Table of Contents

• PLAN: a leafcutter ant colony optimization algorithm for ride-hailing servicesAnoushka Alavilli, Mai Vu. 4-12 [doi]
• A new Ant colony optimization metaheuristic based on pheromone guided local search instead of constructive approachSamia Sammoud, Inès Alaya. 13-21 [doi]
• Measuring optimiser performance on a conical barrier tree benchmarkItshak Tkach, Tim Blackwell. 22-30 [doi]
• Environment induced emergence of collective behavior in evolving swarms with limited sensingFuda van Diggelen, Jie Luo, Tugay Alperen Karagüzel, Nicolas Cambier, Eliseo Ferrante, A. E. Eiben. 31-39 [doi]
• Progressive sampling surrogate-assisted particle swarm optimization for large-scale expensive optimizationHong-Rui Wang, Chun-Hua Chen, Yun Li, Jun Zhang, Zhi-hui Zhan. 40-48 [doi]
• Social learning particle swarm optimization with two-surrogate collaboration for offline data-driven multiobjective optimizationQi-Te Yang, Zhi-hui Zhan, Yun Li 0002, Jun Zhang 0003. 49-57 [doi]
• Hierarchical quality-diversity for online damage recoveryMaxime Allard, Simón C. Smith, Konstantinos I. Chatzilygeroudis, Antoine Cully. 58-67 [doi]
• Illuminating diverse neural cellular automata for level generationSam Earle, Justin Snider, Matthew C. Fontaine, Stefanos Nikolaidis, Julian Togelius. 68-76 [doi]
• Relevance-guided unsupervised discovery of abilities with quality-diversity algorithmsLuca Grillotti, Antoine Cully. 77-85 [doi]
• Learning to walk autonomously via reset-free quality-diversityBryan Lim, Alexander Reichenbach, Antoine Cully. 86-94 [doi]
• Hybridizing bio-inspired strategies with infotaxis through genetic programmingJoão Macedo, Lino Marques, Ernesto Costa. 95-103 [doi]
• Adaptive phototaxis of a swarm of mobile robots using positive and negative feedback self-alignmentYoones Mirhosseini, Matan Yah Ben Zion, Olivier Dauchot, Nicolas Bredèche. 104-112 [doi]
• Plasticity and evolvability under environmental variability: the joint role of fitness-based selection and niche-limited competitionEleni Nisioti, Clément Moulin-Frier. 113-121 [doi]
• Evolving programmable computational metamaterialsAtoosa Parsa, Dong Wang, Corey S. O'Hern, Mark D. Shattuck, Rebecca Kramer-Bottiglio, Josh C. Bongard. 122-129 [doi]
• Minimal neural network models for permutation invariant agentsJoachim Winther Pedersen, Sebastian Risi. 130-138 [doi]
• Multi-objective quality diversity optimizationThomas Pierrot, Guillaume Richard, Karim Beguir, Antoine Cully. 139-147 [doi]
• Evolving modular soft robots without explicit inter-module communication using local self-attentionFederico Pigozzi, Yujin Tang, Eric Medvet, David Ha. 148-157 [doi]
• Deep surrogate assisted MAP-elites for automated hearthstone deckbuildingYulun Zhang, Matthew C. Fontaine, Amy K. Hoover, Stefanos Nikolaidis. 158-167 [doi]
• EvoRobogami: co-designing with humans in evolutionary robotics experimentsZonghao Huang, Quinn Wu, David Howard, Cynthia R. Sung. 168-176 [doi]
• Efficient heuristics and metaheuristics for the unrelated parallel machine scheduling problem with release dates and setup timesMohamed Elamine Athmani, Taha Arbaoui, Younes Mimene, Farouk Yalaoui. 177-185 [doi]
• Exploring the feature space of TSP instances using quality diversityJakob Bossek, Frank Neumann 0001. 186-194 [doi]
• Evolving labelings of graceful graphsLuke Branson, Andrew M. Sutton. 195-203 [doi]
• Drils revisited: on the combination of perturbation with graybox optimization techniquesLorenzo Canonne, Bilel Derbel. 204-212 [doi]
