Abstract is missing.
- Ring cellular encode-decode UMDA: simple is effectiveAnsel Y. Rodríguez González, Samantha Barajas, Ramón Aranda, Yoan Martínez López, Julio Madera Quintana. 1-2 [doi]
- Cooperative co-evolution strategies with time-dependent grouping for optimization problems in smart gridsJunpeng Su, Han Huang 0002, Zhifeng Hao. 3-4 [doi]
- Exact and approximate USCP with branch and boundJanez Radescek, Matjaz Depolli. 5-6 [doi]
- Benchmarking gradient-free optimizers for 3D performance capture in the nevergrad platformAlexandros Doumanoglou, Nikolaos Zioulis, Vladimiros Sterzentsenko, Antonis Karakottas, Dimitrios Zarpalas, Petros Daras. 7-8 [doi]
- Robust benchmarking for multi-objective optimizationTome Eftimov, Peter Korosec. 9-10 [doi]
- SOMA-CLP for competition on bound constrained single objective numerical optimization benchmark: a competition entry on bound constrained single objective numerical optimization at the genetic and evolutionary computation conference (GECCO) 2021Tomas Kadavy, Michal Pluhacek, Adam Viktorin, Roman Senkerik. 11-12 [doi]
- Hospital simulation model optimisation with a random ReLU expansion surrogate modelLaurens Bliek, Arthur Guijt, Rickard Karlsson. 13-14 [doi]
- Surrogate-based optimisation for a hospital simulation scenario using pairwise classifiersPablo S. Naharro, Antonio LaTorre, José María Peña. 15-16 [doi]
- An evolutionary and neighborhood-based algorithm for optimization under low budget requirementsJordi Pereira. 17-18 [doi]
- Linear regression strategy for differential evolutionJosé L. Sainz-Pardo. 19-20 [doi]
- Do quality indicators prefer particular multi-objective search algorithms in search-based software engineering?: (hot off the press track at GECCO 2021)Shaukat Ali 0001, Paolo Arcaini, Tao Yue 0002. 21-22 [doi]
- Runtime analysis via symmetry arguments: (hot-off-the-press track at GECCO 2021)Benjamin Doerr. 23-24 [doi]
- Theoretical analyses of multi-objective evolutionary algorithms on multi-modal objectives: (hot-off-the-press track at GECCO 2021)Benjamin Doerr, Weijie Zheng 0001. 25-26 [doi]
- Reducing bias in multi-objective optimization benchmarkingTome Eftimov, Peter Korosec. 27-28 [doi]
- Optimal recombination and adaptive restarts improve GA performance on the asymmetric TSPAnton V. Eremeev, Yulia V. Kovalenko. 29-30 [doi]
- Genetic improvement of data for maths functionsWilliam B. Langdon, Oliver Krauss. 31-32 [doi]
- Achieving weight coverage for an autonomous driving system with search-based test generation (HOP track at GECCO 2021)Thomas Laurent 0003, Paolo Arcaini, Fuyuki Ishikawa, Anthony Ventresque. 33-34 [doi]
- Genetic improvement of routing in delay tolerant networksMichela Lorandi, Leonardo Lucio Custode, Giovanni Iacca. 35-36 [doi]
- Interactive parameter tuning of bi-objective optimisation algorithms using the empirical attainment functionManuel López-Ibáñez 0001, Juan Esteban Diaz. 37-38 [doi]
- The influence of uncertainties on optimization of vaccinations on a network of animal movementsKrzysztof Michalak, Mario Giacobini. 39-40 [doi]
- Multi-objective parameter-less population pyramid in solving the real-world and theoretical problemsMichal Witold Przewozniczek, Piotr Dziurzanski, Shuai Zhao 0004, Leandro Soares Indrusiak. 41-42 [doi]
- On sampling error in evolutionary algorithmsDirk Schweim, David Wittenberg, Franz Rothlauf. 43-44 [doi]
- Improving assertion oracles with evolutionary computationValerio Terragni, Gunel Jahangirova, Mauro Pezzè, Paolo Tonella. 45-46 [doi]
- Analysis of evolutionary algorithms on fitness function with time-linkage property (hot-off-the-press track at GECCO 2021)Weijie Zheng 0001, Huanhuan Chen, Xin Yao 0001. 47-48 [doi]
- An improved predictor of daily stock index based on a genetic filterDong-Hee Cho, Seung-Hyun Moon, Yong-Hyuk Kim. 49-50 [doi]
- Algorithm selection using transfer learningNiranjana Deshpande, Naveen Sharma. 51-52 [doi]
- A software library for archiving nondominated pointsDuarte M. Dias, Alexandre D. Jesus, Luís Paquete. 53-54 [doi]
- An interactive tool for enhancing hospital capacity predictions using an epidemiological modelF. Gibson, R. Fabbro, A. Rahat, Thomas Torsney-Weir, Daniel Archambault, M. Gravenor, B. Lucini. 55-56 [doi]
- A new hybrid evolutionary algorithm for dial-a-ride problemsSonia Nasri, Hend Bouziri, Wassila Aggoune-Mtalaa. 57-58 [doi]
- Generative design of microfluidic channel geometry using evolutionary approachNikolay O. Nikitin, Alexander Hvatov, Iana S. Polonskaia, Anna V. Kalyuzhnaya, Georgii V. Grigorev, Xiaohao Wang, Xiang Qian. 59-60 [doi]
- Rapid prototyping of evolution-driven biclustering methods in JuliaPawel Renc, Patryk Orzechowski, Aleksander Byrski, Jaroslaw Was, Jason H. Moore. 61-62 [doi]
- k-Pareto optimality for many-objective genetic optimizationJean Ruppert, Marharyta Aleksandrova, Thomas Engel 0001. 63-64 [doi]
- Winner prediction for real-time strategy games through feature selection based on a genetic wrapperSeung Soo Shin, Yong-Hyuk Kim. 65-66 [doi]
- Novelty particle swarm optimisation for truss optimisation problemsHirad Assimi, Frank Neumann 0001, Markus Wagner 0007, Xiaodong Li. 67-68 [doi]
