Table of Contents

• Applying ring cellular encode-decode UMDA to risk-based energy schedulingAnsel Y. Rodríguez González, Ramón Aranda, Miguel Ángel Álvarez Carmona, Yoan Martínez López, Julio Madera Quintana. 1-2 [doi]
• AbstractSwarm multi-agent logistics competition entry: QPlusPatrick A. Winkel. 3-4 [doi]
• NL-SOMA-CLP for real parameter single objective bound constrained optimizationHao Ding, Yongfeng Gu, Hua Wu, Jun Zhou 0011. 5-6 [doi]
• Opposite learning and multi-migrating strategy-based self-organizing migrating algorithm with the convergence monitoring mechanismYongfeng Gu, Hao Ding, Hua Wu, Jun Zhou 0011. 7-8 [doi]
• Zeroth-order covariance matrix adaptation evolution strategy for single objective bound constrained numerical optimization competitionYue Ning 0005, Daohong Jian, Hua Wu, Jun Zhou. 9-10 [doi]
• Implementing the cumulative difference plot in the IOHanalyzerEtor Arza, Josu Ceberio, Ekhiñe Irurozki, Aritz Pérez. 11-12 [doi]
• Precise runtime analysis for plateau functions: (hot-off-the-press track at GECCO 2022)Denis Antipov, Benjamin Doerr. 13-14 [doi]
• Evolutionary generation of metamorphic relations for cyber-physical systemsJon Ayerdi, Valerio Terragni, Aitor Arrieta, Paolo Tonella, Goiuria Sagardui, Maite Arratibel. 15-16 [doi]
• Efficient configuration of optimization algorithmsMarcelo de Souza, Marcus Ritt, Manuel López-Ibáñez 0001. 17-18 [doi]
• Highlights of semantics in multi-objective genetic programmingEdgar Galván, Leonardo Trujillo, Fergal Stapleton. 19-20 [doi]
• Measuring the ability of lexicase selection to find obscure pathways to optimalityJose Guadalupe Hernandez, Alexander Lalejini, Charles Ofria. 21-22 [doi]
• Phylogenetic diversity predicts future success in evolutionary computationJose Guadalupe Hernandez, Alexander Lalejini, Emily L. Dolson. 23-24 [doi]
• Tag-based module regulation for genetic programmingAlexander Lalejini, Matthew Andres Moreno, Charles Ofria. 25-26 [doi]
• Genetic programming convergenceWilliam B. Langdon. 27-28 [doi]
• Long-term evolution experiment with genetic programming [hot of the press]William B. Langdon, Wolfgang Banzhaf. 29-30 [doi]
• A comparison of rule compaction algorithms for michigan style learning classifier systemsYi Liu, Will N. Browne, Bing Xue 0001. 31-32 [doi]
• Targeting requirements violations of autonomous driving systems by dynamic evolutionary search (HOP at GECCO'22)Yixing Luo, Xiao-Yi Zhang, Paolo Arcaini, Zhi Jin, Haiyan Zhao, Fuyuki Ishikawa, Rongxin Wu, Tao Xie 0001. 33-34 [doi]
• Empirical linkage learning for non-binary discrete search spaces in the optimization of a large-scale real-world problemMichal Witold Przewozniczek, Marcin M. Komarnicki. 35-36 [doi]
• Archivers for single- and multi-objective evolutionary optimization algorithmsCarlos Hernández, Oliver Schütze. 37-38 [doi]
• Program synthesis with evolutionary algorithms: Status quo: hot off the press track (GECCO 2022)Dominik Sobania, Dirk Schweim, Franz Rothlauf. 39-40 [doi]
• Modular grammatical evolution for the generation of artificial neural networks: (hot-off-the-press track at GECCO 2022)Khabat Soltanian, Ali Ebnenasir, Mohsen Afsharchi. 41-42 [doi]
• A verified application of genetic programming: QoS time series modeling and forecasting for web servicesYang Syu, Chien-Min Wang, Yong-Yi Fanjiang. 43-44 [doi]
• Choosing the right algorithm with hints from complexity theory: (hot-off-the-press track at GECCO 2022)Shouda Wang, Weijie Zheng 0001, Benjamin Doerr. 45-46 [doi]
• Generating failing test suites for quantum programs with search (hot off the press track at GECCO 2022)Xinyi Wang, Paolo Arcaini, Tao Yue 0002, Shaukat Ali 0001. 47-48 [doi]
• IOHanalyzer: Detailed performance analyses for iterative optimization heuristics: hot-off-the-press track @ GECCO 2022Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas Bäck. 49-50 [doi]
