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ORCIDGECCO 2022: Boston, MA, USA
- Jonathan E. Fieldsend, Markus Wagner:
GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9 - 13, 2022. ACM 2022, ISBN 978-1-4503-9268-6
Competition entry: Competition evolutionary computation in the the energy domain: Risk-based energy scheduling
- Ansel Y. Rodríguez González
, Ramón Aranda, Miguel Ángel Álvarez-Carmona, Yoan Martínez-López, Julio Madera Quintana:
Applying ring cellular encode-decode UMDA to risk-based energy scheduling. 1-2
Competition entry: Competition the abstractswarm multi-agent logistics competition
- Patrick A. Winkel:
AbstractSwarm multi-agent logistics competition entry: QPlus. 3-4
Competition entry: Competition real parameter single objective bound constrained optimization
- Hao Ding, Yongfeng Gu, Hua Wu, Jun Zhou:
NL-SOMA-CLP for real parameter single objective bound constrained optimization. 5-6 - Yongfeng Gu, Hao Ding, Hua Wu, Jun Zhou:
Opposite learning and multi-migrating strategy-based self-organizing migrating algorithm with the convergence monitoring mechanism. 7-8 - Yue Ning, Daohong Jian, Hua Wu, Jun Zhou:
Zeroth-order covariance matrix adaptation evolution strategy for single objective bound constrained numerical optimization competition. 9-10
Competition entry: Competition open optimization competition 2022: Better benchmarking of sampling-based optimization algorithms
- Etor Arza, Josu Ceberio, Ekhiñe Irurozki, Aritz Pérez:
Implementing the cumulative difference plot in the IOHanalyzer. 11-12
Hot off the press
- Denis Antipov, Benjamin Doerr:
Precise runtime analysis for plateau functions: (hot-off-the-press track at GECCO 2022). 13-14 - Jon Ayerdi, Valerio Terragni, Aitor Arrieta, Paolo Tonella, Goiuria Sagardui, Maite Arratibel:
Evolutionary generation of metamorphic relations for cyber-physical systems. 15-16 - Marcelo de Souza, Marcus Ritt, Manuel López-Ibáñez:
Efficient configuration of optimization algorithms. 17-18 - Edgar Galván, Leonardo Trujillo, Fergal Stapleton:
Highlights of semantics in multi-objective genetic programming. 19-20 - Jose Guadalupe Hernandez, Alexander Lalejini, Charles Ofria:
Measuring the ability of lexicase selection to find obscure pathways to optimality. 21-22 - Jose Guadalupe Hernandez, Alexander Lalejini, Emily L. Dolson:
Phylogenetic diversity predicts future success in evolutionary computation. 23-24 - Alexander Lalejini, Matthew Andres Moreno, Charles Ofria:
Tag-based module regulation for genetic programming. 25-26 - William B. Langdon:
Genetic programming convergence. 27-28 - William B. Langdon, Wolfgang Banzhaf:
Long-term evolution experiment with genetic programming [hot of the press]. 29-30 - Yi Liu, Will N. Browne, Bing Xue:
A comparison of rule compaction algorithms for michigan style learning classifier systems. 31-32 - Yixing Luo, Xiao-Yi Zhang, Paolo Arcaini, Zhi Jin, Haiyan Zhao, Fuyuki Ishikawa, Rongxin Wu, Tao Xie:
Targeting requirements violations of autonomous driving systems by dynamic evolutionary search (HOP at GECCO'22). 33-34 - Michal Witold Przewozniczek, Marcin M. Komarnicki:
Empirical linkage learning for non-binary discrete search spaces in the optimization of a large-scale real-world problem. 35-36 - Carlos Hernández, Oliver Schütze:
Archivers for single- and multi-objective evolutionary optimization algorithms. 37-38 - Dominik Sobania, Dirk Schweim, Franz Rothlauf:
Program synthesis with evolutionary algorithms: Status quo: hot off the press track (GECCO 2022). 39-40 - Khabat Soltanian, Ali Ebnenasir, Mohsen Afsharchi:
Modular grammatical evolution for the generation of artificial neural networks: (hot-off-the-press track at GECCO 2022). 41-42 - Yang Syu, Chien-Min Wang, Yong-Yi Fanjiang:
A verified application of genetic programming: QoS time series modeling and forecasting for web services. 43-44 - Shouda Wang, Weijie Zheng, Benjamin Doerr:
Choosing the right algorithm with hints from complexity theory: (hot-off-the-press track at GECCO 2022). 45-46 - Xinyi Wang, Paolo Arcaini, Tao Yue, Shaukat Ali:
Generating failing test suites for quantum programs with search (hot off the press track at GECCO 2022). 47-48 - Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck:
IOHanalyzer: Detailed performance analyses for iterative optimization heuristics: hot-off-the-press track @ GECCO 2022. 49-50 - Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck:
Automated configuration of genetic algorithms by tuning for anytime performance: hot-off-the-press track at GECCCO 2022. 51-52 - Weijie Zheng, Yufei Liu, Benjamin Doerr:
A first mathematical runtime analysis of the non-dominated sorting genetic algorithm II (NSGA-II): (hot-off-the-press track at GECCO 2022). 53-54
Late-breaking abstract
- João E. Batista, Sara Silva:
Evolving a cloud-robust water index with genetic programming. 55-56 - Naoya Ikushima, Keiko Ono, Erina Makihara, Sohei Yamakawa, Ryota Shinhama:
CNN structure optimization using differential evolution with individual dependent mechanism. 57-58 - Jolanta Kawulok, Michal Kawulok:
A genetic algorithm for classifying metagenomic data. 59-60 - Egor Kurbatov, Vladimir Mironovich:
Evaluation of inverse selection operators on maximum flow test generation problem. 61-62 - Cullen A. LaKemper, Cehong Wang, Jason A. Yoder:
Biology inspired growth in meta-learning. 63-64 - Matthew Andres Moreno, Emily L. Dolson, Charles Ofria:
Hereditary stratigraphy: genome annotations to enable phylogenetic inference over distributed populations. 65-66 - Jakub Nalepa, Stanislaw Czembor, Wojciech Dudzik, Michal Kawulok:
Evolutionary algorithms meet classical and deep machine learning for skin detection in color images. 67-68 - Sonia Nasri, Hend Bouziri, Wassila Aggoune-Mtalaa:
A population based-approach to address real-life transport on-demand problems. 69-70 - Eneko Osaba, Josu Díaz-de-Arcaya, Leire Orue-Echevarria, Juncal Alonso, Jesus L. Lobo, Gorka Benguria, Iñaki Etxaniz:
PIACERE project: description and prototype for optimizing infrastructure as code deployment configurations. 71-72 - Nixon K. Ronoh, Edna Milgo, Ambrose K. Kiprop, Bernard Manderick, Ann Nowé:
Natural gradient evolution strategies for adaptive sampling. 73-74 - Sohei Yamakawa, Keiko Ono, Erina Makihara, Daisuke Tawara, Shoma Yakushijin, Naoya Ikushima:
Textonmap optimization for spine segmentation using adaptive differential evolution. 75-76
POSTER SESSION: Ant colony optimization and swarm intelligence
- Cong Bao, Qiang Yang, Xu-Dong Gao, Zhenyu Lu, Jun Zhang:
Ant colony optimization with shortest distance biased dispatch for visiting constrained multiple traveling salesmen problem. 77-80 - Stephen Chen, Shanshan Lao, Irene Moser:
Particle swarm optimization with average-fitness based selection. 81-84 - Alberto Ortega, Juan José Escobar, Miguel Damas, Andrés Ortiz, Jesús González:
Ant colony optimization for feature selection via a filter-randomized search heuristic. 85-88 - Guofang Wang, Xiao Zhang, Wang Yao, Lu Ren:
Cooperative attack-defense evolution of large-scale agents: a multi-population high-dimensional mean-field game approach. 89-92 - Ye-Qun Wang, Chun-Hua Chen, Jun Zhang, Zhi-Hui Zhan:
Dropout topology-assisted bidirectional learning particle swarm optimization for neural architecture search. 93-96 - Xun Zhou, Hongwei Chen, Dewei Shi:
A chaotic parallel antlion optimization algorithm for feature selection. 97-99
POSTER SESSION: Complex systems (artificial life, artificial immune systems, generative and developmental systems, evolutionary robotics evolvable hardware)
- Nicolas Cambier, Eliseo Ferrante:
AutoMoDe-pomodoro: an evolutionary class of modular designs. 100-103 - Q. Tyrell Davis, Josh C. Bongard:
Selecting continuous life-like cellular automata for halting unpredictability: evolving for abiogenesis. 104-107 - Caitlin Grasso, Josh C. Bongard:
Empowered neural cellular automata. 108-111 - Jörn Hoffmann, Clemens Fritzsch, Martin Bogdan:
CoBEA: framework for evolving hardware by direct manipulation of FPGA bitstreams. 112-115 - Tanja Katharina Kaiser, Heiko Hamann:
Minimize surprise MAP-elites: a task-independent MAP-elites variant for swarms. 116-119 - Emiel M. W. Kempen, Ágoston E. Eiben:
Evolving robot bodies with a sense of direction. 120-123 - Adam Klejda, Maciej Komosinski, Agnieszka Mensfelt:
Diversification techniques and distance measures in evolutionary design of 3D structures. 124-127 - Bryan Lim, Maxime Allard, Luca Grillotti, Antoine Cully:
QDax: on the benefits of massive parallelization for quality-diversity. 128-131 - Junxiu Liu, Jufang Dai, Min Su, Shunsheng Zhang, Yifan Hua, Yanhu Wang, Haiping Shu:
De-redundancy in a random boolean network using knockout. 132-135 - Dries Marzougui, Matthijs Biondina, Francis Wyffels:
A comparative analysis on genome pleiotropy for evolved soft robots. 136-139 - Martín Naya-Varela, Andrés Faiña, Richard J. Duro:
Growth-based morphological development: a natural approach to fitness landscape shaping. 140-143 - Brandon Gower-Winter, Geoff Nitschke:
Do harsher environments cause selfish or altruistic behavior? 144-147 - Sidney Pontes-Filho, Kathryn Walker, Elias Najarro, Stefano Nichele, Sebastian Risi:
A single neural cellular automaton for body-brain co-evolution. 148-151 - Mostafa Rizk, Julian Garcia, Aldeida Aleti, David Green:
Using evolutionary game theory to understand scalability in task allocation. 152-155 - Achkan Salehi, Alexandre Coninx, Stéphane Doncieux:
Geodesics, non-linearities and the archive of novelty search. 156-159 - Yuji Sato, Yoshihisa Murakawa:
Comparison of evolutionary multi-objective optimization algorithms using imitation game. 160-163 - Frank Veenstra, Martin Herring Olsen, Kyrre Glette:
Effects of encodings and quality-diversity on evolving 2D virtual creatures. 164-167
POSTER SESSION: Evolutionary combinatorial optimization and metaheuristics
- Utku Umur Acikalin, Bugra Çaskurlu:
Multilevel memetic hypergraph partitioning with greedy recombination. 168-171 - Aldeida Aleti, Mark Wallace, Markus Wagner:
Neighbours similar fitness and the effectiveness of restarting local search. 172-175 - Miroslaw Blocho, Tomasz Jastrzab, Jakub Nalepa:
Cooperative co-evolutionary memetic algorithm for pickup and delivery problem with time windows. 176-179 - Xiang-Ling Chen, Zhi-Xuan Zhang, Ming-Can Geng, Wei-Neng Chen:
Multi-workflow scheduling in industrial edge: a genetic algorithm with heuristic strategy. 180-183 - Marcos Diez García, Mayowa Ayodele, Alberto Moraglio:
Exact and sequential penalty weights in quadratic unconstrained binary optimisation with a digital annealer. 184-187 - Mohamed El Yafrani, Marcella Scoczynski Ribeiro Martins, Myriam R. B. S. Delgado, Ricardo Lüders, Peter Nielsen, Markus Wagner:
On the fitness landscapes of interdependency models in the travelling thief problem. 188-191 - Thomas Feutrier, Nadarajen Veerapen, Marie-Eléonore Kessaci:
Exploiting landscape features for fitness prediction in university timetabling. 192-195 - Amir Nasiri, Ed Keedwell, Raphaël Dorne, Mathias Kern, Gilbert Owusu:
A hyper-heuristic approach for the PDPTW. 196-199 - Franciszek Seredynski, Tomasz Kulpa, Rolf Hoffmann:
Towards evolutionary self-optimization of large multi-agent systems. 200-203 - Ailing Shen, Juan Lin, Yiwen Zhong:
External archive hybrid genetic algorithm for unequal area facility layout problem. 204-207 - Ning Xu, Tian-Ming Bu:
Policy network for solving flexible job shop scheduling problem with setup times and rescoure constraints. 208-211
POSTER SESSION: Evolutionary machine learning
- Ayhan Alp Aydeniz, Anna Nickelson, Kagan Tumer:
Entropy-based local fitnesses for evolutionary multiagent systems. 212-215 - Francisco Baeta, João Correia, Tiago Martins, Penousal Machado:
TGPGAN: towards expression-based generative adversarial networks. 216-219 - Israel Campero-Jurado, Joaquin Vanschoren:
Multi-fidelity optimization method with asynchronous generalized island model for AutoML. 220-223 - Leonardo Lucio Custode, Giovanni Iacca:
Interpretable pipelines with evolutionary optimized modules for reinforcement learning tasks with visual inputs. 224-227 - Taco de Wolff, Hugo Carrillo Lincopi, Luis Martí, Nayat Sánchez Pi:
MOPINNs: an evolutionary multi-objective approach to physics-informed neural networks. 228-231 - Kaan Demir, Bach Hoai Nguyen, Bing Xue, Mengjie Zhang:
Particle swarm optimisation for sparsity-based feature selection in multi-label classification. 232-235 - Gaurav Dixit, Kagan Tumer:
Balancing teams with quality-diversity for heterogeneous multiagent coordination. 236-239 - Wojciech Dudzik, Jakub Nalepa, Michal Kawulok:
Cascades of evolutionary support vector machines. 240-243 - Iztok Fister Jr., Iztok Fister:
On stochastic evolving algorithms. 244-247 - Michael Heider, Helena Stegherr, Jonathan Wurth, Roman Sraj, Jörg Hähner:
Separating rule discovery and global solution composition in a learning classifier system. 248-251 - Daniel Kostrzewa, Michal Ciszynski, Robert Brzeski:
Evolvable hybrid ensembles for musical genre classification. 252-255 - Hoang Lam Le, Ferrante Neri, Dario Landa-Silva, Isaac Triguero:
Accelerated pattern search with variable solution size for simultaneous instance selection and generation. 256-259 - Zi-Xing Li, Xiao-Qi Guo, Wei-Neng Chen, Xiao-Min Hu:
A distributed particle swarm optimization algorithm for distributed clustering. 260-263 - Jiabin Lin, Qi Chen, Bing Xue, Mengjie Zhang:
Multi-task optimisation for multi-objective feature selection in classification. 264-267 - Zheping Liu, Andy Song, Nasser R. Sabar:
KDE-GAN: enhancing evolutionary GAN with knowledge distillation and transfer learning. 268-271 - Sasha Abramowitz, Geoff Nitschke:
Scalable evolutionary hierarchical reinforcement learning. 272-275 - Patryk Orzechowski, Pawel Renc, William G. La Cava, Jason H. Moore, Arkadiusz Sitek, Jaroslaw Was, Joost Wagenaar:
A comparative study of GP-based and state-of-the-art classifiers on a synthetic machine learning benchmark. 276-279 - Golden Rockefeller, Kagan Tumer:
Bootstrapped fitness critics with bidirectional temporal difference. 280-283 - Rihab Said, Maha Elarbi, Slim Bechikh, Carlos A. Coello Coello, Lamjed Ben Said:
Cost-sensitive classification tree induction as a bi-level optimization problem. 284-287 - Jack D. Saunders, Alex Alves Freitas:
GA-auto-PU: a genetic algorithm-based automated machine learning system for positive-unlabeled learning. 288-291 - Nadiya Shvai, Arcadi Llanza, Abul Hasnat, Amir Nakib:
DEvS: data distillation algorithm based on evolution strategy. 292-295 - Sammuel Ramos da Silva, Jadson Castro Gertrudes:
Chaotic genetic bee colony: combining chaos theory and genetic bee algorithm for feature selection in microarray cancer classification. 296-299 - Moshe Sipper:
Binary and multinomial classification through evolutionary symbolic regression. 300-303 - Wei Sun, Qianmu Li, Pengchuan Wang, Jun Hou:
Evolving convolutional neural networks for intrusion detection system using hybrid multi-strategy aquila optimizer. 304-307 - Yujin Tang, Yingtao Tian, David Ha:
EvoJAX: hardware-accelerated neuroevolution. 308-311 - Abhiram Tirumala, Rishi Bhatnager, Sriram Mudireddy, Pranav Manjunath, Jason Zutty:
Designing a novel and high performance algorithmic trading model using evolutionary AutoML and technical analysis. 312-315 - Jonathan Wurth, Michael Heider, Helena Stegherr, Roman Sraj, Jörg Hähner:
Comparing different metaheuristics for model selection in a supervised learning classifier system. 316-319 - Mariia Zameshina, Olivier Teytaud, Fabien Teytaud, Vlad Hosu, Nathanaël Carraz Rakotonirina, Laurent Najman, Markus Wagner:
Fairness in generative modeling: do it unsupervised! 320-323
POSTER SESSION: Evolutionary multiobjective optimization
- Tobias Benecke, Sanaz Mostaghim:
Estimating the quality of initial populations in multi-objective evolutionary algorithms. 324-327 - Susanne Dandl, Florian Pfisterer, Bernd Bischl:
Multi-objective counterfactual fairness. 328-331 - Felipe Honjo Ide, Hernán E. Aguirre, Minami Miyakawa, Darrell Whitley:
Exploring the decision and objective space of SAT constrained multi-objective problems. 332-335 - Stanislaw Kozdrowski, Kacper Wnuk:
Application of nature inspired algorithms to multi-objective optimization of new generation network problem. 336-339 - Claudio Lucio do Val Lopes, Flávio Vinícius Cruzeiro Martins, Elizabeth F. Wanner, Kalyanmoy Deb:
A computationally fast but approximate MIP-DoM calculation for multi-objective optimization. 340-343 - Ons Maâtouk, Emna Ayari, Hend Bouziri, Wassim Ayadi:
BOBEA: a bi-objective biclustering evolutionary algorithm for genome-wide association analysis. 344-347 - Jesús-Adolfo Mejía-de-Dios, Alejandro Rodríguez-Molina, Efrén Mezura-Montes:
A novel evolutionary framework based on a family concept for solving multi-objective bilevel optimization problems. 348-351 - Nisrine Mouhrim, Sergiy Smetana, Anita Bhatia, Alexander Mathys, Ashley Green, Daniela Peguero, Alberto Tonda:
Towards multi-objective optimization of sustainable insect production chains. 352-355 - Jeroen Rook, Heike Trautmann, Jakob Bossek, Christian Grimme:
On the potential of automated algorithm configuration on multi-modal multi-objective optimization problems. 356-359 - Ayaz Ur Rehman, Anas Nadeem, Muhammad Zubair Malik:
Fair feature subset selection using multiobjective genetic algorithm. 360-363 - Dominik Weikert, Christoph Steup, Sanaz Mostaghim:
Surrogate models for IoT task allocation optimization. 364-366 - Erling Wisløff, Marius Aarsnes, Kazi Shah Nawaz Ripon, Pauline Haddow:
Extending the push and pull search framework with boundary search for constrained multi-objective optimization. 367-370 - Yuhei Yamaya, Yan Pei:
An analysis on effectiveness of estimated convergence points for enhancement of multi-objective optimization algorithms. 371-374 - Weiqin Ying, Yanqi Lan, Yu Wu, Xuanda Pan, Banban Huang, Jianyi Peng:
A constraint cone decomposition evolutionary algorithm with dual populations. 375-378 - Sizhe Yuen, Thomas H. G. Ezard, Adam J. Sobey:
The effect of epigenetic blocking on dynamic multi-objective optimisation problems. 379-382 - Haotian Zhang, Jialong Shi, Jianyong Sun, Zongben Xu:
Learning to balance exploration and exploitation in pareto local search for multi-objective combinatorial optimization. 383-386
POSTER SESSION: Evolutionary numerical optimization
- Shakhnaz Akhmedova, Vladimir Stanovov, Aleksei Vakhnin:
A hybrid self-adapting multi-swarm algorithm based on PSO and CMA-ES for continuous dynamic optimization. 387-390 - Le Van Cuong, Nguyen Ngoc Bao, Nguyen Khanh Phuong, Huynh Thi Thanh Binh:
Dynamic perturbation for population diversity management in differential evolution. 391-394 - Qiqi Duan, Guochen Zhou, Chang Shao, Yijun Yang, Yuhui Shi:
Distributed evolution strategies for large-scale optimization. 395-398 - Yong Li, Qiang Yang, Xu-Dong Gao, Zhenyu Lu, Jun Zhang:
A layered learning estimation of distribution algorithm. 399-402 - Duc Manh Nguyen:
The effect of mirrored sampling with active CMA and sample reuse in the CMAES-APOP algorithm. 403-406 - Eryk Warchulski, Jaroslaw Arabas, Rafal Biedrzycki:
Improving the differential evolution strategy by coupling it with CMA-ES. 407-410 - Guosong Yang, Peng Wang, Xinyu Yin:
A novel dynamic analysis on multi-scale quantum harmonic oscillator algorithm using double-well function. 411-414
POSTER SESSION: Genetic algorithms
- Eisa Alblooshi, Ahmed Alblooshi, Kin Poon, Anis Ouali:
A GA based approach for solving ring design telecommunication network. 415-418 - Darren M. Chitty, William B. Yates, Ed Keedwell:
An edge quality aware crossover operator for application to the capacitated vehicle routing problem. 419-422 - Shuchao Deng, Yanan Sun, Edgar Galván:
Neural architecture search using genetic algorithm for facial expression recognition. 423-426 - Léo Françoso Dal Piccol Sotto, Sebastian Mayer, Jochen Garcke:
The pole balancing problem from the viewpoint of system flexibility. 427-430 - Juan Carlos Gómez-López, Juan José Escobar, Antonio Francisco Díaz, Miguel Damas, Francisco Gil Montoya, Jesús González:
Boosting the convergence of a GA-based wrapper for feature selection problems on high-dimensional data. 431-434 - Ching-Chung Huang, Tian-Li Yu:
Trimming, ordering, and similarity check for DSMGA-II: DSMGA-II-TOS. 435-438 - Jun Suk Kim, Chang Wook Ahn:
Quantum strategy of population initialization in genetic algorithm. 439-442 - Yanchi Li, Wenyin Gong, Shuijia Li:
Evolutionary constrained multi-task optimization: benchmark problems and preliminary results. 443-446 - Hao Li, Xuesong Jiang, Xiumei Wei:
Initialization method of genetic algorithm based on improved clustering algorithm. 447-450 - Shogo Matsuno, Kaoru Shimada:
Evolutionary operation setting for outcome accumulation type evolutionary rule discovery method. 451-454 - Chi-Meng Ngai, Tian-Li Yu:
Improving DSMGA-II performance on hierarchical problems by introducing preservative back mixing. 455-458 - Clodomir J. Santana Jr., Edward C. Keedwell, Ronaldo Menezes:
Networks of evolution: modelling and deconstructing genetic algorithms using dynamic networks. 459-462 - David Von Dollen, Sheir Yarkoni, Daniel Weimer, Florian Neukart, Thomas Bäck:
Quantum-enhanced selection operators for evolutionary algorithms. 463-466 - Phoenix Neale Williams, Ke Li, Geyong Min:
Black-box adversarial attack via overlapped shapes. 467-468 - Shasha Zhou, Ke Li, Geyong Min:
Adversarial example generation via genetic algorithm: a preliminary result. 469-470
POSTER SESSION: General evolutionary computation and hybrids
- Kamil Basiukajc, Maciej Komosinski, Konrad Miazga:
Fitness diversification in the service of fitness optimization: a comparison study. 471-474 - Alexandre Bettinger, Armelle Brun, Anne Boyer:
Independent influence of exploration and exploitation for metaheuristic-based recommendations. 475-478 - Jixiang Chen, Fu Luo, Zhenkun Wang:
Dynamic multi-objective ensemble of acquisition functions in batch bayesian optimization. 479-482 - Grasiele Regina Duarte, Beatriz Souza Leite Pires de Lima:
Dynamic evaluation of decomposition methods for large-scale optimization problems using an island model. 483-486 - Parham Hadikhani, Daphne Teck Ching Lai, Wee-Hong Ong, Mohammad H. Nadimi-Shahraki:
Improved data clustering using multi-trial vector-based differential evolution with gaussian crossover. 487-490 - Ryoki Hamano, Shinichi Shirakawa:
Reduction of genetic drift in population-based incremental learning via entropy regularization. 491-494 - Clément Legrand, Diego Cattaruzza, Laetitia Jourdan, Marie-Eléonore Kessaci:
Enhancing MOEA/D with learning: application to routing problems with time windows. 495-498 - Mario Andrés Muñoz, Hamed Soleimani, Sevvandi Kandanaarachchi:
Benchmarking algorithm portfolio construction methods. 499-502 - Seung-Soo Shin, Yong-Hyuk Kim:
A surrogate model-based genetic algorithm for the optimal policy in cart-pole balancing environments. 503-505 - Patrik Valkovic, Martin Pilát:
Implementing and evaluating parallel evolutionary algorithms in modern GPU computing libraries. 506-509 - Hong Zhao, Jiarui Li, Jing Liu:
Localized distance and time-based differential evolution for multimodal optimization problems. 510-513 - Ying Zhao, Erik Hemberg, Nate Derbinsky, Gabino Mata, Una-May O'Reilly:
Using domain knowledge in coevolution and reinforcement learning to simulate a logistics enterprise. 514-517
POSTER SESSION: Genetic programming
- Mihyar Al Masalma, Malcolm I. Heywood:
Genetic programming with external memory in sequence recall tasks. 518-521 - Ryan Amaral, Alexandru Ianta, Caleidgh Bayer, Robert J. Smith, Malcolm I. Heywood:
Benchmarking genetic programming in a multi-action reinforcement learning locomotion task. 522-525 - Geoffrey F. Bomarito, Patrick E. Leser, N. C. M. Strauss, K. M. Garbrecht, Jacob D. Hochhalter:
Bayesian model selection for reducing bloat and overfitting in genetic programming for symbolic regression. 526-529 - Karina Brotto Rebuli, Mario Giacobini, Niccolò Tallone, Leonardo Vanneschi:
A preliminary study of prediction interval methods with genetic programming. 530-533 - Grant Dick, Peter A. Whigham:
Initialisation and grammar design in grammar-guided evolutionary computation. 534-537 - Li Ding, Ryan Boldi, Thomas Helmuth, Lee Spector:
Going faster and hence further with lexicase selection. 538-541 - Francisco Javier Gil Gala, Marko Durasevic, Domagoj Jakobovic:
Genetic programming for electric vehicle routing problem with soft time windows. 542-545 - Chathika Gunaratne, Robert M. Patton:
Genetic programming for understanding cognitive biases that generate polarization in social networks. 546-549 - Nathan Haut, Wolfgang Banzhaf, Bill Punch:
Active learning improves performance on symbolic regression tasks in StackGP. 550-553 - Yifan He, Claus Aranha, Tetsuya Sakurai:
Incorporating sub-programs as knowledge in program synthesis by PushGP and adaptive replacement mutation. 554-557 - Quang Nhat Huynh, Hemant Kumar Singh, Tapabrata Ray:
Discovery of implicit relationships from data using linear programming and mixed integer linear programming. 558-561 - Taran Cyriac John, Muhammad Shabbir Abbasi, Harith Al-Sahaf, Ian Welch:
Automatically evolving malice scoring models through utilisation of genetic programming: a cooperative coevolution approach. 562-565 - Roman Kalkreuth:
Phenotypic duplication and inversion in cartesian genetic programming applied to boolean function learning. 566-569 - Krzysztof Krawiec, Dominik Kossinski:
Compositional genetic programming for symbolic regression. 570-573 - William B. Langdon:
Failed disruption propagation in integer genetic programming. 574-577 - Hannah Peeler, Shuyue Stella Li, Andrew N. Sloss, Kenneth N. Reid, Yuan Yuan, Wolfgang Banzhaf:
Optimizing LLVM pass sequences with shackleton: a linear genetic programming framework. 578-581 - Martin Pilát, Gabriela Suchopárová:
Using graph neural networks as surrogate models in genetic programming. 582-585 - Benjamin Portman, Malcolm I. Heywood:
On the interaction between lexicase selection, modularity and data subsets. 586-589 - Nicolas Potvin, Hugues Bersini, Dragomir Milojevic:
Espresso to the rescue of genetic programming facing exponential complexity. 590-593 - Atif Rafiq, Enrique Naredo, Meghana Kshirsagar, Conor Ryan:
On the effect of embedding hierarchy within multi-objective optimization for evolving symbolic regression models. 594-597 - Anil Kumar Saini, Lee Spector, Thomas Helmuth:
Environments with local scopes for modules in genetic programming. 598-601 - Xinming Shi, Jiashi Gao, Leandro L. Minku, Xin Yao:
Evolving parsimonious circuits through shapley value-based genetic programming. 602-605 - Dominik Sobania, Martin Briesch, David Wittenberg, Franz Rothlauf:
Analyzing optimized constants in genetic programming on a real-world regression problem. 606-607 - Nicolas Sourbier, Justine Bonnot, Frédéric Majorczyk, Olivier Gesny, Thomas Guyet, Maxime Pelcat:
Imbalanced classification with tpg genetic programming: impact of problem imbalance and selection mechanisms. 608-611 - David Wittenberg, Franz Rothlauf:
Denoising autoencoder genetic programming for real-world symbolic regression. 612-614 - Meng Xu, Yi Mei, Fangfang Zhang, Mengjie Zhang:
Genetic programming with diverse partner selection for dynamic flexible job shop scheduling. 615-618 - Peng Zeng, Andrew Lensen, Yanan Sun:
Large scale image classification using GPU-based genetic programming. 619-622 - Jinting Zhang, Ting Hu:
Regulatory genotype-to-phenotype mappings improve evolvability in genetic programming. 623-626
POSTER SESSION: Neuroevolution
- Rui P. Cardoso, Emma Hart, David Burth Kurka, Jeremy V. Pitt:
The diversity-accuracy duality in ensembles of classifiers. 627-630 - Li Chen, Hua Xu:
MFENAS: multifactorial evolution for neural architecture search. 631-634 - Daniel Cummings, Sharath Nittur Sridhar, Anthony Sarah, Maciej Szankin:
Accelerating neural architecture exploration across modalities using genetic algorithms. 635-638 - Federico Da Rold, Olaf Witkovski, Nathanaël Aubert-Kato:
Synaptic pruning with MAP-elites. 639-642 - Cosijopii Garcia-Garcia, Hugo Jair Escalante, Alicia Morales-Reyes:
CGP-NAS: real-based solutions encoding for multi-objective evolutionary neural architecture search. 643-646 - Daniel García-Núñez, Katya Rodríguez-Vázquez, Carlos Hernández:
Neuroevolution based multi-objective algorithm for gene selection and microarray classification. 647-650 - Maximilien Le Clei, Pierre Bellec:
Neuroevolution of recurrent architectures on control tasks. 651-654 - Vasco Lopes, Miguel Santos, Bruno Degardin, Luís A. Alexandre:
Efficient guided evolution for neural architecture search. 655-658 - Zimeng Lyu, Travis Desell:
ONE-NAS: an online neuroevolution based neural architecture search for time series forecasting. 659-662 - Thiago Zafalon Miranda, Diorge Brognara Sardinha, Márcio Porto Basgalupp, Ricardo Cerri:
A new grammatical evolution method for generating deep convolutional neural networks with novel topologies. 663-666 - Evgenia Papavasileiou, Jan Cornelis, Bart Jansen:
Towards optimizing neural networks' connectivity and architecture simultaneously with feature selection. 667-670 - Nilotpal Sinha, Kuan-Wen Chen:
Novelty driven evolutionary neural architecture search. 671-674 - Fergal Stapleton, Edgar Galván, Ganesh Sistu, Senthil Kumar Yogamani:
Neuroevolutionary multi-objective approaches to trajectory prediction in autonomous vehicles. 675-678 - Kai-Hsun Tsai, Chun-Wei Tsai, Ming-Chao Chiang:
An effective metaheuristic-based pruning method for convolutional neural network. 679-682
POSTER SESSION: Real world applications
- Mohammad Majid al-Rifaie, Marc Cavazza:
Multi-objective evolutionary beer optimisation. 683-686 - Kai Arulkumaran, Thu Nguyen-Phuoc:
Minimal criterion artist collective. 687-690 - Claude Carlet, Domagoj Jakobovic, Stjepan Picek:
On generalizing the power function exponent constructions with genetic programming. 691-694 - Tinkle Chugh, Endi Ymeraj:
Wind farm layout optimisation using set based multi-objective bayesian optimisation. 695-698 - João Marcos de Freitas, Heder Soares Bernardino, Luciana Brugiolo Gonçalves, Stênio Sã Rosário Furtado Soares:
Human activity recognition using grammar-based genetic programming. 699-702 - Bryan Dedeurwaerder, Sushil J. Louis, Siming Liu, Nicholas Harris:
Routing for bridge inspecting robots using a metaheuristic genetic algorithm. 703-706 - Seth G. Fitzgerald, Gary W. Delaney, David Howard, Frédéric Maire:
Evolving polydisperse soft robotic jamming grippers. 707-710 - Roberto Gallotta, Kai Arulkumaran, Lisa B. Soros:
Evolving spaceships with a hybrid L-system constrained optimisation evolutionary algorithm. 711-714 - Yongfeng Gu, Hao Ding, Kecai Gu, Runsheng Gan, Xiaoguang Huang, Yanming Fang, Zhigang Hua, Hua Wu, Jifeng Xuan, Jun Zhou:
Heuristic strategies for solving the combinatorial optimization problem in real-world credit risk assessment. 715-718 - Krishn Kumar Gupt, Meghana Kshirsagar, Lukas Rosenbauer, Joseph P. Sullivan, Douglas Mota Dias, Conor Ryan:
PreDive: preserving diversity in test cases for evolving digital circuits using grammatical evolution. 719-722 - Alexander Lalejini, Emily L. Dolson, Anya E. Vostinar, Luis Zaman:
Selection schemes from evolutionary computing show promise for directed evolution of microbes. 723-726 - Lauren R. McCarey, Thomas S. McTavish:
Optimizing sample diversity with fairness constraints on imbalanced, sparse, hiring data. 727-730 - Nisrine Mouhrim, Alberto Tonda, Itzel Rodríguez-Guerra, Aletta D. Kraneveld, Alejandro Lopez Rincon:
An evolutionary approach to the discretization of gene expression profiles to predict the severity of COVID-19. 731-734 - Akinola Ogunsemi, John A. W. McCall, Mathias Kern, Benjamin Lacroix, David Corsar, Gilbert Owusu:
Facility location problem and permutation flow shop scheduling problem: a linked optimisation problem. 735-738 - Anna Ouskova Leonteva, Michel Risser, Radia Hamane, Anne Jeannin-Girardon, Pierre Parrend, Pierre Collet:
A hybrid optimization tool for active magnetic regenerator. 739-742 - Sanjai Pathak, Ashish Mani, Mayank Sharma, Amlan Chatterjee:
Rethinking of controller placement problem from static optimization to multi-objective dynamic optimization. 743-746 - Federico Peralta, Michael Pearce, Matthias Poloczek, Daniel Gutiérrez-Reina, Sergio Toral, Jürgen Branke:
Multi-objective path planning for environmental monitoring using an autonomous surface vehicle. 747-750 - David Peña, Bernabé Dorronsoro, Andrei Tchernykh, Patricia Ruiz:
Public transport timetable and charge optimization using multiple electric buses types. 751-754 - Christina Plump, Bernhard J. Berger, Rolf Drechsler:
Adapting mutation and recombination operators to range-aware relations in real-world application data. 755-758 - Cagatay Sariman, Ahmed Hallawa, Erdi Sayar, Arne Peine, Lukas Martin, Anke Schmeink:
Exploration of unknown environments via evolution of behavioral and morphological properties of miniaturized sensory agents. 759-762 - Zhendong Sha, Yuanzhu Peter Chen, Ting Hu:
Genetic heterogeneity analysis using genetic algorithm and network science. 763-766 - Felix Winter, Nysret Musliu:
A hyper-heuristic approach for artificial teeth scheduling. 767-769 - Yue Xie, Aneta Neumann, Frank Neumann:
An optimization strategy for the complex large-scale stockpile blending problem. 770-773 - Shi-Cheng Zha, Wei-Neng Chen, Wen-Jin Qiu, Xiao-Min Hu:
A surrogate-assisted multi-objective evolutionary algorithm for shelter locating and evacuation planning. 774-777
POSTER SESSION: Search-based software engineering
- Asma Belhadi, Man Zhang, Andrea Arcuri:
Evolutionary-based automated testing for GraphQL APIs. 778-781 - Sofien Boutaib, Maha Elarbi, Slim Bechikh, Fabio Palomba, Lamjed Ben Said:
A bi-level evolutionary approach for the multi-label detection of smelly classes. 782-785 - Tsutomu Kumazawa, Munehiro Takimoto, Yasushi Kambayashi:
A safety checking algorithm with multi-swarm particle swarm optimization. 786-789 - Sherlock A. Licorish, Markus Wagner:
Combining GIN and PMD for code improvements. 790-793 - Cláudia Tupan Rosa, Willian Marques Freire, Aline Maria Malachini Miotto Amaral, Thelma Elita Colanzi:
Towards an interactive ranking operator for NSGA-II. 794-797
POSTER SESSION: Theory
- Paras Nigam, Sumit Mishra:
Counterexample to the best-case running time of efficient non-dominated sorting algorithm. 798-800
TUTORIAL SESSION: Introductory tutorials
- Anne Auger, Nikolaus Hansen:
A (biased) introduction to benchmarking. 801-823 - Jakob Bossek, Aneta Neumann, Frank Neumann:
Evolutionary diversity optimization for combinatorial optimization: tutorial at GECCO'22, Boston, USA. 824-842 - Ivo Couckuyt, Sebastian Rojas-Gonzalez, Jürgen Branke:
Bayesian optimization: tutorial. 843-863 - Antoine Cully, Jean-Baptiste Mouret, Stéphane Doncieux:
Quality-diversity optimisation. 864-889 - Benjamin Doerr:
A gentle introduction to theory (for non-theoreticians). 890-921 - Amir H. Gandomi:
GECCO 2022#: embedding knowledge into optimization process. 922-936 - Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Difficulties in fair performance comparison of multiobjective evolutionary algorithms. 937-957 - Roman Kalkreuth, Léo Françoso Dal Piccol Sotto, Zdenek Vasícek:
Graph-based genetic programming. 958-982 - Ahmed Kheiri, Edward C. Keedwell:
Selection hyper-heuristics. 983-996 - Thomas Stützle, Manuel López-Ibáñez, Leslie Pérez Cáceres:
Automated algorithm configuration and design. 997-1019 - Risto Miikkulainen:
Evolution of neural networks. 1020-1037 - Nelishia Pillay:
Transfer learning in evolutionary spaces. 1038-1045 - Franz Rothlauf:
Representations for evolutionary algorithms. 1046-1066 - Ofer M. Shir:
Introductory mathematical programming for EC. 1067-1080 - Abubakar Siddique, Will N. Browne:
Learning classifier systems: cognitive inspired machine learning for eXplainable AI. 1081-1110 - Daniel R. Tauritz, John R. Woodward:
Generative hyper-heuristics. 1111-1140 - Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms: GECCO 2022 tutorial. 1141-1170 - Darrell Whitley:
Graybox optimization and next generation genetic algorithms. 1171-1199 - Bing Xue, Mengjie Zhang:
Evolutionary computation for feature selection and feature construction. 1200-1229 - Danial Yazdani, Xin Yao:
Evolutionary continuous dynamic optimization. 1230-1242
TUTORIAL SESSION: Advanced tutorials
- Youhei Akimoto, Nikolaus Hansen:
CMA-ES and advanced adaptation mechanisms. 1243-1268 - Dimo Brockhoff, Tea Tusar:
GECCO 2022 tutorial on benchmarking multiobjective optimizers 2.0. 1269-1309 - Carlos A. Coello Coello:
Constraint-handling techniques used with evolutionary algorithms. 1310-1333 - Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye:
Benchmarking and analyzing iterative optimization heuristics with IOH profiler. 1334-1341 - Tome Eftimov, Peter Korosec:
Statistical analyses for multi-objective stochastic optimization algorithms: GECCO 2022 tutorial. 1342-1356 - Sæmundur Óskar Haraldsson, Alexander E. I. Brownlee, John R. Woodward, Bradley Alexander, Emily Winter:
Genetic improvement: taking real-world source code and improving it using computational search methods. 1357-1384 - Thomas Helmuth, William G. La Cava:
Lexicase selection. 1385-1397 - Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of population-based evolutionary algorithms. 1398-1426 - Aneta Neumann, Frank Neumann, Chao Qian:
Evolutionary submodular optimisation: tutorial. 1427-1449 - Ofer M. Shir, Thomas Bäck:
Sequential experimentation by evolutionary algorithms. 1450-1468 - Dirk Sudholt, Giovanni Squillero:
Theory and practice of population diversity in evolutionary computation. 1469-1486 - Jamal Toutouh, Una-May O'Reilly:
Coevolutionary computation for adversarial deep learning. 1487-1505
TUTORIAL SESSION: Specialized tutorials
- Marko Durasevic, Domagoj Jakobovic, Yi Mei, Su Nguyen, Mengjie Zhang:
Introduction to automated design of scheduling heuristics with genetic programming. 1506-1526 - Carlos Gavidia-Calderon, Héctor D. Menéndez:
Ant colony optimization for software engineers. 1527-1541 - Dario Izzo, Manuel López-Ibáñez:
Optimization challenges at the european space agency. 1542-1553 - Ke Li, Qingfu Zhang:
Decomposition multi-objective optimisation: current developments and future opportunities. 1554-1571 - Stjepan Picek, Domagoj Jakobovic:
Evolutionary computation and machine learning in security. 1572-1601 - Mengjie Zhang, Stefano Cagnoni:
Evolutionary computation and evolutionary deep learning for image analysis, signal processing and pattern recognition. 1602-1630
WORKSHOP SESSION: Workshop analysing algorithmic behaviour of optimisation heuristics
- Nielis Brouwer, Danny Dijkzeul, Levi Koppenhol, Iris Pijning, Daan van den Berg:
Survivor selection in a crossoverless evolutionary algorithm. 1631-1639 - Levi Koppenhol, Nielis Brouwer, Danny Dijkzeul, Iris Pijning, Joeri Sleegers, Daan van den Berg:
Exactly characterizable parameter settings in a crossoverless evolutionary algorithm. 1640-1649 - Pavel Krömer, Vojtech Uher:
The effect of decoding fairness on particle swarm optimization for the p-median problem. 1650-1657 - Mario Andrés Muñoz:
Examining algorithm behavior using recurrence quantification and landscape analyses. 1658-1665 - Gasper Petelin, Margarita Antoniou, Gregor Papa:
Dynamic computational resource allocation for CFD simulations based on pareto front optimization. 1666-1673 - Diederick Vermetten, Fabio Caraffini, Bas van Stein, Anna V. Kononova:
Using structural bias to analyse the behaviour of modular CMA-ES. 1674-1682
WORKSHOP SESSION: Workshop black box optimization benchmarking
- Charles Audet, Sébastien Le Digabel, Ludovic Salomon, Christophe Tribes:
Constrained blackbox optimization with the NOMAD solver on the COCO constrained test suite. 1683-1690 - Paul Dufossé, Asma Atamna:
Benchmarking several strategies to update the penalty parameters in AL-CMA-ES on the bbob-constrained testbed. 1691-1699 - Mohamed Gharafi:
Benchmarking of two implementations of CMA-ES with diagonal decoding on the bbob test suite. 1700-1707 - Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa:
Benchmarking CMA-ES with margin on the bbob-mixint testbed. 1708-1716 - Michael Hellwig, Hans-Georg Beyer:
Benchmarking ϵMAg-ES and BP-ϵMAg-ES on the bbob-constrained testbed. 1717-1724 - Zachary Hoffman, Steve Huntsman:
Benchmarking an algorithm for expensive high-dimensional objectives on the bbob and bbob-largescale testbeds. 1725-1733 - Duc Manh Nguyen:
Benchmarking some variants of the CMAES-APOP using keeping search points and mirrored sampling combined with active CMA on the BBOB noiseless testbed. 1734-1742 - Ryoji Tanabe:
Benchmarking the hooke-jeeves method, MTS-LS1, and BSrr on the large-scale BBOB function set. 1743-1751
WORKSHOP SESSION: Workshop evolutionary computation and explainable AI
- Hayden Andersen, Andrew Lensen, Will N. Browne:
Improving the search of learning classifier systems through interpretable feature clustering. 1752-1756 - Jaume Bacardit, Alexander E. I. Brownlee, Stefano Cagnoni, Giovanni Iacca, John A. W:
McCall, David Walker: The intersection of evolutionary computation and explainable AI. 1757-1762 - Leonardo Lucio Custode, Giovanni Iacca:
Interpretable AI for policy-making in pandemics. 1763-1769 - Martina Saletta, Claudio Ferretti:
Towards the evolutionary assessment of neural transformers trained on source code. 1770-1778 - Hormoz Shahrzad, Babak Hodjat, Risto Miikkulainen:
Evolving explainable rule sets. 1779-1784 - Manjinder Singh, Alexander E. I. Brownlee, David E. Cairns:
Towards explainable metaheuristic: mining surrogate fitness models for importance of variables. 1785-1793 - Mathew J. Walter, David J. Walker, Matthew J. Craven:
An explainable visualisation of the evolutionary search process. 1794-1802
WORKSHOP SESSION: Workshop evolutionary computation and decision making
- Pouya Aghaei Pour, Sunith Bandaru, Bekir Afsar, Kaisa Miettinen:
Desirable properties of performance indicators for assessing interactive evolutionary multiobjective optimization methods. 1803-1811 - José Almeida, Fernando Lezama, João P. Soares, Zita A. Vale, Bruno Canizes:
Preliminary results of advanced heuristic optimization in the risk-based energy scheduling competition. 1812-1816 - Tinkle Chugh:
R-MBO: a multi-surrogate approach for preference incorporation in multi-objective bayesian optimisation. 1817-1825 - Giomara Lárraga, Kaisa Miettinen:
Interactive MOEA/D with multiple types of preference information. 1826-1834 - Atanu Mazumdar, Stefan Otayagich, Kaisa Miettinen:
Interactive evolutionary multiobjective optimization with modular physical user interface. 1835-1843
WORKSHOP SESSION: Workshop evolutionary computation for the automated design of algorithms
- Fraser Garrow, Michael A. Lones, Robert J. Stewart:
Why functional program synthesis matters (in the realm of genetic programming). 1844-1853 - Michele Tessari, Giovanni Iacca:
Reinforcement learning based adaptive metaheuristics. 1854-1861
WORKSHOP SESSION: Workshop enhancing generative machine learning with evolutionary computation
- Francisco Baeta, João Correia, Tiago Martins, Penousal Machado:
Exploring expression-based generative adversarial networks. 1862-1869 - Peter J. Bentley, Soo Ling Lim, Adam Gaier, Linh Tran:
COIL: Constrained optimization in learned latent space: learning representations for valid solutions. 1870-1877 - Benjamín Machín, Sergio Nesmachnow, Jamal Toutouh:
Multi-target evolutionary latent space search of a generative adversarial network for human face generation. 1878-1886 - Gabriel Wang, Anish Thite, Rodd Talebi, Anthony D'Achille, Alex Mussa, Jason Zutty:
Evolving SimGANs to improve abnormal electrocardiogram classification. 1887-1894
WORKSHOP SESSION: Workshop on evolutionary optimization in uncertainty quantification models
- Carlos Andreu-Vilarroig, Josu Ceberio, Juan Carlos Cortés, Francisco Fernández de Vega, José Ignacio Hidalgo, Rafael-Jacinto Villanueva:
Evolutionary approach to model calibration with uncertainty: an application to breast cancer growth model. 1895-1901 - Vicente-José Bevia, Carlos Andreu-Vilarroig, Juan Carlos Cortés, Rafael-Jacinto Villanueva:
Probability density function computation in evolutionary model calibration with uncertainty. 1902-1908 - Josu Ceberio, Juan Carlos Cortés, Francisco Fernández de Vega, Oscar Garnica, José Ignacio Hidalgo, J. Manuel Velasco, Rafael-Jacinto Villanueva:
Approaching epistemic and aleatoric uncertainty with evolutionary optimization: examples and challenges. 1909-1915
WORKSHOP SESSION: Workshop 11th international workshop on genetic improvement
- Mahmoud Al Najar, Rafael Almar, Erwin W. J. Bergsma, Jean-Marc Delvit, Dennis G. Wilson:
Genetic improvement of shoreline evolution forecasting models. 1916-1923 - Damien Anderson, Paul Harvey, Yusaku Kaneta, Petros Papadopoulos, Philip Rodgers, Marc Roper:
Towards evolution-based autonomy in large-scale systems. 1924-1925 - Bobby R. Bruce:
Automatically exploring computer system design spaces. 1926-1927 - Chitchanok Chuengsatiansup, Markus Wagner, Yuval Yarom:
Opportunities for genetic improvement of cryptographic code. 1928-1929 - Oliver Krauss:
Amaru: a framework for combining genetic improvement with pattern mining. 1930-1937 - Shuyue Stella Li, Hannah Peeler, Andrew N. Sloss, Kenneth N. Reid, Wolfgang Banzhaf:
Genetic improvement in the shackleton framework for optimizing LLVM pass sequences. 1938-1939 - Sherlock A. Licorish, Markus Wagner:
Dissecting copy/delete/replace/swap mutations: insights from a GIN case study. 1940-1945 - Aidan Murphy, Thomas Laurent, Anthony Ventresque:
The case for grammatical evolution in test generation. 1946-1947 - Yueke Zhang, Yu Huang:
Leveraging fuzzy system to reduce uncertainty of decision making in software engineering automation. 1948-1949 - James Zhong, Max Hort, Federica Sarro:
Py2Cy: a genetic improvement tool to speed up python. 1950-1955 - Shengjie Zuo, Aymeric Blot, Justyna Petke:
Evaluation of genetic improvement tools for improvement of non-functional properties of software. 1956-1965
WORKSHOP SESSION: Workshop evolutionary reinforcement learning
- Enrico Marchesini, Christopher Amato:
Safety-informed mutations for evolutionary deep reinforcement learning. 1966-1970 - Thomas Miconi:
Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learning. 1971-1978 - Yasen Wang, Youhei Akimoto:
On the effect of the sampling ratio of past trajectories in the combination of evolutionary algorithm and deep reinforcement learning. 1979-1983
WORKSHOP SESSION: Workshop evolutionary computation software systems
- Andreas Beham, Sebastian Leitner, Johannes Karder, Bernhard Werth, Stefan Wagner:
DynStack: a benchmarking framework for dynamic optimization problems in warehouse operations. 1984-1991 - Arnaud Berny:
Recent developments in HNCO. 1992-2000 - Hatem Khalloof, Sergen Ciftci, Shadi Shahoud, Clemens Düpmeier, Kevin Förderer, Veit Hagenmeyer:
Facilitating the hybridization of parallel evolutionary algorithms in cluster computing environments. 2001-2008 - Eric Medvet, Giorgia Nadizar, Luca Manzoni:
JGEA: a modular java framework for experimenting with evolutionary computation. 2009-2018
WORKSHOP SESSION: Workshop industrial applications of metaheuristics
- Vinícius Gandra, Carlo S. Sartori, Hatice Çalik, Pieter Smet:
Multi-depot periodic vehicle routing with variable visit patterns. 2019-2026 - Ofer M. Shir, Boris Yazmir, Assaf Israeli, Dan Gamrasni:
Algorithmically-guided postharvest protocols by experimental combinatorial optimization. 2027-2035 - André Thomaser, Anna V. Kononova, Marc-Eric Vogt, Thomas Bäck:
One-shot optimization for vehicle dynamics control systems: towards benchmarking and exploratory landscape analysis. 2036-2045