- Partial-ACO as a GA mutation operator applied to TSP instancesDarren M. Chitty. 69-70 [doi]
- On detecting the novelties in metaphor-based algorithmsIztok Fister Jr., Iztok Fister 0001, Andrés Iglesias 0001, Akemi Gálvez. 71-72 [doi]
- Evolved response thresholds generalize across problem instances for a deterministic-response multiagent systemH. David Mathias, Annie S. Wu, Daniel Dang. 73-74 [doi]
- Ant colony optimization for energy-efficient train operationsFederico Naldini, Paola Pellegrini, Joaquin Rodriguez. 75-76 [doi]
- Learning assignment order in an ant colony optimiser for the university course timetabling problemJames Sakal, Jonathan E. Fieldsend, Edward C. Keedwell. 77-78 [doi]
- Ant swarm algorithm for self-organizing complex systemJuntao Zhang, Peng Cheng. 79-80 [doi]
- Predicting soft robot's locomotion fitnessRenata B. Biazzi, André Fujita, Daniel Y. Takahashi. 81-82 [doi]
- On the use of feature-maps for improved quality-diversity meta-evolutionDavid M. Bossens, Danesh Tarapore. 83-84 [doi]
- Promoting reproductive isolation through diversity in on-line collective roboticsAmine M. Boumaza. 85-86 [doi]
- Younger is better: a simple and efficient selection strategy for MAP-ElitesAlexandre Coninx, Stéphane Doncieux. 87-88 [doi]
- Ad hoc teaming through evolutionJoshua Cook, Kagan Tumer. 89-90 [doi]
- The impact of different tasks on evolved robot morphologiesMatteo De Carlo, Eliseo Ferrante, Jacintha Ellers, Gerben Meynen, A. E. Eiben. 91-92 [doi]
- Comparing lifetime learning methods for morphologically evolving robotsFuda van Diggelen, Eliseo Ferrante, A. E. Eiben. 93-94 [doi]
- Heterogeneous agent coordination via adaptive quality diversity and specializationGaurav Dixit, Charles Koll, Kagan Tumer. 95-96 [doi]
- Reinforcement learning with rare significant events: direct policy search vs. gradient policy searchPaul Ecoffet, Nicolas Fontbonne, Jean-Baptiste André, Nicolas Bredèche. 97-98 [doi]
- Automatic exploration of the property space of reservoirsMika Ito, Leo Cazenille, Nathanaël Aubert-Kato. 99-100 [doi]
- Examining forms of inductive bias towards 'simplicity' in genetic algorithms to enhance evolvability of boolean functionsHetvi Jethwani, Sumeet Agarwal. 101-102 [doi]
- Designing fitness functions for odour source localisationJoão Macedo, Lino Marques, Ernesto Costa. 103-104 [doi]
- How to evolve a neuronW. Garrett Michener. 105-106 [doi]
- Environmental impact on evolving language diversityGregory Furman, Geoff Nitschke. 107-108 [doi]
- Impact of energy efficiency on the morphology and behaviour of evolved robotsMargarita Rebolledo, Daan Zeeuwe, Thomas Bartz-Beielstein, A. E. Eiben. 109-110 [doi]
- Illuminating the space of beatable lode runner levels produced by various generative adversarial networksKirby Steckel, Jacob Schrum. 111-112 [doi]
- Growing simulated robots with environmental feedback: an eco-evo-devo approachKathryn Walker, Helmut Hauser, Sebastian Risi. 113-114 [doi]
- Pathogen dose based natural killer cell algorithm for classificationDongmei Wang, Yiwen Liang, Chengyu Tan, Hongbin Dong, Xinmin Yang. 115-116 [doi]
- Optimizing a GPU-accelerated genetic algorithm for the vehicle routing problemMarwan F. Abdelatti, Abdeltawab Hendawi, Manbir Sodhi. 117-118 [doi]
- Linear representation of categorical valuesArnaud Berny. 119-120 [doi]
- Effective recombination operators for the family of vehicle routing problemsPiotr Cybula, Marek Rogalski, Piotr Sielski, Andrzej Jaszkiewicz, Przemyslaw Pelka. 121-122 [doi]
- Introducing a hash function for the travelling salesman problem for differentiating solutionsMehdi El Krari, Rym Nesrine Guibadj, John Woodward, Denis Robilliard. 123-124 [doi]
- Automated configuration of parallel machine dispatching rules by machine learningGeorg Faustmann, Christoph Mrkvicka, Nysret Musliu, Felix Winter. 125-126 [doi]
- Selecting between evolutionary and classical algorithms for the CVRP using machine learning: optimization of vehicle routing problemsJustin Fellers, José Quevedo, Marwan Abdelatti, Meghan Steinhaus, Manbir Sodhi. 127-128 [doi]
- The optimal filtering set problem with application to surrogate evaluation in genetic programmingFrancisco J. Gil-Gala, María R. Sierra, Carlos Mencía, Ramiro Varela. 129-130 [doi]
- Optimisation algorithms for parallel machine scheduling problems with setup timesFabian Kittel, Jannik Enenkel, Michael Guckert, Jana Holznigenkemper, Neil Urquhart. 131-132 [doi]
- Stochastic local search for efficient hybrid feature selectionOle Jakob Mengshoel, Tong Yu 0001, Jon Riege, Eirik Flogard. 133-134 [doi]
- A grouping genetic algorithm for the unrelated parallel-machine scheduling problemOctavio Ramos-Figueroa, Marcela Quiroz-Castellanos. 135-136 [doi]
- Error function learning with interpretable compositional networks for constraint-based local searchFlorian Richoux, Jean-François Baffier. 137-138 [doi]
- A hybrid local search framework for the dynamic capacitated arc routing problemHao Tong, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao 0001. 139-140 [doi]
- Continuous encoding for community detection in complex networksWei Zheng, Yiqing Zhang, Jianyong Sun. 141-142 [doi]