• Automated configuration of genetic algorithms by tuning for anytime performance: hot-off-the-press track at GECCCO 2022Furong Ye, Carola Doerr, Hao Wang, Thomas Bäck. 51-52 [doi]
• A first mathematical runtime analysis of the non-dominated sorting genetic algorithm II (NSGA-II): (hot-off-the-press track at GECCO 2022)Weijie Zheng 0001, Yufei Liu, Benjamin Doerr. 53-54 [doi]
• Evolving a cloud-robust water index with genetic programmingJoão E. Batista, Sara Silva. 55-56 [doi]
• CNN structure optimization using differential evolution with individual dependent mechanismNaoya Ikushima, Keiko Ono, Erina Makihara, Sohei Yamakawa, Ryota Shinhama. 57-58 [doi]
• A genetic algorithm for classifying metagenomic dataJolanta Kawulok, Michal Kawulok. 59-60 [doi]
• Evaluation of inverse selection operators on maximum flow test generation problemEgor Kurbatov, Vladimir Mironovich. 61-62 [doi]
• Biology inspired growth in meta-learningCullen A. LaKemper, Cehong Wang, Jason A. Yoder. 63-64 [doi]
• Hereditary stratigraphy: genome annotations to enable phylogenetic inference over distributed populationsMatthew Andres Moreno, Emily L. Dolson, Charles Ofria. 65-66 [doi]
• Evolutionary algorithms meet classical and deep machine learning for skin detection in color imagesJakub Nalepa, Stanislaw Czembor, Wojciech Dudzik, Michal Kawulok. 67-68 [doi]
• A population based-approach to address real-life transport on-demand problemsSonia Nasri, Hend Bouziri, Wassila Aggoune-Mtalaa. 69-70 [doi]
• PIACERE project: description and prototype for optimizing infrastructure as code deployment configurationsEneko Osaba, Josu Díaz-de-Arcaya, Leire Orue-Echevarria, Juncal Alonso, Jesus L. Lobo, Gorka Benguria, Iñaki Etxaniz. 71-72 [doi]
• Natural gradient evolution strategies for adaptive samplingNixon K. Ronoh, Edna Milgo, Ambrose K. KIprop, Bernard Manderick, Ann Nowé. 73-74 [doi]
• Textonmap optimization for spine segmentation using adaptive differential evolutionSohei Yamakawa, Keiko Ono, Erina Makihara, Daisuke Tawara, Shoma Yakushijin, Naoya Ikushima. 75-76 [doi]
• Ant colony optimization with shortest distance biased dispatch for visiting constrained multiple traveling salesmen problemCong Bao, Qiang Yang, Xu-Dong Gao, Zhen Yu Lu, Jun Zhang 0003. 77-80 [doi]
• Particle swarm optimization with average-fitness based selectionStephen Chen, Shanshan Lao, Irene Moser. 81-84 [doi]
• Ant colony optimization for feature selection via a filter-randomized search heuristicAlberto Ortega, Juan José Escobar, Miguel Damas, Andrés Ortiz, Jesús González 0001. 85-88 [doi]
• Cooperative attack-defense evolution of large-scale agents: a multi-population high-dimensional mean-field game approachGuofang Wang, Xiao Zhang 0004, Wang Yao, Lu Ren. 89-92 [doi]
• Dropout topology-assisted bidirectional learning particle swarm optimization for neural architecture searchYe-Qun Wang, Chun-Hua Chen, Jun Zhang, Zhi-hui Zhan. 93-96 [doi]
• A chaotic parallel antlion optimization algorithm for feature selectionXun Zhou, Hongwei Chen, Dewei Shi. 97-99 [doi]
• AutoMoDe-pomodoro: an evolutionary class of modular designsNicolas Cambier, Eliseo Ferrante. 100-103 [doi]
• Selecting continuous life-like cellular automata for halting unpredictability: evolving for abiogenesisQ. Tyrell Davis, Josh Bongard. 104-107 [doi]
• Empowered neural cellular automataCaitlin Grasso, Josh Bongard. 108-111 [doi]
• CoBEA: framework for evolving hardware by direct manipulation of FPGA bitstreamsJörn Hoffmann 0001, Clemens Fritzsch, Martin Bogdan. 112-115 [doi]
• Minimize surprise MAP-elites: a task-independent MAP-elites variant for swarmsTanja Katharina Kaiser, Heiko Hamann. 116-119 [doi]
• Evolving robot bodies with a sense of directionEmiel M. W. Kempen, Ágoston E. Eiben. 120-123 [doi]