• Guided local search with an adaptive neighbourhood size heuristic for large scale vehicle routing problemsJoão Guilherme Cavalcanti Costa, Yi Mei 0001, Mengjie Zhang 0001. 213-221 [doi]
• Improved regression models for algorithm configurationMarcelo de Souza, Marcus Ritt. 222-231 [doi]
• Metaheuristic algorithms for the bus driver scheduling problem with complex break constraintsLucas Kletzander, Tommaso Mannelli Mazzoli, Nysret Musliu. 232-240 [doi]
• A biased random key genetic algorithm applied to target set selection in viral marketingAlbert López Serrano, Christian Blum 0001. 241-250 [doi]
• Understanding the cost of fitness evaluation for subset selection: Markov chain analysis of stochastic local searchOle Jakob Mengshoel, Eirik Lund Flogard, Tong Yu 0001, Jon Riege. 251-259 [doi]
• On the use of quality diversity algorithms for the traveling thief problemAdel Nikfarjam, Aneta Neumann, Frank Neumann 0001. 260-268 [doi]
• On turning black - into dark gray-optimization with the direct empirical linkage discovery and partition crossoverMichal Witold Przewozniczek, Renato Tinós, Bartosz Frej, Marcin M. Komarnicki. 269-277 [doi]
• Negative learning Ant colony optimization for network alignmentGuillem Rodríguez Corominas, Christian Blum 0001, Maria J. Blesa. 278-286 [doi]
• On funnel depths and acceptance criteria in stochastic local searchSarah L. Thomson, Gabriela Ochoa. 287-295 [doi]
• Iterated local search with perturbation based on variables interaction for pseudo-boolean optimizationRenato Tinós, Michal Witold Przewozniczek, Darrell Whitley. 296-304 [doi]
• What makes the dynamic capacitated Arc routing problem hard to solve: insights from fitness landscape analysisHao Tong, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao 0001. 305-313 [doi]
• Local ranking explanation for genetic programming evolved routing policies for uncertain capacitated Arc routing problemsShaolin Wang, Yi Mei 0001, Mengjie Zhang 0001. 314-322 [doi]
• Pittsburgh learning classifier systems for explainable reinforcement learning: comparing with XCSJordan T. Bishop, Marcus Gallagher, Will N. Browne. 323-331 [doi]
• Fitness shaping for multiple teamsJoshua Cook, Kagan Tumer. 332-340 [doi]
• DiBB: distributing black-box optimizationGiuseppe Cuccu, Luca Rolshoven, Fabien Vorpe, Philippe Cudré-Mauroux, Tobias Glasmachers. 341-349 [doi]
• Diversifying behaviors for learning in asymmetric multiagent systemsGaurav Dixit, Everardo Gonzalez, Kagan Tumer. 350-358 [doi]
• Evolutionary feature selection: a novel wrapper feature selection architecture based on evolutionary strategiesAaryan Dubey, Alexandre Hoppe Inoue, Pedro Terra Fernandes Birmann, Sammuel Ramos da Silva. 359-366 [doi]
• Coevolutionary generative adversarial networks for medical image augumentation at scaleDiana Flores, Erik Hemberg, Jamal Toutouh, Una-May O'Reilly. 367-376 [doi]
• Assessing evolutionary terrain generation methods for curriculum reinforcement learningDavid Howard, Humphrey Munn, Davide Dolcetti, Josh Kannemeyer, Nicole L. Robinson. 377-384 [doi]
• Evolving transferable neural pruning functionsYuchen Liu, S. Y. Kung, David Wentzlaff. 385-394 [doi]
• Multi-objective framework for quantile forecasting in financial time series using transformersSamuel López-Ruiz, Carlos Ignacio Hernández Castellanos, Katya Rodríguez-Vázquez. 395-403 [doi]
• Hyperparameter tuning in echo state networksFilip Matzner. 404-412 [doi]
• The Bayesian learning classifier system: implementation, replicability, comparison with XCSFDavid Pätzel, Jörg Hähner. 413-421 [doi]