- Detecting anomalies in spacecraft telemetry using evolutionary thresholding and LSTMsPawel Benecki, Szymon Piechaczek, Daniel Kostrzewa, Jakub Nalepa. 143-144 [doi]
- Improved evolution of generative adversarial networksVictor Costa, Nuno Lourenço 0002, João Correia, Penousal Machado. 145-146 [doi]
- Sparsity-based evolutionary multi-objective feature selection for multi-label classificationKaan Demir, Bach Hoai Nguyen, Bing Xue 0001, Mengjie Zhang 0001. 147-148 [doi]
- Scatter search for high-dimensional feature selection using feature groupingMiguel García Torres, Francisco Gómez-Vela, Federico Divina, Diego P. Pinto-Roa, José Luis Vázquez Noguera, Julio César Mello Román. 149-150 [doi]
- Meta-learning for symbolic hyperparameter defaultsPieter Gijsbers, Florian Pfisterer, Jan N. van Rijn, Bernd Bischl, Joaquin Vanschoren. 151-152 [doi]
- Evo-RL: evolutionary-driven reinforcement learningAhmed Hallawa, Thorsten Born, Anke Schmeink, Guido Dartmann, Arne Peine, Lukas Martin, Giovanni Iacca, A. E. Eiben, Gerd Ascheid. 153-154 [doi]
- Understanding evolutionary induction of decision trees: a multi-tree repository approachKrzysztof Jurczuk, Marcin Czajkowski, Marek Kretowski. 155-156 [doi]
- Growth and harvest induce essential dynamics in neural networksIlona M. Kulikovskikh, Tarzan Legovic. 157-158 [doi]
- Permutation-based optimization using a generative adversarial networkSami Lemtenneche, Abdelhakim Cheriet, Bensayah Abdellah. 159-160 [doi]
- EvolMusic: towards musical adversarial examples for black-box attacks on speech-to-textMariele Motta, Tanja Hagemann, Sebastian Fischer, Felix Assion. 161-162 [doi]
- Explainability and performance of anticipatory learning classifier systems in non-deterministic environmentsRomain Orhand, Anne Jeannin-Girardon, Pierre Parrend, Pierre Collet. 163-164 [doi]
- Multi-objective genetic programming for symbolic regression with the adaptive weighted splines representationChristian Raymond, Qi Chen 0002, Bing Xue 0001, Mengjie Zhang 0001. 165-166 [doi]
- An evolutionary approach to interpretable learningJake Robertson, Ting Hu. 167-168 [doi]
- Misclassification detection based on conditional VAE for rule evolution in learning classifier systemHiroki Shiraishi, Masakazu Tadokoro, Yohei Hayamizu, Yukiko Fukumoto, Hiroyuki Sato, Keiki Takadama. 169-170 [doi]
- Adopting lexicase selection for michigan-style learning classifier systems with continuous-valued inputsAlexander R. M. Wagner, Anthony Stein. 171-172 [doi]
- Evolving local interpretable model-agnostic explanations for deep neural networks in image classificationBin Wang 0001, WenBin Pei, Bing Xue 0001, Mengjie Zhang 0001. 173-174 [doi]
- Adaptive multi-fitness learning for robust coordinationConnor Yates, Ayhan Alp Aydeniz, Kagan Tumer. 175-176 [doi]
- MOMPA: a high performance multi-objective optimizer based on marine predator algorithmLong Chen, Xuebing Cai, Kezhong Jin, Zhenzhou Tang. 177-178 [doi]
- The effect of offspring population size on NSGA-II: a preliminary studyMax Hort, Federica Sarro. 179-180 [doi]
- Dynamic adaptation of decomposition vector set size for MOEA/DYuta Kobayashi, Claus Aranha, Tetsuya Sakurai. 181-182 [doi]
- Multi-criteria differential evolution: treating multitask optimization as multi-criteria optimizationJian-Yu Li, Ke-Jing Du, Zhi-hui Zhan, Hua Wang, Jun Zhang 0003. 183-184 [doi]
- An approximate MIP-DoM calculation for multi-objective optimization using affinity propagation clustering algorithmClaudio Lucio do Val Lopes, Flávio V. C. Martins, Elizabeth F. Wanner, Kalyanmoy Deb. 185-186 [doi]
- Generating multi-objective bilevel optimization problems with multiple non-cooperative followersJesús-Adolfo Mejía-de-Dios, Efrén Mezura-Montes. 187-188 [doi]
- 3)Sumit Mishra, Ved Prakash, Maxim Buzdalov. 189-190 [doi]
- A niching framework based on fitness proportionate sharing for multi-objective genetic algorithm (MOGA-FPS)Abdul-Rauf Nuhu, Xuyang Yan, Daniel Opoku, Abdollah Homaifar. 191-192 [doi]
- Landmark-based multi-objective route planning for large-scale road netJiaze Sun, Nan Han, Jianbin Huang, Jiahui Deng. 193-194 [doi]
- One step preference elicitation in multi-objective Bayesian optimizationJuan Ungredda, Jürgen Branke, Mariapia Marchi, Teresa Montrone. 195-196 [doi]
- Two comprehensive performance metrics for overcoming the deficiencies of IGD and HVLiping Wang, Lin Zhang, Yu Ren, Qicang Qiu, Feiyue Qiu. 197-198 [doi]
- Estimation of von mises-fisher distribution algorithm, with application to support vector classificationAdetunji David Ajimakin, V. Susheela Devi. 199-200 [doi]
- Reinforcement learning for dynamic optimization problemsAbdennour Boulesnane, Souham Meshoul. 201-202 [doi]
- An empirical study of cooperative frequency in distributed cooperative co-evolutionLing-Yu Li, Wen-Jie Ou, Xiao-Min Hu, Wei-neng Chen, An Song. 203-204 [doi]
- Disease outbreaks: tuning predictive machine learningTassallah Abdullahi, Geoff Nitschke. 205-206 [doi]
- Setup of fuzzy hybrid particle swarms: a heuristic approachNicolas Roy 0003, Charlotte Beauthier, Timotéo Carletti, Alexandre Mayer. 207-208 [doi]
- CMA-ES with coordinate selection for high-dimensional and ill-conditioned functionsHiroki Shimizu, Masashi Toyoda. 209-210 [doi]
