based sampling. 211-212 - Ruwang Jiao, Sanyou Zeng, Changhe Li, Yuhong Jiang:
Dynamic constrained multi-objective evolutionary algorithms with a novel selection strategy for constrained optimization. 213-214 - Genghui Li, Qingfu Zhang, Weifeng Gao:
Multipopulation evolution framework for multifactorial optimization. 215-216 - Yongsheng Liang, Zhigang Ren, Bei Pang, An Chen:
Niching an archive-based gaussian estimation of distribution algorithm via adaptive clustering. 217-218 - Duc Manh Nguyen:
An adapting population size approach in the CMA-ES for multimodal functions. 219-220 - Bei Pang, Zhigang Ren, Yongsheng Liang, An Chen:
Enhancing cooperative coevolution for large scale optimization by adaptively constructing surrogate models. 221-222 - Kiyoharu Tagawa:
Extension of weighted empirical distribution and group-based adaptive differential evolution for joint chance constrained problems. 223-224 - Sander van Rijn, Sebastian Schmitt, Markus Olhofer, Matthijs van Leeuwen, Thomas Bäck:
Multi-fidelity surrogate model approach to optimization. 225-226 - Takahiro Yamaguchi, Youhei Akimoto:
A note on the CMA-ES for functions with periodic variables. 227-228 - Lei Zhou, Liang Feng, Jinghui Zhong, Zexuan Zhu, Bingshui Da, Zhou Wu:
A study of similarity measure between tasks for multifactorial evolutionary algorithm. 229-230
Poster: genetic algorithms
- Yu-Hsiang Chung, Tuan-Fang Fan, Churn-Jung Liau:
A comparative study on algorithms for influence maximization in social networks. 231-232 - José Mario García Valdez, Juan Julián Merelo Guervós:
A modern, event-based architecture for distributed evolutionary algorithms. 233-234 - Lina Hao, Bryan C. K. Ng:
Using genetic algorithms based on neighbor list mechanism to reduce handover latency for IEEE 802.11 WLAN. 235-236 - Andrei Iacob, Mihail Morosan, Francisco Sepulveda, Riccardo Poli:
Genetic optimisation of BCI systems for identifying games related cognitive states. 237-238 - Salvador Moreno, Julio Ortega, Miguel Damas, Antonio F. Díaz, Jesús González, Héctor Pomares:
Prediction of energy consumption in a NSGA-II-based evolutionary algorithm. 239-240