• Diversification techniques and distance measures in evolutionary design of 3D structuresAdam Klejda, Maciej Komosinski, Agnieszka Mensfelt. 124-127 [doi]
• QDax: on the benefits of massive parallelization for quality-diversityBryan Lim, Maxime Allard, Luca Grillotti, Antoine Cully. 128-131 [doi]
• De-redundancy in a random boolean network using knockoutJunxiu Liu, Jufang Dai, Min Su, Shunsheng Zhang, Yifan Hua, Yanhu Wang, Haiping Shu. 132-135 [doi]
• A comparative analysis on genome pleiotropy for evolved soft robotsDries Marzougui, Matthijs Biondina, Francis Wyffels. 136-139 [doi]
• Growth-based morphological development: a natural approach to fitness landscape shapingMartín Naya-Varela, Andrés Faiña, Richard J. Duro. 140-143 [doi]
• Do harsher environments cause selfish or altruistic behavior?Brandon Gower-Winter, Geoff Nitschke. 144-147 [doi]
• A single neural cellular automaton for body-brain co-evolutionSidney Pontes-Filho, Kathryn Walker, Elias Najarro, Stefano Nichele, Sebastian Risi. 148-151 [doi]
• Using evolutionary game theory to understand scalability in task allocationMostafa Rizk, Julian Garcia, Aldeida Aleti, David Green. 152-155 [doi]
• Geodesics, non-linearities and the archive of novelty searchAchkan Salehi, Alexandre Coninx, Stéphane Doncieux. 156-159 [doi]
• Comparison of evolutionary multi-objective optimization algorithms using imitation gameYuji Sato, Yoshihisa Murakawa. 160-163 [doi]
• Effects of encodings and quality-diversity on evolving 2D virtual creaturesFrank Veenstra, Martin Herring Olsen, Kyrre Glette. 164-167 [doi]
• Multilevel memetic hypergraph partitioning with greedy recombinationUtku Umur Acikalin, Bugra Caskurlu. 168-171 [doi]
• Neighbours similar fitness and the effectiveness of restarting local searchAldeida Aleti, Mark Wallace 0001, Markus Wagner 0007. 172-175 [doi]
• Cooperative co-evolutionary memetic algorithm for pickup and delivery problem with time windowsMiroslaw Blocho, Tomasz Jastrzab, Jakub Nalepa. 176-179 [doi]
• Multi-workflow scheduling in industrial edge: a genetic algorithm with heuristic strategyXiang-Ling Chen, Zhi-Xuan Zhang, Ming-can Geng, Wei-neng Chen. 180-183 [doi]
• Exact and sequential penalty weights in quadratic unconstrained binary optimisation with a digital annealerMarcos Diez García, Mayowa Ayodele, Alberto Moraglio. 184-187 [doi]
• On the fitness landscapes of interdependency models in the travelling thief problemMohamed El Yafrani, Marcella Scoczynski Ribeiro Martins, Myriam R. B. S. Delgado, Ricardo Lüders, Peter Nielsen, Markus Wagner 0007. 188-191 [doi]
• Exploiting landscape features for fitness prediction in university timetablingThomas Feutrier, Nadarajen Veerapen, Marie-Eléonore Kessaci. 192-195 [doi]
• A hyper-heuristic approach for the PDPTWAmir Nasiri, Ed Keedwell, Raphaël Dorne, Mathias Kern, Gilbert Owusu. 196-199 [doi]
• Towards evolutionary self-optimization of large multi-agent systemsFranciszek Seredynski, Tomasz Kulpa, Rolf Hoffmann. 200-203 [doi]
• External archive hybrid genetic algorithm for unequal area facility layout problemAiling Shen, Juan Lin 0001, Yiwen Zhong. 204-207 [doi]
• Policy network for solving flexible job shop scheduling problem with setup times and rescoure constraintsNing Xu, Tian-Ming Bu. 208-211 [doi]
• Entropy-based local fitnesses for evolutionary multiagent systemsAyhan Alp Aydeniz, Anna Nickelson, Kagan Tumer. 212-215 [doi]
• TGPGAN: towards expression-based generative adversarial networksFrancisco Baeta, João Correia, Tiago Martins, Penousal Machado. 216-219 [doi]
• Multi-fidelity optimization method with asynchronous generalized island model for AutoMLIsrael Campero-Jurado, Joaquin Vanschoren. 220-223 [doi]
• Interpretable pipelines with evolutionary optimized modules for reinforcement learning tasks with visual inputsLeonardo Lucio Custode, Giovanni Iacca. 224-227 [doi]