• Absumption based on overgenerality and condition-clustering based specialization for XCS with continuous-valued inputsHiroki Shiraishi, Yohei Hayamizu, Hiroyuki Sato, Keiki Takadama. 422-430 [doi]
• Can the same rule representation change its matching area?: enhancing representation in XCS for continuous space by probability distribution in multiple dimensionHiroki Shiraishi, Yohei Hayamizu, Hiroyuki Sato, Keiki Takadama. 431-439 [doi]
• Multi-modal multi-objective model-based genetic programming to find multiple diverse high-quality modelsE. M. C. Sijben, Tanja Alderliesten, Peter A. N. Bosman. 440-448 [doi]
• Understanding AutoML search spaces with local optima networksMatheus C. Teixeira, Gisele L. Pappa. 449-457 [doi]
• On genetic programming representations and fitness functions for interpretable dimensionality reductionThomas Uriot, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman. 458-466 [doi]
• Multi-objective QUBO solver: bi-objective quadratic assignment problemMayowa Ayodele, Richard Allmendinger 0001, Manuel López-Ibáñez 0001, Matthieu Parizy. 467-475 [doi]
• An enhanced adaptive geometry evolutionary algorithm using stochastic diversity mechanismFodil Benali, Damien Bodénès, Cyril De Runz, Nicolas Labroche. 476-483 [doi]
• Parallelization of corner sort with CUDA for many-objective optimizationVandana Bharti, Aryan Singhal, Anant Saxena, Bhaskar Biswas, Kaushal Kumar Shukla. 484-492 [doi]
• Cost-vs-accuracy of sampling in multi-objective combinatorial exploratory landscape analysisRaphaël Cosson, Bilel Derbel, Arnaud Liefooghe, Sébastien Vérel, Hernán E. Aguirre, Qingfu Zhang 0001, Kiyoshi Tanaka. 493-501 [doi]
• Multi-objective NK landscapes with heterogeneous objectivesRaphaël Cosson, Roberto Santana, Bilel Derbel, Arnaud Liefooghe. 502-510 [doi]
• Multi-point acquisition function for constraint parallel efficient multi-objective optimizationRoy de Winter, Bas van Stein, Thomas Bäck. 511-519 [doi]
• The (1 + (λ, λ)) global SEMO algorithmBenjamin Doerr, Omar El Hadri, Adrien Pinard. 520-528 [doi]
• Reproducibility and baseline reporting for dynamic multi-objective benchmark problemsDaniel Herring, Michael Kirley, Xin Yao 0001. 529-537 [doi]
• Component-wise analysis of automatically designed multiobjective algorithms on constrained problemsYuri Cossich Lavinas, Marcelo Ladeira, Gabriela Ochoa, Claus Aranha. 538-546 [doi]
• A classification-assisted level-based learning evolutionary algorithm for expensive multiobjective optimization problemsZhuo Liu, Xiaolin Xiao, Feng-Feng Wei, Wei-neng Chen. 547-555 [doi]
• Region of interest based non-dominated sorting genetic algorithm-II: an invite and conquer approachManu Manuel, Benjamin Hien, Simon Conrady, Arne Kreddig, Nguyen Anh Vu Doan, Walter Stechele. 556-564 [doi]
• An improved Pareto front modeling algorithm for large-scale many-objective optimizationAnnibale Panichella. 565-573 [doi]
• Unsupervised framework for comment-based multi-document extractive summarizationVishal Singh Roha, Naveen Saini, Sriparna Saha 0001, Jose G. Moreno 0001. 574-582 [doi]
• A bounded archive based for bi-objective problems based on distance and e-dominance to avoid cyclic behaviorCarlos Hernández, Oliver Schütze. 583-591 [doi]
• MOLE: digging tunnels through multimodal multi-objective landscapesLennart Schäpermeier, Christian Grimme, Pascal Kerschke. 592-600 [doi]
• A two-phase framework with a bézier simplex-based interpolation method for computationally expensive multi-objective optimizationRyoji Tanabe, Youhei Akimoto, Ken Kobayashi, Hiroshi Umeki, Shinichi Shirakawa, Naoki Hamada. 601-610 [doi]