- Bridging kriging believer and expected improvement using bump hunting for expensive black-box optimizationBing Wang, Hemant Kumar Singh, Tapabrata Ray. 211-212 [doi]
- Automated feature detection of black-box continuous search-landscapes using neural image recognitionBoris Yazmir, Ofer M. Shir. 213-214 [doi]
- A complementarity analysis of the COCO benchmark problems and artificially generated problemsUrban Skvorc, Tome Eftimov, Peter Korosec. 215-216 [doi]
- Three population co-evolution for generating mechanics of endless runner gamesVojtech Cerný, Jakub Gemrot. 217-218 [doi]
- Quantum genetic selection: using a quantum computer to select individuals in genetic algorithmsGiovanni Acampora, Roberto Schiattarella, Autilia Vitiello. 219-220 [doi]
- Fitness value curves prediction in the evolutionary process of genetic algorithmsRenuá Meireles Almeida, Denys Menfredy Ferreira Ribeiro, Rodrigo Moraes Rodrigues, Otávio Noura Teixeira. 221-222 [doi]
- A genetic algorithm approach to compute mixed strategy solutions for general Stackelberg gamesSrivathsa Gottipati, Praveen Paruchuri. 223-224 [doi]
- ALF: a fitness-based artificial life form for evolving large-scale neural networksRune Krauss, Marcel Merten, Mirco Bockholt, Rolf Drechsler. 225-226 [doi]
- Optimization of multi-objective mixed-integer problems with a model-based evolutionary algorithm in a black-box settingKrzysztof L. Sadowski, Dirk Thierens, Peter A. N. Bosman. 227-228 [doi]
- A benchmark generator of tree decomposition Mk landscapesDirk Thierens, Tobias van Driessel. 229-230 [doi]
- It's the journey not the destination: building genetic algorithms practitioners can trustJakub Vincalek, Sean Walton, Ben Evans. 231-232 [doi]
- A crossover that matches diverse parents together in evolutionary algorithmsMaciej Swiechowski. 233-234 [doi]
- A multimethod approach to multimodal function optimizationFredrik Foss, Ole Jakob Mengshoel. 235-236 [doi]
- Elo-based similar-strength opponent sampling for multiobjective competitive coevolutionSean N. Harris, Daniel R. Tauritz. 237-238 [doi]
- OPTION: optimization algorithm benchmarking ontologyAna Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov. 239-240 [doi]
- Learning multiple defaults for machine learning algorithmsFlorian Pfisterer, Jan N. van Rijn, Philipp Probst, Andreas C. Müller, Bernd Bischl. 241-242 [doi]
- The factory must grow: automation in FactorioKenneth N. Reid, Iliya Miralavy, Stephen Kelly, Wolfgang Banzhaf, Cedric Gondro. 243-244 [doi]
- Leveraging benchmarking data for informed one-shot dynamic algorithm selectionFurong Ye, Carola Doerr, Thomas Bäck. 245-246 [doi]
- Empirical study of correlations in the fitness landscapes of combinatorial optimization problemsLongfei Zhang, Ke Li, Shi Gu. 247-248 [doi]
- Genetic programming with a new representation and a new mutation operator for image classificationQinglan Fan, Ying Bi, Bing Xue 0001, Mengjie Zhang 0001. 249-250 [doi]
- Empirical analysis of variance for genetic programming based symbolic regressionLukas Kammerer, Gabriel Kronberger, Stephan M. Winkler. 251-252 [doi]
- Fitness first and fatherless crossoverWilliam B. Langdon. 253-254 [doi]
- "Re-ID BUFF": an enhanced similarity measurement based on genetic programming for person re-identificationYiming Li, Lin Shang. 255-256 [doi]
- Linear-dependent multi-interpretation neuro-encoded expression programmingJun Ma, Fenghui Gao, Shuangrong Liu, Lin Wang. 257-258 [doi]
- Principled quality diversity for ensemble classifiers using MAP-ElitesKyle L. Nickerson, Ting Hu. 259-260 [doi]
- Improving estimation of distribution genetic programming with novelty initializationChristian Olmscheid, David Wittenberg, Dominik Sobania, Franz Rothlauf. 261-262 [doi]
- GLEAM: genetic learning by extraction and absorption of modulesAnil Kumar Saini, Lee Spector. 263-264 [doi]
- Improving the generalisation of genetic programming models with evaluation time and asynchronous parallel computingAliyu Sani Sambo, R. Muhammad Atif Azad, Yevgeniya Kovalchuk, Vivek Padmanaabhan Indramohan, Hanifa Shah. 265-266 [doi]
- Neurally guided transfer learning for genetic programmingAlexander Wild, Barry Porter. 267-268 [doi]
- Adversarial bandit gene expression programming for symbolic regressionCongwen Xu, Qiang Lu, Jake Luo, Zhiguang Wang. 269-270 [doi]
- Evolving reservoir weights in the frequency domainSebastián Basterrech, Gerardo Rubino. 271-272 [doi]
- Evolving transformer architecture for neural machine translationBen Feng, Dayiheng Liu, Yanan Sun. 273-274 [doi]
- Growth and evolution of deep neural networks from gene regulatory networksColin Flynn, Mohammed Bennamoun, Farid Boussaïd. 275-276 [doi]
- A NEAT-based multiclass classification method with class binarizationZhenyu Gao, Gongjin Lan. 277-278 [doi]
- On the exploitation of neuroevolutionary informationUnai Garciarena, Nuno Lourenço 0002, Penousal Machado, Roberto Santana, Alexander Mendiburu. 279-280 [doi]
- Modeling the evolution of retina neural networkZiyi Gong, Paul Munro. 281-282 [doi]
- A coevolutionary approach to deep multi-agent reinforcement learningDaan Klijn, A. E. Eiben. 283-284 [doi]