• MOPINNs: an evolutionary multi-objective approach to physics-informed neural networksTaco de Wolff, Hugo Carrillo Lincopi, Luis Martí, Nayat Sánchez Pi. 228-231 [doi]
• Particle swarm optimisation for sparsity-based feature selection in multi-label classificationKaan Demir, Bach Hoai Nguyen, Bing Xue 0001, Mengjie Zhang 0001. 232-235 [doi]
• Balancing teams with quality-diversity for heterogeneous multiagent coordinationGaurav Dixit, Kagan Tumer. 236-239 [doi]
• Cascades of evolutionary support vector machinesWojciech Dudzik, Jakub Nalepa, Michal Kawulok. 240-243 [doi]
• On stochastic evolving algorithmsIztok Fister Jr., Iztok Fister 0001. 244-247 [doi]
• Separating rule discovery and global solution composition in a learning classifier systemMichael Heider, Helena Stegherr, Jonathan Wurth, Roman Sraj, Jörg Hähner. 248-251 [doi]
• Evolvable hybrid ensembles for musical genre classificationDaniel Kostrzewa, Michal Ciszynski, Robert Brzeski. 252-255 [doi]
• Accelerated pattern search with variable solution size for simultaneous instance selection and generationHoang Lam Le, Ferrante Neri, Dario Landa Silva, Isaac Triguero. 256-259 [doi]
• A distributed particle swarm optimization algorithm for distributed clusteringZi-Xing Li, Xiao-Qi Guo, Wei-neng Chen, Xiao-Min Hu. 260-263 [doi]
• Multi-task optimisation for multi-objective feature selection in classificationJiabin Lin, Qi Chen 0002, Bing Xue 0001, Mengjie Zhang 0001. 264-267 [doi]
• KDE-GAN: enhancing evolutionary GAN with knowledge distillation and transfer learningZheping Liu, Andy Song, Nasser R. Sabar. 268-271 [doi]
• Scalable evolutionary hierarchical reinforcement learningSasha Abramowitz, Geoff Nitschke. 272-275 [doi]
• A comparative study of GP-based and state-of-the-art classifiers on a synthetic machine learning benchmarkPatryk Orzechowski, Pawel Renc, William G. La Cava, Jason H. Moore, Arkadiusz Sitek, Jaroslaw Was, Joost Wagenaar. 276-279 [doi]
• Bootstrapped fitness critics with bidirectional temporal differenceGolden Rockefeller, Kagan Tumer. 280-283 [doi]
• Cost-sensitive classification tree induction as a bi-level optimization problemRihab Said, Maha Elarbi, Slim Bechikh, Carlos A. Coello Coello, Lamjed Ben Said. 284-287 [doi]
• GA-auto-PU: a genetic algorithm-based automated machine learning system for positive-unlabeled learningJack D. Saunders, Alex Alves Freitas. 288-291 [doi]
• DEvS: data distillation algorithm based on evolution strategyNadiya Shvai, Arcadi Llanza, Md. Abul Hasnat, Amir Nakib. 292-295 [doi]
• Chaotic genetic bee colony: combining chaos theory and genetic bee algorithm for feature selection in microarray cancer classificationSammuel Ramos da Silva, Jadson Castro Gertrudes. 296-299 [doi]
• Binary and multinomial classification through evolutionary symbolic regressionMoshe Sipper. 300-303 [doi]
• Evolving convolutional neural networks for intrusion detection system using hybrid multi-strategy aquila optimizerWei Sun, Qianmu Li, Pengchuan Wang, Jun Hou 0002. 304-307 [doi]
• EvoJAX: hardware-accelerated neuroevolutionYujin Tang, Yingtao Tian, David Ha. 308-311 [doi]
• Designing a novel and high performance algorithmic trading model using evolutionary AutoML and technical analysisAbhiram Tirumala, Rishi Bhatnager, Sriram Mudireddy, Pranav Manjunath, Jason Zutty. 312-315 [doi]
• Comparing different metaheuristics for model selection in a supervised learning classifier systemJonathan Wurth, Michael Heider, Helena Stegherr, Roman Sraj, Jörg Hähner. 316-319 [doi]
• Fairness in generative modeling: do it unsupervised!Mariia Zameshina, Olivier Teytaud, Fabien Teytaud, Vlad Hosu, Nathanaël Carraz Rakotonirina, Laurent Najman, Markus Wagner 0007. 320-323 [doi]