• Better approximation guarantees for the NSGA-II by using the current crowding distanceWeijie Zheng 0001, Benjamin Doerr. 611-619 [doi]
• SELECTOR: selecting a representative benchmark suite for reproducible statistical comparisonGjorgjina Cenikj, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov. 620-629 [doi]
• Learning rate adaptation by line search in evolution strategies with recombinationArmand Gissler, Anne Auger, Nikolaus Hansen. 630-638 [doi]
• CMA-ES with margin: lower-bounding marginal probability for mixed-integer black-box optimizationRyoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa. 639-647 [doi]
• The importance of landscape features for performance prediction of modular CMA-ES variantsAna Kostovska, Diederick Vermetten, Saso Dzeroski, Carola Doerr, Peter Korosec, Tome Eftimov. 648-656 [doi]
• A collection of deep learning-based feature-free approaches for characterizing single-objective continuous fitness landscapesMoritz Vinzent Seiler, Raphael Patrick Prager, Pascal Kerschke, Heike Trautmann. 657-665 [doi]
• The influence of noise on multi-parent crossover for an island model GABrahim Aboutaib, Andrew M. Sutton. 666-674 [doi]
• GPU-accelerated parallel gene-pool optimal mixing in a gray-box optimization settingAnton Bouter, Peter A. N. Bosman. 675-683 [doi]
• Niching-based evolutionary diversity optimization for the traveling salesperson problemAnh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann 0001. 684-693 [doi]
• Reducing the cost of partition crossover on large MAXSAT problems: the PX-preprocessorPreston Dunton, Darrell Whitley. 694-702 [doi]
• Solving multi-structured problems by introducing linkage kernels into GOMEAArthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman. 703-711 [doi]
• TAGA: a transfer-based black-box adversarial attack with genetic algorithmsLiang-Jung Huang, Tian-Li Yu. 712-720 [doi]
• Effective mutation rate adaptation through group elite selectionAkarsh Kumar, Bo Liu, Risto Miikkulainen, Peter Stone. 721-729 [doi]
• LUCIE: an evaluation and selection method for stochastic problemsErwan Lecarpentier, Paul Templier, Emmanuel Rachelson, Dennis G. Wilson. 730-738 [doi]
• Simple genetic operators are universal approximators of probability distributions (and other advantages of expressive encodings)Elliot Meyerson, Xin Qiu, Risto Miikkulainen. 739-748 [doi]
• Evolutionary diversity optimisation for the traveling thief problemAdel Nikfarjam, Aneta Neumann, Frank Neumann 0001. 749-756 [doi]
• Local optima organize into lattices under recombination: an example using the traveling salesman problemDarrell Whitley, Gabriela Ochoa. 757-765 [doi]
• Theory-inspired parameter control benchmarks for dynamic algorithm configurationAndré Biedenkapp, Nguyen Dang 0001, Martin S. Krejca, Frank Hutter, Carola Doerr. 766-775 [doi]
• MBORE: multi-objective Bayesian optimisation by density-ratio estimationGeorge De Ath, Tinkle Chugh, Alma A. M. Rahat. 776-785 [doi]
• Guiding surrogate-assisted multi-objective optimisation with decision maker preferencesFinley J. Gibson, Richard M. Everson, Jonathan E. Fieldsend. 786-795 [doi]
• Hard problems are easier for success-based parameter controlMario Alejandro Hevia Fajardo, Dirk Sudholt. 796-804 [doi]
• High performance evolutionary computation with tensor-based accelerationJonatan Klosko, Mateusz Benecki, Grzegorz Wcislo, Jacek Dajda, Wojciech Turek. 805-813 [doi]
• Are evolutionary algorithms safe optimizers?Youngmin Kim, Richard Allmendinger 0001, Manuel López-Ibáñez 0001. 814-822 [doi]
• Black-box min-max continuous optimization using CMA-ES with worst-case ranking approximationAtsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto. 823-831 [doi]