- Evolving neuronal plasticity rules using cartesian genetic programmingHenrik D. Mettler, Maximilian Schmidt, Walter Senn, Mihai A. Petrovici, Jakob Jordan. 285-286 [doi]
- A transfer learning based evolutionary deep learning framework to evolve convolutional neural networksBin Wang, Bing Xue, Mengjie Zhang 0001. 287-288 [doi]
- Neuroevolution of a recurrent neural network for spatial and working memory in a simulated robotic environmentXinyun Zou, Eric O. Scott, Alexander B. Johnson, Kexin Chen, Douglas A. Nitz, Kenneth A. De Jong, Jeffrey L. Krichmar. 289-290 [doi]
- Selecting miners within blockchain-based systems using evolutionary algorithms for energy optimisationAkram Alofi, Mahmoud A. Bokhari, Robert Hendley, Rami Bahsoon. 291-292 [doi]
- Resource planning for hospitals under special consideration of the COVID-19 pandemic: optimization and sensitivity analysisThomas Bartz-Beielstein, Marcel Dröscher, Alpar Gür, Alexander Hinterleitner, Olaf Mersmann, Dessislava Peeva, Lennard Reese, Nicolas Rehbach, Frederik Rehbach, A. Sen, Aleksandr Subbotin, Martin Zaefferer. 293-294 [doi]
- Risk aware optimization of water sensor placementAntonio Candelieri, Andrea Ponti, Francesco Archetti. 295-296 [doi]
- Distributed evolutionary design of HIFU treatment plansJakub Chlebik, Jirí Jaros. 297-298 [doi]
- An optimal oil skimmer assignment based on a genetic algorithm with minimal mobilized locationsDong-Hee Cho, Yong-Hyuk Kim. 299-300 [doi]
- Diagnosing autonomous vehicle driving criteria with an adversarial evolutionary algorithmMark A. Coletti, Shang Gao, Spencer Paulissen, Nicholas Quentin Haas, Robert Patton. 301-302 [doi]
- Optimizing the parameters of a physical exercise dose-response model: an algorithmic comparisonMark Connor, Michael O'Neill 0001. 303-304 [doi]
- Dealing with a problematic roundabout by optimizing a traffic light system through evolutionary computationFrancisco Cruz-Zelante, Eduardo Segredo, Gara Miranda. 305-306 [doi]
- Weighted ensemble of gross error detection methods based on particle swarm optimizationDaniel Dobos, Tien Thanh Nguyen, John A. W. McCall, Allan Wilson, Phil Stockton, Helen Corbett. 307-308 [doi]
- Wastewater systems planned maintenance scheduling using multi-objective optimisationSabrina Draude, Edward C. Keedwell, Zoran Kapelan, Rebecca Hiscock. 309-310 [doi]
- Evolving potential field parameters for deploying UAV-based two-hop wireless mesh networksRahul Dubey, Sushil J. Louis. 311-312 [doi]
- ARCH-Elites: quality-diversity for urban designTheodoros Galanos, Antonios Liapis, Georgios N. Yannakakis, Reinhard Koenig. 313-314 [doi]
- Optimising the introduction of connected and autonomous vehicles in a public transport system using macro-level mobility simulations and evolutionary algorithmsKate Han, Lee A. Christie, Alexandru-Ciprian Zavoianu, John McCall 0001. 315-316 [doi]
- Structural damage identification under non-linear EOV effects using genetic programmingMohsen Mousavi, Amir H. Gandomi, Magd Abdel Wahab. 317-318 [doi]
- Towards higher order fairness functionals for smooth path planningVictor Parque. 319-320 [doi]
- Novelty search for evolving interesting character mechanics for a two-player video gameEirik Høgdahl Skjærseth, Harald Vinje, Ole Jakob Mengshoel. 321-322 [doi]
- Optimising pheromone communication in a UAV swarmDaniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, Pascal Bouvry. 323-324 [doi]
- A new pathway to approximate energy expenditure and recovery of an athleteFabian Clemens Weigend, Jason Siegler, Oliver Obst. 325-326 [doi]
- Unit-aware multi-objective genetic programming for the prediction of the stokes flow around a sphereHeiner Zille, Sanaz Mostaghim, Fabien Evrard, Berend G. M. van Wachem. 327-328 [doi]
- Neurogenetic programming framework for explainable reinforcement learningVadim Liventsev, Aki Härmä, Milan Petkovic. 329-330 [doi]
- Using knowledge of human-generated code to bias the search in program synthesis with grammatical evolutionDirk Schweim, Erik Hemberg, Dominik Sobania, Una-May O'Reilly, Franz Rothlauf. 331-332 [doi]
- On the effectiveness of restarting local searchAldeida Aleti, Mark Wallace 0001, Markus Wagner 0007. 333-334 [doi]
- Affine OneMaxArnaud Berny. 335-336 [doi]
- Time complexity analysis of the deductive sort in the best caseSumit Mishra, Ved Prakash. 337-338 [doi]
- Benchmarking: state-of-the-art and beyondAnne Auger, Nikolaus Hansen. 339-340 [doi]
- Recent advances in particle swarm optimization analysis and understanding 2021Andries P. Engelbrecht, Christopher W. Cleghorn. 341-368 [doi]
- A gentle introduction to theory (for non-theoreticians)Benjamin Doerr. 369-398 [doi]
- Runtime analysis of evolutionary algorithms: basic introductionPer Kristian Lehre, Pietro S. Oliveto. 399-425 [doi]
- Evolution of neural networksRisto Miikkulainen. 426-442 [doi]
- Genetic programming: a tutorial introductionUna-May O'Reilly, Erik Hemberg. 443-453 [doi]
- Replicability and reproducibility in evolutionary optimizationLuís Paquete, Manuel López-Ibáñez 0001. 454-462 [doi]
- Representations for evolutionary algorithmsFranz Rothlauf. 463-483 [doi]
- Introductory mathematical programming for ECOfer M. Shir. 484-497 [doi]
- Learning classifier systems: from principles to modern systemsAnthony Stein, Masaya Nakata. 498-527 [doi]