• Estimating the quality of initial populations in multi-objective evolutionary algorithmsTobias Benecke, Sanaz Mostaghim. 324-327 [doi]
• Multi-objective counterfactual fairnessSusanne Dandl, Florian Pfisterer, Bernd Bischl. 328-331 [doi]
• Exploring the decision and objective space of SAT constrained multi-objective problemsFelipe Honjo Ide, Hernán E. Aguirre, Minami Miyakawa, Darrell Whitley. 332-335 [doi]
• Application of nature inspired algorithms to multi-objective optimization of new generation network problemStanislaw Kozdrowski, Kacper Wnuk. 336-339 [doi]
• A computationally fast but approximate MIP-DoM calculation for multi-objective optimizationClaudio Lucio do Val Lopes, Flávio Vinícius Cruzeiro Martins, Elizabeth F. Wanner, Kalyanmoy Deb. 340-343 [doi]
• BOBEA: a bi-objective biclustering evolutionary algorithm for genome-wide association analysisOns Maâtouk, Emna Ayari, Hend Bouziri, Wassim Ayadi. 344-347 [doi]
• A novel evolutionary framework based on a family concept for solving multi-objective bilevel optimization problemsJesús-Adolfo Mejía-de-Dios, Alejandro Rodríguez-Molina, Efrén Mezura-Montes. 348-351 [doi]
• Towards multi-objective optimization of sustainable insect production chainsNisrine Mouhrim, Sergiy Smetana, Anita Bhatia, Alexander Mathys, Ashley Green, Daniela Peguero, Alberto Tonda. 352-355 [doi]
• On the potential of automated algorithm configuration on multi-modal multi-objective optimization problemsJeroen Rook, Heike Trautmann, Jakob Bossek, Christian Grimme. 356-359 [doi]
• Fair feature subset selection using multiobjective genetic algorithmAyaz Ur Rehman, Anas Nadeem, Muhammad Zubair Malik. 360-363 [doi]
• Surrogate models for IoT task allocation optimizationDominik Weikert, Christoph Steup, Sanaz Mostaghim. 364-366 [doi]
• Extending the push and pull search framework with boundary search for constrained multi-objective optimizationErling Wisløff, Marius Aarsnes, Kazi Shah Nawaz Ripon, Pauline Haddow. 367-370 [doi]
• An analysis on effectiveness of estimated convergence points for enhancement of multi-objective optimization algorithmsYuhei Yamaya, Yan Pei. 371-374 [doi]
• A constraint cone decomposition evolutionary algorithm with dual populationsWeiqin Ying, Yanqi Lan, Yu Wu, Xuanda Pan, Banban Huang, Jianyi Peng. 375-378 [doi]
• The effect of epigenetic blocking on dynamic multi-objective optimisation problemsSizhe Yuen, Thomas H. G. Ezard, Adam J. Sobey. 379-382 [doi]
• Learning to balance exploration and exploitation in pareto local search for multi-objective combinatorial optimizationHaotian Zhang, Jialong Shi, Jianyong Sun, ZongBen Xu. 383-386 [doi]
• A hybrid self-adapting multi-swarm algorithm based on PSO and CMA-ES for continuous dynamic optimizationShakhnaz Akhmedova, Vladimir Stanovov, Aleksei Vakhnin. 387-390 [doi]
• Dynamic perturbation for population diversity management in differential evolutionLe Van Cuong, Nguyen Ngoc Bao, Nguyen Khanh Phuong, Huynh Thi Thanh Binh. 391-394 [doi]
• Distributed evolution strategies for large-scale optimizationQiqi Duan, Guochen Zhou, Chang Shao, Yijun Yang, Yuhui Shi. 395-398 [doi]
• A layered learning estimation of distribution algorithmYong Li, Qiang Yang, Xu-Dong Gao, Zhen Yu Lu, Jun Zhang. 399-402 [doi]
• The effect of mirrored sampling with active CMA and sample reuse in the CMAES-APOP algorithmDuc Manh Nguyen. 403-406 [doi]
• Improving the differential evolution strategy by coupling it with CMA-ESEryk Warchulski, Jaroslaw Arabas, Rafal Biedrzycki. 407-410 [doi]
• A novel dynamic analysis on multi-scale quantum harmonic oscillator algorithm using double-well functionGuosong Yang, Peng Wang, Xinyu Yin. 411-414 [doi]
• A GA based approach for solving ring design telecommunication networkEisa Alblooshi, Ahmed Alblooshi, Kin Poon, Anis Ouali. 415-418 [doi]