• Coevolutionary Pareto diversity optimizationAneta Neumann, Denis Antipov, Frank Neumann 0001. 832-839 [doi]
• Expensive optimization with production-graph resource constraints: a first look at a new problem classStefan Pricopie, Richard Allmendinger 0001, Manuel López-Ibáñez 0001, Clyde Fare, Matt Benatan, Joshua Knowles. 840-848 [doi]
• Using phylogenetic analysis to enhance genetic improvementPenny Faulkner Rainford, Barry Porter. 849-857 [doi]
• Boomerang-shaped neural embeddings for NK landscapesRoberto Santana, Arnaud Liefooghe, Bilel Derbel. 858-866 [doi]
• Analyzing the impact of undersampling on the benchmarking and configuration of evolutionary algorithmsDiederick Vermetten, Hao Wang 0025, Manuel López-Ibáñez 0001, Carola Doerr, Thomas Bäck. 867-875 [doi]
• On optimal static and dynamic parameter choices for fixed-target optimizationDmitry Vinokurov, Maxim Buzdalov 0001. 876-883 [doi]
• Improving LSHADE by means of a pre-screening mechanismMateusz Zaborski, Jacek Mandziuk. 884-892 [doi]
• Novel ensemble collaboration method for dynamic scheduling problemsMarko Durasevic, Lucija Planinic, Francisco Javier Gil Gala, Domagoj Jakobovic. 893-901 [doi]
• Automated grammar-based feature selection in symbolic regressionMuhammad Sarmad Ali, Meghana Kshirsagar 0002, Enrique Naredo, Conor Ryan. 902-910 [doi]
• Genetic programming for structural similarity design at multiple spatial scalesIllya Bakurov, Marco Buzzelli, Mauro Castelli, Raimondo Schettini, Leonardo Vanneschi. 911-919 [doi]
• Transformation-interaction-rational representation for symbolic regressionFabrício Olivetti de França. 920-928 [doi]
• 2: lexicase selection with lexicographic parsimony pressureAllan de Lima, Samuel Carvalho, Douglas Mota Dias, Enrique Naredo, Joseph P. Sullivan, Conor Ryan. 929-937 [doi]
• Comparing optimistic and pessimistic constraint evaluation in shape-constrained symbolic regressionChristian Haider, Fabrício Olivetti de França, Gabriel Kronberger, Bogdan Burlacu. 938-945 [doi]
• Taylor genetic programming for symbolic regressionBaihe He, Qiang Lu, Qingyun Yang, Jake Luo, Zhiguang Wang. 946-954 [doi]
• Graph-based linear genetic programming: a case study of dynamic schedulingZhixing Huang, Yi Mei 0001, Fangfang Zhang 0003, Mengjie Zhang 0001. 955-963 [doi]
• Measuring failed disruption propagation in genetic programmingWilliam B. Langdon, Afnan A. Al-Subaihin, David Clark. 964-972 [doi]
• Evolvability degeneration in multi-objective genetic programming for symbolic regressionDazhuang Liu, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman. 973-981 [doi]
• Exploring hidden semantics in neural networks with symbolic regressionYuanzhen Luo, Qiang Lu, Xilei Hu, Jake Luo, Zhiguang Wang. 982-990 [doi]
• Co-evolutionary probabilistic structured grammatical evolutionJessica Mégane, Nuno Lourenço 0002, Penousal Machado. 991-999 [doi]
• Functional code building genetic programmingEdward R. Pantridge, Thomas Helmuth, Lee Spector. 1000-1008 [doi]
• Evolving generalizable multigrid-based helmholtz preconditioners with grammar-guided genetic programmingJonas Schmitt, Harald Köstler. 1009-1018 [doi]
• Choose your programming copilot: a comparison of the program synthesis performance of github copilot and genetic programmingDominik Sobania, Martin Briesch, Franz Rothlauf. 1019-1027 [doi]
• Procedural content generation using neuroevolution and novelty search for diverse video game levelsMichael Beukman, Christopher W. Cleghorn, Steven James. 1028-1037 [doi]