- Hyper-heuristics tutorialDaniel R. Tauritz, John R. Woodward. 528-557 [doi]
- Model-based evolutionary algorithmsDirk Thierens, Peter A. N. Bosman. 558-587 [doi]
- Theoretical foundations of evolutionary computation for beginners and veteransDarrell Whitley. 588-635 [doi]
- CMA-ES and advanced adaptation mechanismsYouhei Akimoto, Nikolaus Hansen. 636-663 [doi]
- Benchmarking multiobjective optimizers 2.0Dimo Brockhoff, Tea Tusar. 664-668 [doi]
- Advanced Learning Classifier SystemsProf Will Browne. 669-691 [doi]
- Constraint-handling techniques used with evolutionary algorithmsCarlos A. Coello Coello. 692-714 [doi]
- Quality-diversity optimisationAntoine Cully, Jean-Baptiste Mouret, Stéphane Doncieux. 715-739 [doi]
- Evolutionary multi- and many-objective optimization: methodologies, applications and demonstrationKalyanmoy Deb, Julian Blank. 740-769 [doi]
- Statistical analyses for meta-heuristic stochastic optimization algorithmsTome Eftimov, Peter Korosec. 770-785 [doi]
- Genetic improvement: taking real-world source code and improving it using genetic programmingSæmundur Óskar Haraldsson, Alexander E. I. Brownlee, John R. Woodward, Markus Wagner 0007, Bradley Alexander. 786-817 [doi]
- Dynamic multi-objective optimization: introduction, challenges, applications and future directionsMardé Helbig. 818-838 [doi]
- Lexicase SelectionThomas Helmuth, William G. La Cava. 839-855 [doi]
- Runtime analysis of population-based evolutionary algorithmsPer Kristian Lehre, Pietro S. Oliveto. 856-880 [doi]
- Decomposition multi-objective optimisation: current developments and future opportunitiesKe Li 0001, Qingfu Zhang 0001. 881-898 [doi]
- Recent advances in landscape analysis for optimisation and learningKatherine Malan, Gabriela Ochoa. 899-917 [doi]
- Evolutionary submodular optimisationAneta Neumann, Frank Neumann 0001, Chao Qian 0001. 918-940 [doi]
- Sequential experimentation by evolutionary algorithmsOfer M. Shir, Thomas Bäck. 941-958 [doi]
- Automated algorithm configuration and designThomas Stützle, Manuel López-Ibáñez 0001. 959-982 [doi]
- Coevolutionary computation for adversarial deep learningJamal Toutouh, Una-May O'Reilly. 983-1001 [doi]
- Evolutionary art and design: representation, fitness and interactionPenousal Machado. 1002-1031 [doi]
- Search based software engineering: challenges, opportunities and recent applicationsAli Ouni 0001, Mohamed Wiem Mkaouer. 1032-1063 [doi]
- Applications of dynamic parameter control in evolutionary computationGregor Papa. 1064-1088 [doi]
- Evolutionary computation and machine learning in cryptologyStjepan Picek, Domagoj Jakobovic. 1089-1118 [doi]
- PushLee Spector. 1119-1134 [doi]
- Towards a green AI: evolutionary solutions for an ecologically viable artificial intelligenceNayat Sánchez Pi, Luis Martí. 1135-1140 [doi]
- Evolutionary computation for feature selection and feature constructionBing Xue, Mengjie Zhang 0001. 1141-1168 [doi]
- Evolutionary computation and evolutionary deep learning for image analysis, signal processing and pattern recognitionMengjie Zhang 0001, Stefano Cagnoni. 1169-1198 [doi]
- Quantifying the impact of boundary constraint handling methods on differential evolutionRick Boks, Anna V. Kononova, Hao Wang 0025. 1199-1207 [doi]
- On the genotype compression and expansion for evolutionary algorithms in the continuous domainLucija Planinic, Marko Djurasevic, Luca Mariot, Domagoj Jakobovic, Stjepan Picek, Carlos A. Coello Coello. 1208-1216 [doi]
- Design of large-scale metaheuristic component studiesHelena Stegherr, Michael Heider, Leopold Luley, Jörg Hähner. 1217-1226 [doi]
- Benchmark generator for TD Mk landscapesTobias van Driessel, Dirk Thierens. 1227-1233 [doi]
- Emergence of structural bias in differential evolutionBas van Stein, Fabio Caraffini, Anna V. Kononova. 1234-1242 [doi]
- Is there anisotropy in structural bias?Diederick Vermetten, Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck. 1243-1250 [doi]
- DMS and MultiGLODS: black-box optimization benchmarking of two direct search methods on the bbob-biobj test suiteDimo Brockhoff, Baptiste Plaquevent-Jourdain, Anne Auger, Nikolaus Hansen. 1251-1258 [doi]
- Benchmarking SHADE algorithm enhanced with model based optimization on the BBOB noiseless testbedMichal Okulewicz, Mateusz Zaborski. 1259-1266 [doi]
- An abstract interface for large-scale continuous optimization decomposition methodsRodolfo Ayala Lopes, Rodrigo C. P. Silva, Alan R. R. de Freitas. 1267-1274 [doi]
- The bee-benders hybrid algorithm with application to transmission expansion planningCameron A. G. MacRae, Melih Ozlen, Andreas T. Ernst. 1275-1282 [doi]
- Population-based coordinate descent algorithm with majority votingDavood Zaman Farsa, Azam Asilian Bidgoli, Ehsan Rokhsat-Yazdi, Shahryar Rahnamayan. 1283-1289 [doi]
- An efficient fault-tolerant communication algorithm for population-based metaheuristicsAmanda Sabatini Dufek, Douglas Adriano Augusto, Helio J. C. Barbosa, Pedro L. S. Dias, Jack R. Deslippe. 1290-1298 [doi]
- Improving the scalability of distributed neuroevolution using modular congruence class generated innovation numbersJoshua Karns, Travis Desell. 1299-1307 [doi]