• An edge quality aware crossover operator for application to the capacitated vehicle routing problemDarren M. Chitty, William B. Yates, Ed Keedwell. 419-422 [doi]
• Neural architecture search using genetic algorithm for facial expression recognitionShuchao Deng, Yanan Sun, Edgar Galván. 423-426 [doi]
• The pole balancing problem from the viewpoint of system flexibilityLéo Françoso Dal Piccol Sotto, Sebastian Mayer, Jochen Garcke. 427-430 [doi]
• Boosting the convergence of a GA-based wrapper for feature selection problems on high-dimensional dataJuan Carlos Gómez-López, Juan José Escobar, Antonio Francisco Díaz, Miguel Damas, Francisco Gil Montoya, Jesús González 0001. 431-434 [doi]
• Trimming, ordering, and similarity check for DSMGA-II: DSMGA-II-TOSChing-Chung Huang, Tian-Li Yu. 435-438 [doi]
• Quantum strategy of population initialization in genetic algorithmJun Suk Kim, Chang Wook Ahn. 439-442 [doi]
• Evolutionary constrained multi-task optimization: benchmark problems and preliminary resultsYanchi Li, Wenyin Gong, Shuijia Li. 443-446 [doi]
• Initialization method of genetic algorithm based on improved clustering algorithmHao Li, Xuesong Jiang, Xiumei Wei. 447-450 [doi]
• Evolutionary operation setting for outcome accumulation type evolutionary rule discovery methodShogo Matsuno, Kaoru Shimada. 451-454 [doi]
• Improving DSMGA-II performance on hierarchical problems by introducing preservative back mixingChi-Meng Ngai, Tian-Li Yu. 455-458 [doi]
• Networks of evolution: modelling and deconstructing genetic algorithms using dynamic networksClodomir J. Santana Jr., Edward C. Keedwell, Ronaldo Menezes. 459-462 [doi]
• Quantum-enhanced selection operators for evolutionary algorithmsDavid Von Dollen, Sheir Yarkoni, Daniel Weimer, Florian Neukart, Thomas Bäck. 463-466 [doi]
• Black-box adversarial attack via overlapped shapesPhoenix Neale Williams, Ke Li 0001, Geyong Min. 467-468 [doi]
• Adversarial example generation via genetic algorithm: a preliminary resultShasha Zhou, Ke Li 0001, Geyong Min. 469-470 [doi]
• Fitness diversification in the service of fitness optimization: a comparison studyKamil Basiukajc, Maciej Komosinski, Konrad Miazga. 471-474 [doi]
• Independent influence of exploration and exploitation for metaheuristic-based recommendationsAlexandre Bettinger, Armelle Brun, Anne Boyer. 475-478 [doi]
• Dynamic multi-objective ensemble of acquisition functions in batch bayesian optimizationJixiang Chen, Fu Luo, Zhenkun Wang. 479-482 [doi]
• Dynamic evaluation of decomposition methods for large-scale optimization problems using an island modelGrasiele R. Duarte, Beatriz Souza Leite Pires de Lima. 483-486 [doi]
• Improved data clustering using multi-trial vector-based differential evolution with gaussian crossoverParham Hadikhani, Daphne Teck Ching Lai, Wee-Hong Ong, Mohammad H. Nadimi-Shahraki. 487-490 [doi]
• Reduction of genetic drift in population-based incremental learning via entropy regularizationRyoki Hamano, Shinichi Shirakawa. 491-494 [doi]
• Enhancing MOEA/D with learning: application to routing problems with time windowsClément Legrand, Diego Cattaruzza, Laetitia Jourdan, Marie-Eléonore Kessaci. 495-498 [doi]
• Benchmarking algorithm portfolio construction methodsMario Andrés Muñoz, Hamed Soleimani, Sevvandi Kandanaarachchi. 499-502 [doi]
• A surrogate model-based genetic algorithm for the optimal policy in cart-pole balancing environmentsSeung Soo Shin, Yong-Hyuk Kim. 503-505 [doi]
• Implementing and evaluating parallel evolutionary algorithms in modern GPU computing librariesPatrik Valkovic, Martin Pilát. 506-509 [doi]
• Localized distance and time-based differential evolution for multimodal optimization problemsHong Zhao, Jiarui Li, Jing Liu. 510-513 [doi]
• Using domain knowledge in coevolution and reinforcement learning to simulate a logistics enterpriseYing Zhao 0006, Erik Hemberg, Nate Derbinsky, Gabino Mata, Una-May O'Reilly. 514-517 [doi]