• Evolutionary neural cascade search across supernetworksAlexander Chebykin, Tanja Alderliesten, Peter A. N. Bosman. 1038-1047 [doi]
• Surrogate-assisted neuroevolutionBryson Greenwood, Tyler McDonnell. 1048-1056 [doi]
• Neuroevolution-enhanced multi-objective optimization for mixed-precision quantizationSantiago Miret, Vui Seng Chua, Mattias Marder, Mariano Phiellip, Nilesh Jain, Somdeb Majumdar. 1057-1065 [doi]
• PRE-NAS: predictor-assisted evolutionary neural architecture searchYameng Peng, Andy Song, Vic Ciesielski, Haytham M. Fayek, Xiaojun Chang. 1066-1074 [doi]
• Diversity policy gradient for sample efficient quality-diversity optimizationThomas Pierrot, Valentin Macé, Félix Chalumeau, Arthur Flajolet, Geoffrey Cideron, Karim Beguir, Antoine Cully, Olivier Sigaud, Nicolas Perrin-Gilbert. 1075-1083 [doi]
• RankNEAT: outperforming stochastic gradient search in preference learning tasksKosmas Pinitas, Konstantinos Makantasis, Antonios Liapis, Georgios N. Yannakakis. 1084-1092 [doi]
• Neural architecture search using progressive evolutionNilotpal Sinha, Kuan-Wen Chen. 1093-1101 [doi]
• Approximating gradients for differentiable quality diversity in reinforcement learningBryon Tjanaka, Matthew C. Fontaine, Julian Togelius, Stefanos Nikolaidis. 1102-1111 [doi]
• Dynamics-aware novelty search with behavior repulsionKang Xu, Yan Ma, Wei Li. 1112-1120 [doi]
• Swarm led tomographic reconstructionMohammad Majid al-Rifaie, Tim Blackwell. 1121-1129 [doi]
• Towards explainable real estate valuation via evolutionary algorithmsSebastian Angrick, Ben Bals, Niko Hastrich, Maximilian Kleissl, Jonas Schmidt 0002, Vanja Doskoc, Louise Molitor, Tobias Friedrich 0001, Maximilian Katzmann. 1130-1138 [doi]
• Evolutionary bi-objective optimization for the electric vehicle charging stand infrastructure problemRolando Armas, Hernán E. Aguirre, Daniel Orellana. 1139-1146 [doi]
• Evolving constructions for balanced, highly nonlinear boolean functionsClaude Carlet, Marko Djurasevic, Domagoj Jakobovic, Luca Mariot, Stjepan Picek. 1147-1155 [doi]
• An evolutionary fragment-based approach to molecular fingerprint reconstructionTim Cofala, Oliver Kramer 0001. 1156-1163 [doi]
• Genetic algorithm for qubits initialisation in noisy intermediate-scale quantum machines: the IBM case studyZakaria Abdelmoiz Dahi, Francisco Chicano, Gabriel Luque, Enrique Alba 0001. 1164-1172 [doi]
• Adaptive objective configuration in bi-objective evolutionary optimization for cervical cancer brachytherapy treatment planningLeah R. M. Dickhoff, Ellen M. Kerkhof, Heloisa H. Deuzeman, Carien L. Creutzberg, Tanja Alderliesten, Peter A. N. Bosman. 1173-1181 [doi]
• A multi-objective evolutionary algorithm with new reproduction and decomposition mechanisms for the multi-point dynamic aggregation problemGuanqiang Gao, Bin Xin 0002, Yi Mei 0001, Shengyu Lu, Shuxin Ding. 1182-1190 [doi]
• Defending active directory by combining neural network based dynamic program and evolutionary diversity optimisationDiksha Goel, Max Hector Ward-Graham, Aneta Neumann, Frank Neumann 0001, Hung Nguyen, Mingyu Guo. 1191-1199 [doi]
• EvoIsland: interactive evolution via an island-inspired spatial user interface frameworkAlexander Ivanov 0004, Wesley Willett, Christian Jacob 0001. 1200-1208 [doi]
• RTune: a RocksDB tuning system with deep genetic algorithmHuijun Jin, Jieun Lee, Sanghyun Park. 1209-1217 [doi]
• Environment driven dynamic decomposition for cooperative coevolution of multi-agent systemsLuke Kelly, Martin Masek, Chiou Peng Lam. 1218-1226 [doi]