- Generating combinations on the GPU and its application to the k-subset sumVictor Parque. 1308-1316 [doi]
- X-Aevol: GPU implementation of an evolutionary experimentation simulatorLaurent Turpin, Thierry Gautier, Jonathan Rouzaud-Cornabas. 1317-1325 [doi]
- Maximising hypervolume and minimising ϵ-indicators using Bayesian optimisation over setsTinkle Chugh, Manuel López-Ibáñez 0001. 1326-1334 [doi]
- RARE: evolutionary feature engineering for rare-variant bin discoverySatvik Dasariraju, Ryan J. Urbanowicz. 1335-1343 [doi]
- A new acquisition function for robust Bayesian optimization of unconstrained problemsSibghat Ullah, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck. 1344-1345 [doi]
- A divide and conquer approach for web services location allocation problemHarshal Tupsamudre, Saket Saurabh 0003, Arun Ramamurthy, Mangesh S. Gharote, Sachin Lodha. 1346-1354 [doi]
- Model learning with personalized interpretability estimation (ML-PIE)Marco Virgolin, Andrea De Lorenzo, Francesca Randone, Eric Medvet, Mattias Wahde. 1355-1364 [doi]
- Towards large scale automated algorithm design by integrating modular benchmarking frameworksAmine Aziz-Alaoui, Carola Doerr, Johann Dréo. 1365-1374 [doi]
- Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modulesJacob de Nobel, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck. 1375-1384 [doi]
- Automated design of accurate and robust image classifiers with brain programmingGerardo Ibarra-Vázquez, Gustavo Olague, Cesar Puente 0001, Mariana Chan-Ley, Carlos Soubervielle-Montalvo. 1385-1393 [doi]
- A selection hyperheuristic guided by Thompson sampling for numerical optimizationMarcella Scoczynski Ribeiro Martins, Diego Oliva, Erick Rodríguez-Esparza, Myriam Regattieri Delgado, Ricardo Lüders, Mohamed El Yafrani, Luiz Ledo, Mohamed E. Abd Elaziz, Marco Peréz-Cisnero. 1394-1402 [doi]
- Which hyperparameters to optimise?: an investigation of evolutionary hyperparameter optimisation in graph neural network for molecular property predictionYingfang Yuan, Wenjun Wang, Wei Pang. 1403-1404 [doi]
- Towards the landscape rotation as a perturbation strategy on the quadratic assignment problemJoan Alza, Mark Bartlett, Josu Ceberio, John A. W. McCall. 1405-1413 [doi]
- On the symmetry of the quadratic assignment problem through elementary landscape decompositionXabier Benavides, Josu Ceberio, Leticia Hernando. 1414-1422 [doi]
- Generating instances with performance differences for more than just two algorithmsJakob Bossek, Markus Wagner 0007. 1423-1432 [doi]
- Exploratory analysis of the Monte Carlo tree search for solving the linear ordering problemAndoni I. Garmendia, Josu Ceberio, Alexander Mendiburu. 1433-1441 [doi]
- Hybrid linkage learning for permutation optimization with Gene-pool optimal mixing evolutionary algorithmsMichal Witold Przewozniczek, Marcin M. Komarnicki, Peter A. N. Bosman, Dirk Thierens, Bartosz Frej, Ngoc Hoang Luong. 1442-1450 [doi]
- An empirical evaluation of permutation-based policies for stochastic RCPSPOlivier Regnier-Coudert, Guillaume Povéda. 1451-1458 [doi]
- Solving job shop scheduling problems without using a bias for good solutionsThomas Weise 0001, Xinlu Li, Yan Chen, Zhize Wu. 1459-1466 [doi]
- Graph-aware evolutionary algorithms for influence maximizationKateryna Konotopska, Giovanni Iacca. 1467-1475 [doi]
- Focusing on the hybrid quantum computing - Tabu search algorithm: new results on the Asymmetric Salesman ProblemEneko Osaba, Esther Villar-Rodriguez, Izaskun Oregi, Aitor Moreno-Fernandez-de-Leceta. 1476-1482 [doi]
- Novelty and MCTSHendrik Baier, Michael Kaisers. 1483-1487 [doi]
- Using deep Q-network for selection hyper-heuristicsAugusto Lopez Dantas, Alexander Fiabane do Rego, Aurora T. R. Pozo. 1488-1492 [doi]
- Coordinate ascent MORE with adaptive entropy control for population-based regret minimizationMaximilian Hüttenrauch, Gerhard Neumann. 1493-1497 [doi]
- On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation schemeLéni K. Le Goff, Emma Hart. 1498-1502 [doi]
- Using reinforcement learning for tuning genetic algorithmsJosé Quevedo, Marwan Abdelatti, Farhad Imani, Manbir Sodhi. 1503-1507 [doi]
- Evolutionary reinforcement learning for sparse rewardsShibei Zhu, Francesco Belardinelli, Borja Gonzalez León. 1508-1512 [doi]
- AI programmer: autonomously creating software programs using genetic algorithmsKory Becker, Justin Gottschlich. 1513-1521 [doi]
- Paradiseo: from a modular framework for evolutionary computation to the automated design of metaheuristics: 22 years of ParadiseoJohann Dréo, Arnaud Liefooghe, Sébastien Vérel, Marc Schoenauer, Juan Julián Merelo Guervós, Alexandre Quemy, Benjamin Bouvier, Jan Gmys. 1522-1530 [doi]
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- EBIC.JL: an efficient implementation of evolutionary biclustering algorithm in JuliaPawel Renc, Patryk Orzechowski, Aleksander Byrski, Jaroslaw Was, Jason H. Moore. 1540-1548 [doi]
- A multi-objective genetic algorithm for jacket optimizationJan Burak, Ole Jakob Mengshoel. 1549-1556 [doi]
- Using grammatical evolution for modelling energy consumption on a computer numerical control machineSamuel Carvalho, Joe Sullivan, Douglas Mota Dias, Enrique Naredo, Conor Ryan. 1557-1563 [doi]