• Genetic programming with external memory in sequence recall tasksMihyar Al Masalma, Malcolm I. Heywood. 518-521 [doi]
• Benchmarking genetic programming in a multi-action reinforcement learning locomotion taskRyan Amaral, Alexandru Ianta, Caleidgh Bayer, Robert J. Smith 0002, Malcolm I. Heywood. 522-525 [doi]
• Bayesian model selection for reducing bloat and overfitting in genetic programming for symbolic regressionGeoffrey F. Bomarito, Patrick E. Leser, N. C. M. Strauss, K. M. Garbrecht, J. D. Hochhalter. 526-529 [doi]
• A preliminary study of prediction interval methods with genetic programmingKarina Brotto Rebuli, Mario Giacobini, Niccolò Tallone, Leonardo Vanneschi. 530-533 [doi]
• Initialisation and grammar design in grammar-guided evolutionary computationGrant Dick, Peter A. Whigham. 534-537 [doi]
• Going faster and hence further with lexicase selectionLi Ding, Ryan Boldi, Thomas Helmuth, Lee Spector. 538-541 [doi]
• Genetic programming for electric vehicle routing problem with soft time windowsFrancisco Javier Gil Gala, Marko Durasevic, Domagoj Jakobovic. 542-545 [doi]
• Genetic programming for understanding cognitive biases that generate polarization in social networksChathika Gunaratne, Robert M. Patton. 546-549 [doi]
• Active learning improves performance on symbolic regression tasks in StackGPNathan Haut, Wolfgang Banzhaf, Bill Punch. 550-553 [doi]
• Incorporating sub-programs as knowledge in program synthesis by PushGP and adaptive replacement mutationYifan He, Claus Aranha, Tetsuya Sakurai. 554-557 [doi]
• Discovery of implicit relationships from data using linear programming and mixed integer linear programmingQuang Nhat Huynh, Hemant Kumar Singh, Tapabrata Ray. 558-561 [doi]
• Automatically evolving malice scoring models through utilisation of genetic programming: a cooperative coevolution approachTaran Cyriac John, Muhammad Shabbir Abbasi, Harith Al-Sahaf, Ian Welch. 562-565 [doi]
• Phenotypic duplication and inversion in cartesian genetic programming applied to boolean function learningRoman Kalkreuth. 566-569 [doi]
• Compositional genetic programming for symbolic regressionKrzysztof Krawiec, Dominik Kossinski. 570-573 [doi]
• Failed disruption propagation in integer genetic programmingWilliam B. Langdon. 574-577 [doi]
• Optimizing LLVM pass sequences with shackleton: a linear genetic programming frameworkHannah Peeler, Shuyue Stella Li, Andrew N. Sloss, Kenneth N. Reid, Yuan Yuan 0004, Wolfgang Banzhaf. 578-581 [doi]
• Using graph neural networks as surrogate models in genetic programmingMartin Pilát, Gabriela Suchopárová. 582-585 [doi]
• On the interaction between lexicase selection, modularity and data subsetsBenjamin Portman, Malcolm I. Heywood. 586-589 [doi]
• Espresso to the rescue of genetic programming facing exponential complexityNicolas Potvin, Hugues Bersini, Dragomir Milojevic. 590-593 [doi]
• On the effect of embedding hierarchy within multi-objective optimization for evolving symbolic regression modelsAtif Rafiq, Enrique Naredo, Meghana Kshirsagar 0002, Conor Ryan. 594-597 [doi]
• Environments with local scopes for modules in genetic programmingAnil Kumar Saini, Lee Spector, Thomas Helmuth. 598-601 [doi]
• Evolving parsimonious circuits through shapley value-based genetic programmingXinming Shi, Jiashi Gao, Leandro L. Minku, Xin Yao 0001. 602-605 [doi]
• Analyzing optimized constants in genetic programming on a real-world regression problemDominik Sobania, Martin Briesch, David Wittenberg, Franz Rothlauf. 606-607 [doi]
• Imbalanced classification with tpg genetic programming: impact of problem imbalance and selection mechanismsNicolas Sourbier, Justine Bonnot, Frédéric Majorczyk, Olivier Gesny, Thomas Guyet, Maxime Pelcat. 608-611 [doi]