• Learning the characteristics of engineering optimization problems with applications in automotive crashFu Xing Long, Bas van Stein, Moritz Frenzel, Peter Krause, Markus Gitterle, Thomas Bäck. 1227-1236 [doi]
• Identifying the source of an epidemic using particle swarm optimizationJohn Magee, Viplove Arora, Mario Ventresca. 1237-1244 [doi]
• Bug report summarization using multi-view multi-objective optimization frameworkSantosh Kumar Mishra, Harshavardhan Kundarapu, Sayantan Mitra, Sriparna Saha 0001, Pushpak Bhattacharyya. 1245-1253 [doi]
• Adapting novelty towards generating antigens for antivirus systemsRitwik Murali, C. Shunmuga Velayutham. 1254-1262 [doi]
• Automated algorithm selection for radar network configurationQuentin Renau, Johann Dréo, Alain Peres, Yann Semet, Carola Doerr, Benjamin Doerr. 1263-1271 [doi]
• Effects of imputation strategy on genetic algorithms and neural networks on a binary classification problemEsteban Segarra Martinez, Stephen V. Maldonado, Annie S. Wu, Ryan P. McMahan, Xinliang Liu, Blake Oakley. 1272-1280 [doi]
• Optimising autonomous robot swarm parameters for stable formation designDaniel H. Stolfi, Grégoire Danoy. 1281-1289 [doi]
• Analyzing multi-agent reinforcement learning and coevolution in cybersecurityMatthew J. Turner, Erik Hemberg, Una-May O'Reilly. 1290-1298 [doi]
• Addressing tactic volatility in self-adaptive systems using evolved recurrent neural networks and uncertainty reduction tacticsAizaz Ul Haq, Niranjana Deshpande, AbdElRahman A. ElSaid, Travis Desell, Daniel E. Krutz. 1299-1307 [doi]
• High-performance evolutionary algorithms for online neuron controlBinxu Wang, Carlos R. Ponce. 1308-1316 [doi]
• Is the revisited hypervolume an appropriate quality indicator to evaluate multi-objective test case selection algorithms?Aitor Arrieta. 1317-1326 [doi]
• Multi-objective metamorphic follow-up test case selection for deep learning systemsAitor Arrieta. 1327-1335 [doi]
• Improving source-code representations to enhance search-based software repairPemma Reiter, Antonio M. Espinoza, Adam Doupé, Ruoyu Wang 0001, Westley Weimer, Stephanie Forrest. 1336-1344 [doi]
• Mutation-based test generation for quantum programs with multi-objective searchXinyi Wang, Tongxuan Yu, Paolo Arcaini, Tao Yue 0002, Shaukat Ali 0001. 1345-1353 [doi]
• Monotone improvement of information-geometric optimization algorithms with a surrogate functionYouhei Akimoto. 1354-1362 [doi]
• Analysis of a gray-box operator for vertex coverSamuel Baguley, Tobias Friedrich 0001, Timo Kötzing, Xiaoyue Li, Marcus Pappik, Ziena Zeif. 1363-1371 [doi]
• Fast non-elitist evolutionary algorithms with power-law ranking selectionDuc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre, Xiaoyu Qin. 1372-1380 [doi]
• Simulated annealing is a polynomial-time approximation scheme for the minimum spanning tree problemBenjamin Doerr, Amirhossein Rajabi, Carsten Witt. 1381-1389 [doi]
• Towards a stronger theory for permutation-based evolutionary algorithmsBenjamin Doerr, Yassine Ghannane, Marouane Ibn Brahim. 1390-1398 [doi]
• Crossover for cardinality constrained optimizationTobias Friedrich 0001, Timo Kötzing, Aishwarya Radhakrishnan, Leon Schiller, Martin Schirneck, Georg Tennigkeit, Simon Wietheger. 1399-1407 [doi]
• Runtime analysis of competitive co-evolutionary algorithms for maximin optimisation of a bilinear functionPer Kristian Lehre. 1408-1416 [doi]
• Self-adaptation via multi-objectivisation: a theoretical studyPer Kristian Lehre, Xiaoyu Qin. 1417-1425 [doi]
• The compact genetic algorithm struggles on Cliff functionsFrank Neumann 0001, Dirk Sudholt, Carsten Witt. 1426-1433 [doi]