- A heuristic approach to feasibility verification for truck loadingVinicius Gandra, Hatice Çalik, Tony Wauters, Greet Vanden Berghe. 1564-1569 [doi]
- Trustworthy AI for process automation on a Chylla-Haase polymerization reactorDaniel Hein 0001, Daniel Labisch. 1570-1578 [doi]
- Multi tree operators for genetic programming to identify optimal energy flow controllersKathrin Kefer, Roland Hanghofer, Patrick Kefer, Markus Stöger, Bernd Hofer, Michael Affenzeller, Stephan M. Winkler. 1579-1586 [doi]
- Simulation-based scheduling of a large-scale industrial formulation plant using a heuristics-assisted genetic algorithmChristian Klanke, Dominik R. Bleidorn, Christian Koslowski, Christian Sonntag, Sebastian Engell. 1587-1595 [doi]
- Addressing the multiplicity of solutions in optical lens design as a niching evolutionary algorithms computational challengeAnna V. Kononova, Ofer M. Shir, Teus Tukker, Pierluigi Frisco, Shutong Zeng, Thomas Bäck. 1596-1604 [doi]
- Advanced mine optimisation under uncertainty using evolutionWilliam Reid, Aneta Neumann, Simon Ratcliffe, Frank Neumann 0001. 1605-1613 [doi]
- Determining a consistent experimental setup for benchmarking and optimizing databasesMoisés Silva-Muñoz, Gonzalo Calderon, Alberto Franzin, Hugues Bersini. 1614-1621 [doi]
- Multi-objective evolutionary product bundling: a case studyOkan Tunali, Ahmet Tugrul Bayrak, Víctor Sánchez-Anguix, Reyhan Aydogan. 1622-1629 [doi]
- A genetic fuzzy system for interpretable and parsimonious reinforcement learning policiesJordan T. Bishop, Marcus Gallagher, Will N. Browne. 1630-1638 [doi]
- An experimental comparison of explore/exploit strategies for the learning classifier system XCSTim Hansmeier, Marco Platzner. 1639-1647 [doi]
- An overview of LCS research from 2020 to 2021David Pätzel, Michael Heider, Alexander R. M. Wagner. 1648-1656 [doi]
- Understanding parameter spaces using local optima networks: a case study on particle swarm optimizationChristopher W. Cleghorn, Gabriela Ochoa. 1657-1664 [doi]
- Investigating the landscape of a hybrid local search approach for a timetabling problemThomas Feutrier, Marie-Eléonore Kessaci, Nadarajen Veerapen. 1665-1673 [doi]
- Towards population-based fitness landscape analysis using local optima networksMelike D. Karatas, Ozgur E. Akman, Jonathan E. Fieldsend. 1674-1682 [doi]
- Dissipative polynomialsWilliam B. Langdon, Justyna Petke, David Clark. 1683-1691 [doi]
- Analysing the loss landscape features of generative adversarial networksJarrod Moses, Katherine M. Malan, Anna S. Bosman. 1692-1699 [doi]
- Dynamic landscape analysis for open-ended stackingBernhard Werth, Johannes Karder, Andreas Beham, Stefan Wagner 0002. 1700-1707 [doi]
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- Evolving neural selection with adaptive regularizationLi Ding, Lee Spector. 1717-1725 [doi]
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- Neuroevolution of recurrent neural networks for time series forecasting of coal-fired power plant operating parametersZimeng Lyu, Shuchita Patwardhan, David Stadem, James Langfeld, Steven A. Benson, Seth Thoelke, Travis Desell. 1735-1743 [doi]
- On the effects of pruning on evolved neural controllers for soft robotsGiorgia Nadizar, Eric Medvet, Felice Andrea Pellegrino, Marco Zullich, Stefano Nichele. 1744-1752 [doi]
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- A partially asynchronous global parallel genetic algorithmDarren M. Chitty. 1771-1778 [doi]
- An operation to promote diversity in evolutionary algorithms in a dynamic hybrid island modelGrasiele R. Duarte, Beatriz S. L. P. de Lima. 1779-1787 [doi]
- Solving QUBO with GPU parallel MOPSONoriyuki Fujimoto, Kouki Nanai. 1788-1794 [doi]
- Conduit: a C++ library for best-effort high performance computingMatthew Andres Moreno, Santiago Rodriguez Papa, Charles Ofria. 1795-1800 [doi]
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- House price prediction using clustering and genetic programming along with conducting a comparative studyFateme Azimlu, Shahryar Rahnamayan, Masoud Makrehchi. 1809-1816 [doi]
- A matheuristic approach for finding effective base locations and team configurations for north west air ambulanceBurak Boyaci, Muhammad Ali Nayeem, Ahmed Kheiri. 1817-1824 [doi]
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- Deceiving neural source code classifiers: finding adversarial examples with grammatical evolutionClaudio Ferretti, Martina Saletta. 1889-1897 [doi]
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- Simulating a logistics enterprise using an asymmetrical wargame simulation with soar reinforcement learning and coevolutionary algorithmsYing Zhao 0006, Erik Hemberg, Nate Derbinsky, Gabino Mata, Una-May O'Reilly. 1907-1915 [doi]
- Self-organizing migrating algorithm with clustering-aided migration and adaptive perturbation vector controlTomas Kadavy, Michal Pluhacek, Adam Viktorin, Roman Senkerik. 1916-1922 [doi]
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- A differential particle scheme and its application to PID parameter tuning of an inverted pendulumVictor Parque. 1937-1943 [doi]
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