• Denoising autoencoder genetic programming for real-world symbolic regressionDavid Wittenberg, Franz Rothlauf. 612-614 [doi]
• Genetic programming with diverse partner selection for dynamic flexible job shop schedulingMeng Xu, Yi Mei 0001, Fangfang Zhang 0003, Mengjie Zhang 0001. 615-618 [doi]
• Large scale image classification using GPU-based genetic programmingPeng Zeng, Andrew Lensen, Yanan Sun 0001. 619-622 [doi]
• Regulatory genotype-to-phenotype mappings improve evolvability in genetic programmingJinting Zhang, Ting Hu. 623-626 [doi]
• The diversity-accuracy duality in ensembles of classifiersRui P. Cardoso, Emma Hart, David Burth Kurka, Jeremy V. Pitt. 627-630 [doi]
• MFENAS: multifactorial evolution for neural architecture searchLi Chen, Hua Xu. 631-634 [doi]
• Accelerating neural architecture exploration across modalities using genetic algorithmsDaniel Cummings, Sharath Nittur Sridhar, Anthony Sarah, Maciej Szankin. 635-638 [doi]
• Synaptic pruning with MAP-elitesFederico Da Rold, Olaf Witkovski, Nathanaël Aubert-Kato. 639-642 [doi]
• CGP-NAS: real-based solutions encoding for multi-objective evolutionary neural architecture searchCosijopii Garcia-Garcia, Hugo Jair Escalante, Alicia Morales-Reyes. 643-646 [doi]
• Neuroevolution based multi-objective algorithm for gene selection and microarray classificationDaniel García-Núñez, Katya Rodríguez-Vázquez, Carlos Hernández. 647-650 [doi]
• Neuroevolution of recurrent architectures on control tasksMaximilien Le Clei, Pierre Bellec. 651-654 [doi]
• Efficient guided evolution for neural architecture searchVasco Lopes, Miguel Santos, Bruno Degardin, Luís A. Alexandre. 655-658 [doi]
• ONE-NAS: an online neuroevolution based neural architecture search for time series forecastingZimeng Lyu, Travis Desell. 659-662 [doi]
• A new grammatical evolution method for generating deep convolutional neural networks with novel topologiesThiago Zafalon Miranda, Diorge Brognara Sardinha, Márcio Porto Basgalupp, Ricardo Cerri. 663-666 [doi]
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• Routing for bridge inspecting robots using a metaheuristic genetic algorithmBryan Dedeurwaerder, Sushil J. Louis, Siming Liu 0001, Nicholas Harris. 703-706 [doi]
• Evolving polydisperse soft robotic jamming grippersSeth G. Fitzgerald, Gary W. Delaney, David Howard, Frédéric Maire. 707-710 [doi]
• Evolving spaceships with a hybrid L-system constrained optimisation evolutionary algorithmRoberto Gallotta, Kai Arulkumaran, Lisa B. Soros. 711-714 [doi]
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• Selection schemes from evolutionary computing show promise for directed evolution of microbesAlexander Lalejini, Emily L. Dolson, Anya E. Vostinar, Luis Zaman. 723-726 [doi]
• Optimizing sample diversity with fairness constraints on imbalanced, sparse, hiring dataLauren R. McCarey, Thomas S. McTavish. 727-730 [doi]
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• Facility location problem and permutation flow shop scheduling problem: a linked optimisation problemAkinola Ogunsemi, John A. W. McCall, Mathias Kern, Benjamin Lacroix, David Corsar, Gilbert Owusu. 735-738 [doi]
• A hybrid optimization tool for active magnetic regeneratorAnna Ouskova Leonteva, Michel Risser, Radia Hamane, Anne Jeannin-Girardon, Pierre Parrend, Pierre Collet. 739-742 [doi]
• Rethinking of controller placement problem from static optimization to multi-objective dynamic optimizationSanjai Pathak, Ashish Mani, Mayank Sharma, Amlan Chatterjee. 743-746 [doi]
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• Adapting mutation and recombination operators to range-aware relations in real-world application dataChristina Plump, Bernhard J. Berger, Rolf Drechsler. 755-758 [doi]
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