WORKSHOP SESSION: Workshop large-scale evolutionary optimization and learning
- Darren M. Chitty:
Accelerating genetic algorithm evolution via ant-based mutation and crossover for application to large-scale TSPs. 2046-2053 - Li Ding, Ryan Boldi, Thomas Helmuth, Lee Spector:
Lexicase selection at scale. 2054-2062 - Luciana Nascimento Santana Prachedes, José Eduardo Henriques da Silva, Heder Soares Bernardino, Itamar Leite de Oliveira:
High-performance cartesian genetic programming on GPU for the inference of gene regulatory networks using scRNA-seq time-series data. 2063-2070
WORKSHOP SESSION: Workshop international workshop on learning classifier systems
- Mathis Brede, Tim Hansmeier, Marco Platzner:
XCS on embedded systems: an analysis of execution profiles and accelerated classifier deletion. 2071-2079 - Markus Görlich-Bucher, Jörg Hähner:
XCSF under limited supervision. 2080-2085 - Michael Heider, David Pätzel, Alexander R. M. Wagner:
An overview of LCS research from 2021 to 2022. 2086-2094 - Olgierd Unold, Norbert Kozlowski, Lsukasz Smierzchala:
Preliminary tests of an anticipatory classifier system with experience replay. 2095-2103
WORKSHOP SESSION: Workshop neuroevolution at work
- Arkadiy Dushatskiy, Tanja Alderliesten, Peter A. N. Bosman:
Heed the noise in performance evaluations in neural architecture search. 2104-2112 - Raz Lapid, Moshe Sipper:
Evolution of activation functions for deep learning-based image classification. 2113-2121 - Eric Medvet, Giorgia Nadizar, Federico Pigozzi:
On the impact of body material properties on neuroevolution for embodied agents: the case of voxel-based soft robots. 2122-2130
WORKSHOP SESSION: Workshop on quality diversity algorithm benchmarks
- Paul Kent, Jürgen Branke, Adam Gaier, Jean-Baptiste Mouret:
A discretization-free metric for assessing quality diversity algorithms. 2131-2135 - Lennart Schneider, Florian Pfisterer, Janek Thomas, Bernd Bischl:
A collection of quality diversity optimization problems derived from hyperparameter optimization of machine learning models. 2136-2142
WORKSHOP SESSION: Workshop surrogate-assisted evolutionary optimisation
- Tinkle Chugh:
Mono-surrogate vs multi-surrogate in multi-objective bayesian optimisation. 2143-2151
WORKSHOP SESSION: Workshop genetic and evolutionary computation in defense, security, and risk management
- Miguel León Ortiz, Tijana Markovic, Sasikumar Punnekkat:
Feature encoding with autoencoder and differential evolution for network intrusion detection using machine learning. 2152-2159 - Samuel Migirditch, John Asplund, William Curran:
Chaos engineering: stress-testing algorithms to facilitate resilient strategic military planning. 2160-2167 - Stephen Moskal, Erik Hemberg, Una-May O'Reilly:
CyberEvo: evolutionary search of knowledge-based behaviors in a cyber attack campaign. 2168-2176
WORKSHOP SESSION: Workshop quantum optimization
- Marco Baioletti:
Probabilistic reasoning as quadratic unconstrained binary optimization. 2177-2181 - Yao-Hsin Chou, Shu-Yu Kuo, Yu-Chi Jiang, Ching-Hsuan Wu, Jyun-Yi Shen, Cheng-Yen Hua, Pei-Shin Huang, Yun-Ting Lai, Yong Feng Tong, Ming-He Chang:
A novel quantum-inspired evolutionary computation-based quantum circuit synthesis for various universal gate libraries. 2182-2189 - Li Ding, Lee Spector:
Evolutionary quantum architecture search for parametrized quantum circuits. 2190-2195 - Thomas Gabor, Maximilian Zorn, Claudia Linnhoff-Popien:
The applicability of reinforcement learning for the automatic generation of state preparation circuits. 2196-2204 - Thomas Gabor, Michael Lachner, Nico Kraus, Christoph Roch, Jonas Stein, Daniel Ratke, Claudia Linnhoff-Popien:
Modifying the quantum-assisted genetic algorithm. 2205-2213 - Mikel Garcia de Andoin, Eneko Osaba, Izaskun Oregi, Esther Villar-Rodriguez, Mikel Sanz:
Hybrid quantum-classical heuristic for the bin packing problem. 2214-2222 - Siong Thye Goh, Jianyuan Bo, Sabrish Gopalakrishnan, Hoong Chuin Lau:
Techniques to enhance a QUBO solver for permutation-based combinatorial optimization. 2223-2231 - Alberto Moraglio, Serban Georgescu, Przemyslaw Sadowski:
AutoQubo: data-driven automatic QUBO generation. 2232-2239 - Jonas Nüßlein, Thomas Gabor, Claudia Linnhoff-Popien, Sebastian Feld:
Algorithmic QUBO formulations for k-SAT and hamiltonian cycles. 2240-2246 - Vicente P. Soloviev, Pedro Larrañaga, Concha Bielza:
Quantum parametric circuit optimization with estimation of distribution algorithms. 2247-2250 - Whei Yeap Suen, Matthieu Parizy, Hoong Chuin Lau:
Enhancing a QUBO solver via data driven multi-start and its application to vehicle routing problem. 2251-2257 - Tim Whitaker:
Quantum neuron selection: finding high performing subnetworks with quantum algorithms. 2258-2264
WORKSHOP SESSION: Workshop on symbolic regression
- Grant Dick:
Genetic programming, standardisation, and stochastic gradient descent revisited: initial findings on SRBench. 2265-2273 - Guilherme Seidyo Imai Aldeia, Fabrício Olivetti de França:
Interaction-transformation evolutionary algorithm with coefficients optimization. 2274-2281 - David L. Randall, Tyler S. Townsend, Jacob D. Hochhalter, Geoffrey F. Bomarito:
Bingo: a customizable framework for symbolic regression with genetic programming. 2282-2288 - Marco Virgolin, Peter A. N. Bosman:
Coefficient mutation in the gene-pool optimal mixing evolutionary algorithm for symbolic regression. 2289-2297 - Matthias Werner, Andrej Junginger, Philipp Hennig, Georg Martius:
Uncertainty in equation learning. 2298-2305
WORKSHOP SESSION: Student workshop
- Estelle Chigot, Dennis G. Wilson:
Coevolution of neural networks for agents and environments. 2306-2309 - Robert Gold, Andrew Haydn Grant, Erik Hemberg, Chathika Gunaratne, Una-May O'Reilly:
GUI-based, efficient genetic programming for Unity3D. 2310-2313 - Mounir Hafsa, Pamela Wattebled, Julie Jacques, Laetitia Jourdan:
Multi-objective recommender system for corporate MOOC. 2314-2317 - Subodh Kalia, Chilukuri K. Mohan, Ramakrishna R. Nemani:
Evolutionary training of deep neural networks on heterogeneous computing environments. 2318-2321 - Shakiba Shahbandegan, Jose Guadalupe Hernandez, Alexander Lalejini, Emily L. Dolson:
Untangling phylogenetic diversity's role in evolutionary computation using a suite of diagnostic fitness landscapes. 2322-2325 - Aleksandr Smirnov, Vladimir Mironovich:
Towards landscape-aware parameter tuning for the (1 + (λ, λ)) genetic algorithm for permutations. 2326-2329 - Kok Cheng Tan, Daniel Zantedeschi, Amruth N. Kumar, Alessio Gaspar:
Genetic algorithm cleaning in sequential data mining: analyzing solutions to parsons' puzzles. 2330-2333 - Dmytro Vitel, Alessio Gaspar:
Analysis of neutral rewrite operator effects on arithmetic domain. 2334-2337
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