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ORCIDGECCO 2021: Lille, France
- Krzysztof Krawiec:
GECCO '21: Genetic and Evolutionary Computation Conference, Companion Volume, Lille, France, July 10-14, 2021. ACM 2021, ISBN 978-1-4503-8351-6
Competition: Evolutionary computation in the energy domain: Smart grid applications
- Ansel Y. Rodríguez González
, Samantha Barajas, Ramón Aranda, Yoan Martínez-López, Julio Madera Quintana:
Ring cellular encode-decode UMDA: simple is effective. 1-2 - Junpeng Su, Han Huang, Zhifeng Hao:
Cooperative co-evolution strategies with time-dependent grouping for optimization problems in smart grids. 3-4
Competition: Optimal camera placement problem (OCP) and the unicost set covering problem (USCP)
- Janez Radescek, Matjaz Depolli:
Exact and approximate USCP with branch and bound. 5-6
Competition: Open optimization competition 2021: Competition and benchmarking of sampling-based optimization algorithms
- Alexandros Doumanoglou, Nikolaos Zioulis, Vladimiros Sterzentsenko, Antonis Karakottas, Dimitrios Zarpalas, Petros Daras:
Benchmarking gradient-free optimizers for 3D performance capture in the nevergrad platform. 7-8 - Tome Eftimov, Peter Korosec:
Robust benchmarking for multi-objective optimization. 9-10
Competition: Bound constrained single objective numerical optimization
- Tomas Kadavy, Michal Pluhacek, Adam Viktorin, Roman Senkerik:
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) 2021. 11-12
Competition: Optimization of a simulation model for a capacity and resource planning task for hospitals under special consideration of the COVID-19 pandemic
- Laurens Bliek, Arthur Guijt, Rickard Karlsson:
Hospital simulation model optimisation with a random ReLU expansion surrogate model. 13-14 - Pablo S. Naharro, Antonio LaTorre, José-María Peña:
Surrogate-based optimisation for a hospital simulation scenario using pairwise classifiers. 15-16 - Jordi Pereira:
An evolutionary and neighborhood-based algorithm for optimization under low budget requirements. 17-18 - José L. Sainz-Pardo:
Linear regression strategy for differential evolution. 19-20
Hot off the press
- Shaukat Ali, Paolo Arcaini, Tao Yue:
Do quality indicators prefer particular multi-objective search algorithms in search-based software engineering?: (hot off the press track at GECCO 2021). 21-22 - Benjamin Doerr:
Runtime analysis via symmetry arguments: (hot-off-the-press track at GECCO 2021). 23-24 - Benjamin Doerr, Weijie Zheng:
Theoretical analyses of multi-objective evolutionary algorithms on multi-modal objectives: (hot-off-the-press track at GECCO 2021). 25-26 - Tome Eftimov, Peter Korosec:
Reducing bias in multi-objective optimization benchmarking. 27-28 - Anton V. Eremeev, Yulia V. Kovalenko:
Optimal recombination and adaptive restarts improve GA performance on the asymmetric TSP. 29-30 - William B. Langdon, Oliver Krauss:
Genetic improvement of data for maths functions. 31-32 - Thomas Laurent, Paolo Arcaini, Fuyuki Ishikawa, Anthony Ventresque:
Achieving weight coverage for an autonomous driving system with search-based test generation (HOP track at GECCO 2021). 33-34 - Michela Lorandi, Leonardo Lucio Custode, Giovanni Iacca:
Genetic improvement of routing in delay tolerant networks. 35-36 - Manuel López-Ibáñez, Juan Esteban Diaz:
Interactive parameter tuning of bi-objective optimisation algorithms using the empirical attainment function. 37-38 - Krzysztof Michalak, Mario Giacobini:
The influence of uncertainties on optimization of vaccinations on a network of animal movements. 39-40 - Michal Witold Przewozniczek, Piotr Dziurzanski, Shuai Zhao, Leandro Soares Indrusiak:
Multi-objective parameter-less population pyramid in solving the real-world and theoretical problems. 41-42 - Dirk Schweim, David Wittenberg, Franz Rothlauf:
On sampling error in evolutionary algorithms. 43-44 - Valerio Terragni, Gunel Jahangirova, Mauro Pezzè, Paolo Tonella:
Improving assertion oracles with evolutionary computation. 45-46 - Weijie Zheng, Huanhuan Chen, Xin Yao:
Analysis of evolutionary algorithms on fitness function with time-linkage property (hot-off-the-press track at GECCO 2021). 47-48
Late-breaking abstracts
- Dong-Hee Cho, Seung-Hyun Moon, Yong-Hyuk Kim:
An improved predictor of daily stock index based on a genetic filter. 49-50 - Niranjana Deshpande, Naveen Sharma:
Algorithm selection using transfer learning. 51-52 - Duarte M. Dias, Alexandre D. Jesus, Luís Paquete:
A software library for archiving nondominated points. 53-54 - F. Gibson, R. Fabbro, Alma A. M. Rahat, Thomas Torsney-Weir, Daniel Archambault, M. Gravenor, B. Lucini:
An interactive tool for enhancing hospital capacity predictions using an epidemiological model. 55-56 - Sonia Nasri, Hend Bouziri, Wassila Aggoune-Mtalaa:
A new hybrid evolutionary algorithm for dial-a-ride problems. 57-58 - Nikolay O. Nikitin, Alexander Hvatov, Iana S. Polonskaia, Anna V. Kalyuzhnaya, Georgii V. Grigorev, Xiaohao Wang, Xiang Qian:
Generative design of microfluidic channel geometry using evolutionary approach. 59-60 - Pawel Renc, Patryk Orzechowski, Aleksander Byrski, Jaroslaw Was, Jason H. Moore:
Rapid prototyping of evolution-driven biclustering methods in Julia. 61-62 - Jean Ruppert, Marharyta Aleksandrova, Thomas Engel:
k-Pareto optimality for many-objective genetic optimization. 63-64 - Seung-Soo Shin, Yong-Hyuk Kim:
Winner prediction for real-time strategy games through feature selection based on a genetic wrapper. 65-66
Posters: Ant colony optimization and swarm intelligence
- Hirad Assimi, Frank Neumann, Markus Wagner, Xiaodong Li:
Novelty particle swarm optimisation for truss optimisation problems. 67-68 - Darren M. Chitty:
Partial-ACO as a GA mutation operator applied to TSP instances. 69-70 - Iztok Fister Jr., Iztok Fister, Andrés Iglesias, Akemi Gálvez:
On detecting the novelties in metaphor-based algorithms. 71-72 - H. David Mathias, Annie S. Wu, Daniel Dang:
Evolved response thresholds generalize across problem instances for a deterministic-response multiagent system. 73-74 - Federico Naldini, Paola Pellegrini, Joaquin Rodriguez:
Ant colony optimization for energy-efficient train operations. 75-76 - James Sakal, Jonathan E. Fieldsend, Edward C. Keedwell:
Learning assignment order in an ant colony optimiser for the university course timetabling problem. 77-78 - Juntao Zhang, Peng Cheng:
Ant swarm algorithm for self-organizing complex system. 79-80
Posters: Complex systems (artificial life, artificial immune systems, generative and developmental systems, evolutionary robotics, evolvable hardware)
- Renata B. Biazzi, André Fujita, Daniel Y. Takahashi:
Predicting soft robot's locomotion fitness. 81-82 - David M. Bossens, Danesh Tarapore:
On the use of feature-maps for improved quality-diversity meta-evolution. 83-84 - Amine M. Boumaza:
Promoting reproductive isolation through diversity in on-line collective robotics. 85-86 - Alexandre Coninx, Stéphane Doncieux:
Younger is better: a simple and efficient selection strategy for MAP-Elites. 87-88 - Joshua Cook, Kagan Tumer:
Ad hoc teaming through evolution. 89-90 - Matteo De Carlo, Eliseo Ferrante, Jacintha Ellers, Gerben Meynen, A. E. Eiben:
The impact of different tasks on evolved robot morphologies. 91-92 - Fuda van Diggelen, Eliseo Ferrante, A. E. Eiben:
Comparing lifetime learning methods for morphologically evolving robots. 93-94 - Gaurav Dixit, Charles Koll, Kagan Tumer:
Heterogeneous agent coordination via adaptive quality diversity and specialization. 95-96 - Paul Ecoffet, Nicolas Fontbonne, Jean-Baptiste André, Nicolas Bredèche:
Reinforcement learning with rare significant events: direct policy search vs. gradient policy search. 97-98 - Mika Ito, Leo Cazenille, Nathanaël Aubert-Kato:
Automatic exploration of the property space of reservoirs. 99-100 - Hetvi Jethwani, Sumeet Agarwal:
Examining forms of inductive bias towards 'simplicity' in genetic algorithms to enhance evolvability of boolean functions. 101-102 - João Macedo, Lino Marques, Ernesto Costa:
Designing fitness functions for odour source localisation. 103-104 - W. Garrett Mitchener:
How to evolve a neuron. 105-106 - Gregory Furman, Geoff Nitschke:
Environmental impact on evolving language diversity. 107-108 - Margarita Rebolledo, Daan Zeeuwe, Thomas Bartz-Beielstein, A. E. Eiben:
Impact of energy efficiency on the morphology and behaviour of evolved robots. 109-110 - Kirby Steckel, Jacob Schrum:
Illuminating the space of beatable lode runner levels produced by various generative adversarial networks. 111-112 - Kathryn Walker, Helmut Hauser, Sebastian Risi:
Growing simulated robots with environmental feedback: an eco-evo-devo approach. 113-114 - Dongmei Wang, Yiwen Liang, Chengyu Tan, Hongbin Dong, Xinmin Yang:
Pathogen dose based natural killer cell algorithm for classification. 115-116
Posters: Evolutionary combinatorial optimization and metaheuristics
- Marwan F. Abdelatti, Abdeltawab M. Hendawi, Manbir Sodhi:
Optimizing a GPU-accelerated genetic algorithm for the vehicle routing problem. 117-118 - Arnaud Berny:
Linear representation of categorical values. 119-120 - Piotr Cybula, Marek Rogalski, Piotr Sielski, Andrzej Jaszkiewicz, Przemyslaw Pelka:
Effective recombination operators for the family of vehicle routing problems. 121-122 - Mehdi El Krari, Rym Nesrine Guibadj, John Woodward, Denis Robilliard:
Introducing a hash function for the travelling salesman problem for differentiating solutions. 123-124 - Georg Faustmann, Christoph Mrkvicka, Nysret Musliu, Felix Winter:
Automated configuration of parallel machine dispatching rules by machine learning. 125-126 - Justin Fellers, José Quevedo, Marwan F. Abdelatti, Meghan Steinhaus, Manbir Sodhi:
Selecting between evolutionary and classical algorithms for the CVRP using machine learning: optimization of vehicle routing problems. 127-128 - Francisco Javier Gil Gala, María R. Sierra, Carlos Mencía, Ramiro Varela:
The optimal filtering set problem with application to surrogate evaluation in genetic programming. 129-130 - Fabian Kittel, Jannik Enenkel, Michael Guckert, Jana Holznigenkemper, Neil Urquhart:
Optimisation algorithms for parallel machine scheduling problems with setup times. 131-132 - Ole Jakob Mengshoel, Tong Yu, Jon Riege, Eirik Flogard:
Stochastic local search for efficient hybrid feature selection. 133-134 - Octavio Ramos-Figueroa, Marcela Quiroz-Castellanos:
A grouping genetic algorithm for the unrelated parallel-machine scheduling problem. 135-136 - Florian Richoux, Jean-François Baffier:
Error function learning with interpretable compositional networks for constraint-based local search. 137-138 - Hao Tong, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao:
A hybrid local search framework for the dynamic capacitated arc routing problem. 139-140 - Wei Zheng, Yiqing Zhang, Jianyong Sun:
Continuous encoding for community detection in complex networks. 141-142
Posters: Evolutionary machine learning
- Pawel Benecki, Szymon Piechaczek, Daniel Kostrzewa, Jakub Nalepa:
Detecting anomalies in spacecraft telemetry using evolutionary thresholding and LSTMs. 143-144 - Victor Costa, Nuno Lourenço, João Correia, Penousal Machado:
Improved evolution of generative adversarial networks. 145-146 - Kaan Demir, Bach Hoai Nguyen, Bing Xue, Mengjie Zhang:
Sparsity-based evolutionary multi-objective feature selection for multi-label classification. 147-148 - Miguel García-Torres, Francisco Gómez-Vela, Federico Divina, Diego P. Pinto-Roa, José Luis Vázquez Noguera, Julio César Mello Román:
Scatter search for high-dimensional feature selection using feature grouping. 149-150 - Pieter Gijsbers, Florian Pfisterer, Jan N. van Rijn, Bernd Bischl, Joaquin Vanschoren:
Meta-learning for symbolic hyperparameter defaults. 151-152 - Ahmed Hallawa, Thorsten Born, Anke Schmeink, Guido Dartmann, Arne Peine, Lukas Martin, Giovanni Iacca, A. E. Eiben, Gerd Ascheid:
Evo-RL: evolutionary-driven reinforcement learning. 153-154 - Krzysztof Jurczuk, Marcin Czajkowski, Marek Kretowski:
Understanding evolutionary induction of decision trees: a multi-tree repository approach. 155-156 - Ilona M. Kulikovskikh, Tarzan Legovic:
Growth and harvest induce essential dynamics in neural networks. 157-158 - Sami Lemtenneche, Abdelhakim Cheriet, Bensayah Abdellah:
Permutation-based optimization using a generative adversarial network. 159-160 - Mariele Motta, Tanja Hagemann, Sebastian Fischer, Felix Assion:
EvolMusic: towards musical adversarial examples for black-box attacks on speech-to-text. 161-162 - Romain Orhand, Anne Jeannin-Girardon, Pierre Parrend, Pierre Collet:
Explainability and performance of anticipatory learning classifier systems in non-deterministic environments. 163-164 - Christian Raymond, Qi Chen, Bing Xue, Mengjie Zhang:
Multi-objective genetic programming for symbolic regression with the adaptive weighted splines representation. 165-166 - Jake Robertson, Ting Hu:
An evolutionary approach to interpretable learning. 167-168 - Hiroki Shiraishi, Masakazu Tadokoro, Yohei Hayamizu, Yukiko Fukumoto, Hiroyuki Sato, Keiki Takadama:
Misclassification detection based on conditional VAE for rule evolution in learning classifier system. 169-170 - Alexander R. M. Wagner, Anthony Stein:
Adopting lexicase selection for michigan-style learning classifier systems with continuous-valued inputs. 171-172 - Bin Wang, Wenbin Pei, Bing Xue, Mengjie Zhang:
Evolving local interpretable model-agnostic explanations for deep neural networks in image classification. 173-174 - Connor Yates, Ayhan Alp Aydeniz, Kagan Tumer:
Adaptive multi-fitness learning for robust coordination. 175-176
Posters: Evolutionary multiobjective optimization
- Long Chen, Xuebing Cai, Kezhong Jin, Zhenzhou Tang:
MOMPA: a high performance multi-objective optimizer based on marine predator algorithm. 177-178 - Max Hort, Federica Sarro:
The effect of offspring population size on NSGA-II: a preliminary study. 179-180 - Yuta Kobayashi, Claus Aranha, Tetsuya Sakurai:
Dynamic adaptation of decomposition vector set size for MOEA/D. 181-182 - Jian-Yu Li, Ke-Jing Du, Zhi-Hui Zhan, Hua Wang, Jun Zhang:
Multi-criteria differential evolution: treating multitask optimization as multi-criteria optimization. 183-184 - Claudio Lucio do Val Lopes, Flávio V. C. Martins, Elizabeth F. Wanner, Kalyanmoy Deb:
An approximate MIP-DoM calculation for multi-objective optimization using affinity propagation clustering algorithm. 185-186 - Jesús-Adolfo Mejía-de-Dios, Efrén Mezura-Montes:
Generating multi-objective bilevel optimization problems with multiple non-cooperative followers. 187-188 - Sumit Mishra, Ved Prakash, Maxim Buzdalov:
Labeling-oriented non-dominated sorting is Θ(MN3). 189-190 - Abdul-Rauf Nuhu, Xuyang Yan, Daniel Opoku, Abdollah Homaifar:
A niching framework based on fitness proportionate sharing for multi-objective genetic algorithm (MOGA-FPS). 191-192 - Jiaze Sun, Nan Han, Jianbin Huang, Jiahui Deng:
Landmark-based multi-objective route planning for large-scale road net. 193-194 - Juan Ungredda, Jürgen Branke, Mariapia Marchi, Teresa Montrone:
One step preference elicitation in multi-objective Bayesian optimization. 195-196 - Liping Wang, Lin Zhang, Yu Ren, Qicang Qiu, Feiyue Qiu:
Two comprehensive performance metrics for overcoming the deficiencies of IGD and HV. 197-198
Posters: Evolutionary numerical optimization
- Adetunji David Ajimakin, V. Susheela Devi:
Estimation of von mises-fisher distribution algorithm, with application to support vector classification. 199-200 - Abdennour Boulesnane, Souham Meshoul:
Reinforcement learning for dynamic optimization problems. 201-202 - Ling-Yu Li, Wen-Jie Ou, Xiao-Min Hu, Wei-Neng Chen, An Song:
An empirical study of cooperative frequency in distributed cooperative co-evolution. 203-204 - Tassallah Abdullahi, Geoff Nitschke:
Disease outbreaks: tuning predictive machine learning. 205-206 - Nicolas Roy, Charlotte Beauthier, Timotéo Carletti, Alexandre Mayer:
Setup of fuzzy hybrid particle swarms: a heuristic approach. 207-208 - Hiroki Shimizu, Masashi Toyoda:
CMA-ES with coordinate selection for high-dimensional and ill-conditioned functions. 209-210 - Bing Wang, Hemant Kumar Singh, Tapabrata Ray:
Bridging kriging believer and expected improvement using bump hunting for expensive black-box optimization. 211-212 - Boris Yazmir, Ofer M. Shir:
Automated feature detection of black-box continuous search-landscapes using neural image recognition. 213-214 - Urban Skvorc, Tome Eftimov, Peter Korosec:
A complementarity analysis of the COCO benchmark problems and artificially generated problems. 215-216
Posters: Genetic algorithms
- Vojtech Cerný, Jakub Gemrot:
Three population co-evolution for generating mechanics of endless runner games. 217-218 - Giovanni Acampora, Roberto Schiattarella, Autilia Vitiello:
Quantum genetic selection: using a quantum computer to select individuals in genetic algorithms. 219-220 - Renuá Meireles Almeida, Denys Menfredy Ferreira Ribeiro, Rodrigo Moraes Rodrigues, Otávio Noura Teixeira:
Fitness value curves prediction in the evolutionary process of genetic algorithms. 221-222 - Srivathsa Gottipati, Praveen Paruchuri:
A genetic algorithm approach to compute mixed strategy solutions for general Stackelberg games. 223-224 - Rune Krauss, Marcel Merten, Mirco Bockholt, Rolf Drechsler:
ALF: a fitness-based artificial life form for evolving large-scale neural networks. 225-226 - Krzysztof L. Sadowski, Dirk Thierens, Peter A. N. Bosman:
Optimization of multi-objective mixed-integer problems with a model-based evolutionary algorithm in a black-box setting. 227-228 - Dirk Thierens, Tobias van Driessel:
A benchmark generator of tree decomposition Mk landscapes. 229-230 - Jakub Vincalek, Sean P. Walton, Ben J. Evans:
It's the journey not the destination: building genetic algorithms practitioners can trust. 231-232
Posters: General evolutionary computation and hybrids
- Maciej Swiechowski:
A crossover that matches diverse parents together in evolutionary algorithms. 233-234 - Fredrik Foss, Ole Jakob Mengshoel:
A multimethod approach to multimodal function optimization. 235-236 - Sean N. Harris, Daniel R. Tauritz:
Elo-based similar-strength opponent sampling for multiobjective competitive coevolution. 237-238 - Ana Kostovska, Diederick Vermetten, Carola Doerr, Saso Dzeroski, Pance Panov, Tome Eftimov:
OPTION: optimization algorithm benchmarking ontology. 239-240 - Florian Pfisterer, Jan N. van Rijn, Philipp Probst, Andreas C. Müller, Bernd Bischl:
Learning multiple defaults for machine learning algorithms. 241-242 - Kenneth N. Reid, Iliya Miralavy, Stephen Kelly, Wolfgang Banzhaf, Cedric Gondro:
The factory must grow: automation in Factorio. 243-244 - Furong Ye, Carola Doerr, Thomas Bäck:
Leveraging benchmarking data for informed one-shot dynamic algorithm selection. 245-246 - Longfei Zhang, Ke Li, Shi Gu:
Empirical study of correlations in the fitness landscapes of combinatorial optimization problems. 247-248
Posters: Genetic programming
- Qinglan Fan, Ying Bi, Bing Xue, Mengjie Zhang:
Genetic programming with a new representation and a new mutation operator for image classification. 249-250 - Lukas Kammerer, Gabriel Kronberger, Stephan M. Winkler:
Empirical analysis of variance for genetic programming based symbolic regression. 251-252 - William B. Langdon:
Fitness first and fatherless crossover. 253-254 - Yiming Li, Lin Shang:
"Re-ID BUFF": an enhanced similarity measurement based on genetic programming for person re-identification. 255-256 - Jun Ma, Fenghui Gao, Shuangrong Liu, Lin Wang:
Linear-dependent multi-interpretation neuro-encoded expression programming. 257-258 - Kyle L. Nickerson, Ting Hu:
Principled quality diversity for ensemble classifiers using MAP-Elites. 259-260 - Christian Olmscheid, David Wittenberg, Dominik Sobania, Franz Rothlauf:
Improving estimation of distribution genetic programming with novelty initialization. 261-262 - Anil Kumar Saini, Lee Spector:
GLEAM: genetic learning by extraction and absorption of modules. 263-264 - Aliyu Sani Sambo, R. Muhammad Atif Azad, Yevgeniya Kovalchuk, Vivek Padmanaabhan Indramohan, Hanifa Shah:
Improving the generalisation of genetic programming models with evaluation time and asynchronous parallel computing. 265-266 - Alexander Wild, Barry Porter:
Neurally guided transfer learning for genetic programming. 267-268 - Congwen Xu, Qiang Lu, Jake Luo, Zhiguang Wang:
Adversarial bandit gene expression programming for symbolic regression. 269-270
Posters: Neuroevolution
- Sebastián Basterrech, Gerardo Rubino:
Evolving reservoir weights in the frequency domain. 271-272 - Ben Feng, Dayiheng Liu, Yanan Sun:
Evolving transformer architecture for neural machine translation. 273-274 - Colin Flynn, Mohammed Bennamoun, Farid Boussaïd:
Growth and evolution of deep neural networks from gene regulatory networks. 275-276 - Zhenyu Gao, Gongjin Lan:
A NEAT-based multiclass classification method with class binarization. 277-278 - Unai Garciarena, Nuno Lourenço, Penousal Machado, Roberto Santana, Alexander Mendiburu:
On the exploitation of neuroevolutionary information. 279-280 - Ziyi Gong, Paul Munro:
Modeling the evolution of retina neural network. 281-282 - Daan Klijn, A. E. Eiben:
A coevolutionary approach to deep multi-agent reinforcement learning. 283-284 - Henrik D. Mettler, Maximilian Schmidt, Walter Senn, Mihai A. Petrovici, Jakob Jordan:
Evolving neuronal plasticity rules using cartesian genetic programming. 285-286 - Bin Wang, Bing Xue, Mengjie Zhang:
A transfer learning based evolutionary deep learning framework to evolve convolutional neural networks. 287-288 - Xinyun Zou, Eric O. Scott, Alexander B. Johnson, Kexin Chen, Douglas A. Nitz, Kenneth A. De Jong, Jeffrey L. Krichmar:
Neuroevolution of a recurrent neural network for spatial and working memory in a simulated robotic environment. 289-290
Posters: Real world applications
- Akram Alofi, Mahmoud A. Bokhari, Robert J. Hendley, Rami Bahsoon:
Selecting miners within blockchain-based systems using evolutionary algorithms for energy optimisation. 291-292 - Thomas Bartz-Beielstein, Marcel Dröscher, Alpar Gür, Alexander Hinterleitner, Olaf Mersmann, Dessislava Peeva, Lennard Reese, Nicolas Rehbach, Frederik Rehbach, A. Sen, Aleksandr Subbotin, Martin Zaefferer:
Resource planning for hospitals under special consideration of the COVID-19 pandemic: optimization and sensitivity analysis. 293-294 - Antonio Candelieri, Andrea Ponti, Francesco Archetti:
Risk aware optimization of water sensor placement. 295-296 - Jakub Chlebik, Jirí Jaros:
Distributed evolutionary design of HIFU treatment plans. 297-298 - Dong-Hee Cho, Yong-Hyuk Kim:
An optimal oil skimmer assignment based on a genetic algorithm with minimal mobilized locations. 299-300 - Mark A. Coletti, Shang Gao, Spencer Paulissen, Nicholas Quentin Haas, Robert M. Patton:
Diagnosing autonomous vehicle driving criteria with an adversarial evolutionary algorithm. 301-302 - Mark Connor, Michael O'Neill:
Optimizing the parameters of a physical exercise dose-response model: an algorithmic comparison. 303-304 - Francisco Cruz-Zelante, Eduardo Segredo, Gara Miranda:
Dealing with a problematic roundabout by optimizing a traffic light system through evolutionary computation. 305-306 - Daniel Dobos, Tien Thanh Nguyen, John A. W. McCall, Allan Wilson, Phil Stockton, Helen Corbett:
Weighted ensemble of gross error detection methods based on particle swarm optimization. 307-308 - Sabrina Draude, Edward C. Keedwell, Zoran Kapelan, Rebecca Hiscock:
Wastewater systems planned maintenance scheduling using multi-objective optimisation. 309-310 - Rahul Dubey, Sushil J. Louis:
Evolving potential field parameters for deploying UAV-based two-hop wireless mesh networks. 311-312 - Theodoros Galanos, Antonios Liapis, Georgios N. Yannakakis, Reinhard Koenig:
ARCH-Elites: quality-diversity for urban design. 313-314 - Kate Han, Lee A. Christie, Alexandru-Ciprian Zavoianu, John McCall:
Optimising the introduction of connected and autonomous vehicles in a public transport system using macro-level mobility simulations and evolutionary algorithms. 315-316 - Mohsen Mousavi, Amir H. Gandomi, Magd Abdel Wahab:
Structural damage identification under non-linear EOV effects using genetic programming. 317-318 - Victor Parque:
Towards higher order fairness functionals for smooth path planning. 319-320 - Eirik Høgdahl Skjærseth, Harald Vinje, Ole Jakob Mengshoel:
Novelty search for evolving interesting character mechanics for a two-player video game. 321-322 - Daniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, Pascal Bouvry:
Optimising pheromone communication in a UAV swarm. 323-324 - Fabian Clemens Weigend, Jason Siegler, Oliver Obst:
A new pathway to approximate energy expenditure and recovery of an athlete. 325-326 - Heiner Zille, Sanaz Mostaghim, Fabien Evrard, Berend G. M. van Wachem:
Unit-aware multi-objective genetic programming for the prediction of the stokes flow around a sphere. 327-328
Posters: Search-based software engineering
- Vadim Liventsev, Aki Härmä, Milan Petkovic:
Neurogenetic programming framework for explainable reinforcement learning. 329-330 - Dirk Schweim, Erik Hemberg, Dominik Sobania, Una-May O'Reilly, Franz Rothlauf:
Using knowledge of human-generated code to bias the search in program synthesis with grammatical evolution. 331-332
Posters: Theory
- Aldeida Aleti, Mark Wallace, Markus Wagner:
On the effectiveness of restarting local search. 333-334 - Arnaud Berny:
Affine OneMax. 335-336 - Sumit Mishra, Ved Prakash:
Time complexity analysis of the deductive sort in the best case. 337-338
Tutorials: Introductory tutorials
- Anne Auger, Nikolaus Hansen:
Benchmarking: state-of-the-art and beyond. 339-340 - Andries P. Engelbrecht, Christopher W. Cleghorn:
Recent advances in particle swarm optimization analysis and understanding 2021. 341-368 - Benjamin Doerr:
A gentle introduction to theory (for non-theoreticians). 369-398 - Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of evolutionary algorithms: basic introduction. 399-425 - Risto Miikkulainen:
Evolution of neural networks. 426-442 - Una-May O'Reilly, Erik Hemberg:
Genetic programming: a tutorial introduction. 443-453 - Luís Paquete, Manuel López-Ibáñez:
Replicability and reproducibility in evolutionary optimization. 454-462 - Franz Rothlauf:
Representations for evolutionary algorithms. 463-483 - Ofer M. Shir:
Introductory mathematical programming for EC. 484-497 - Anthony Stein, Masaya Nakata:
Learning classifier systems: from principles to modern systems. 498-527 - Daniel R. Tauritz, John R. Woodward:
Hyper-heuristics tutorial. 528-557 - Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms. 558-587 - Darrell Whitley:
Theoretical foundations of evolutionary computation for beginners and veterans. 588-635
Tutorials: Advanced tutorials
- Youhei Akimoto, Nikolaus Hansen:
CMA-ES and advanced adaptation mechanisms. 636-663 - Dimo Brockhoff, Tea Tusar:
Benchmarking multiobjective optimizers 2.0. 664-668 - Will N. Browne:
Advanced Learning Classifier Systems. 669-691 - Carlos A. Coello Coello:
Constraint-handling techniques used with evolutionary algorithms. 692-714 - Antoine Cully, Jean-Baptiste Mouret, Stéphane Doncieux:
Quality-diversity optimisation. 715-739 - Kalyanmoy Deb, Julian Blank:
Evolutionary multi- and many-objective optimization: methodologies, applications and demonstration. 740-769 - Tome Eftimov, Peter Korosec:
Statistical analyses for meta-heuristic stochastic optimization algorithms. 770-785 - Sæmundur Óskar Haraldsson, Alexander E. I. Brownlee, John R. Woodward, Markus Wagner, Bradley Alexander:
Genetic improvement: taking real-world source code and improving it using genetic programming. 786-817 - Mardé Helbig:
Dynamic multi-objective optimization: introduction, challenges, applications and future directions. 818-838 - Thomas Helmuth, William G. La Cava:
Lexicase Selection. 839-855 - Per Kristian Lehre, Pietro S. Oliveto:
Runtime analysis of population-based evolutionary algorithms. 856-880 - Ke Li, Qingfu Zhang:
Decomposition multi-objective optimisation: current developments and future opportunities. 881-898 - Katherine M. Malan, Gabriela Ochoa:
Recent advances in landscape analysis for optimisation and learning. 899-917 - Aneta Neumann, Frank Neumann, Chao Qian:
Evolutionary submodular optimisation. 918-940 - Ofer M. Shir, Thomas Bäck:
Sequential experimentation by evolutionary algorithms. 941-958 - Thomas Stützle, Manuel López-Ibáñez:
Automated algorithm configuration and design. 959-982 - Jamal Toutouh, Una-May O'Reilly:
Coevolutionary computation for adversarial deep learning. 983-1001
Tutorials: Specialized tutorials
- Penousal Machado:
Evolutionary art and design: representation, fitness and interaction. 1002-1031 - Ali Ouni, Mohamed Wiem Mkaouer:
Search based software engineering: challenges, opportunities and recent applications. 1032-1063 - Gregor Papa:
Applications of dynamic parameter control in evolutionary computation. 1064-1088 - Stjepan Picek, Domagoj Jakobovic:
Evolutionary computation and machine learning in cryptology. 1089-1118 - Lee Spector:
Push. 1119-1134 - Nayat Sánchez Pi, Luis Martí:
Towards a green AI: evolutionary solutions for an ecologically viable artificial intelligence. 1135-1140 - Bing Xue, Mengjie Zhang:
Evolutionary computation for feature selection and feature construction. 1141-1168 - Mengjie Zhang, Stefano Cagnoni:
Evolutionary computation and evolutionary deep learning for image analysis, signal processing and pattern recognition. 1169-1198
Workshop: Analysing algorithmic behaviour of optimisation heuristics
- Rick Boks, Anna V. Kononova, Hao Wang:
Quantifying the impact of boundary constraint handling methods on differential evolution. 1199-1207 - Lucija Planinic, Marko Djurasevic, Luca Mariot, Domagoj Jakobovic, Stjepan Picek, Carlos A. Coello Coello:
On the genotype compression and expansion for evolutionary algorithms in the continuous domain. 1208-1216 - Helena Stegherr, Michael Heider, Leopold Luley, Jörg Hähner:
Design of large-scale metaheuristic component studies. 1217-1226 - Tobias van Driessel, Dirk Thierens:
Benchmark generator for TD Mk landscapes. 1227-1233 - Bas van Stein, Fabio Caraffini, Anna V. Kononova:
Emergence of structural bias in differential evolution. 1234-1242 - Diederick Vermetten, Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck:
Is there anisotropy in structural bias? 1243-1250
Workshop: Black box optimization benchmarking
- Dimo Brockhoff, Baptiste Plaquevent-Jourdain, Anne Auger, Nikolaus Hansen:
DMS and MultiGLODS: black-box optimization benchmarking of two direct search methods on the bbob-biobj test suite. 1251-1258 - Michal Okulewicz, Mateusz Zaborski:
Benchmarking SHADE algorithm enhanced with model based optimization on the BBOB noiseless testbed. 1259-1266
Workshop: Decomposition techniques in evolutionary optimization
- Rodolfo Ayala Lopes, Rodrigo C. P. Silva, Alan R. R. de Freitas:
An abstract interface for large-scale continuous optimization decomposition methods. 1267-1274 - Cameron A. G. MacRae, Melih Ozlen, Andreas T. Ernst:
The bee-benders hybrid algorithm with application to transmission expansion planning. 1275-1282 - Davood Zaman Farsa, Azam Asilian Bidgoli, Ehsan Rokhsat-Yazdi, Shahryar Rahnamayan:
Population-based coordinate descent algorithm with majority voting. 1283-1289
Workshop: Evolutionary algorithms and HPC
- Amanda S. Dufek, Douglas Adriano Augusto, Helio J. C. Barbosa, Pedro L. S. Dias, Jack R. Deslippe:
An efficient fault-tolerant communication algorithm for population-based metaheuristics. 1290-1298 - Joshua Karns, Travis Desell:
Improving the scalability of distributed neuroevolution using modular congruence class generated innovation numbers. 1299-1307 - Victor Parque:
Generating combinations on the GPU and its application to the k-subset sum. 1308-1316 - Laurent Turpin, Thierry Gautier, Jonathan Rouzaud-Cornabas:
X-Aevol: GPU implementation of an evolutionary experimentation simulator. 1317-1325
Workshop: Evolutionary algorithms for problems with uncertainty
- Tinkle Chugh, Manuel López-Ibáñez:
Maximising hypervolume and minimising ϵ-indicators using Bayesian optimisation over sets. 1326-1334 - Satvik Dasariraju, Ryan J. Urbanowicz:
RARE: evolutionary feature engineering for rare-variant bin discovery. 1335-1343 - Sibghat Ullah, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck:
A new acquisition function for robust Bayesian optimization of unconstrained problems. 1344-1345
Workshop: Evolutionary computation and decision making
- Harshal Tupsamudre, Saket Saurabh, Arun Ramamurthy, Mangesh S. Gharote, Sachin Lodha:
A divide and conquer approach for web services location allocation problem. 1346-1354 - Marco Virgolin, Andrea De Lorenzo, Francesca Randone, Eric Medvet, Mattias Wahde:
Model learning with personalized interpretability estimation (ML-PIE). 1355-1364
Workshop: Evolutionary computation for the automated design of algorithms
- Amine Aziz-Alaoui, Carola Doerr, Johann Dréo:
Towards large scale automated algorithm design by integrating modular benchmarking frameworks. 1365-1374 - Jacob de Nobel, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules. 1375-1384 - Gerardo Ibarra-Vázquez, Gustavo Olague, Cesar Puente, Mariana Chan-Ley, Carlos Soubervielle-Montalvo:
Automated design of accurate and robust image classifiers with brain programming. 1385-1393 - Marcella Scoczynski Ribeiro Martins, Diego Oliva, Erick Rodríguez-Esparza, Myriam Regattieri Delgado, Ricardo Lüders, Mohamed El Yafrani, Luiz Ledo, Mohamed E. Abd Elaziz, Marco Antonio Pérez Cisneros:
A selection hyperheuristic guided by Thompson sampling for numerical optimization. 1394-1402 - Yingfang Yuan, Wenjun Wang, Wei Pang:
Which hyperparameters to optimise?: an investigation of evolutionary hyperparameter optimisation in graph neural network for molecular property prediction. 1403-1404
Workshop: Evolutionary computation for permutation problems
- Joan Alza, Mark Bartlett, Josu Ceberio, John A. W. McCall:
Towards the landscape rotation as a perturbation strategy on the quadratic assignment problem. 1405-1413 - Xabier Benavides, Josu Ceberio, Leticia Hernando:
On the symmetry of the quadratic assignment problem through elementary landscape decomposition. 1414-1422 - Jakob Bossek, Markus Wagner:
Generating instances with performance differences for more than just two algorithms. 1423-1432 - Andoni I. Garmendia, Josu Ceberio, Alexander Mendiburu:
Exploratory analysis of the Monte Carlo tree search for solving the linear ordering problem. 1433-1441 - Michal Witold Przewozniczek, Marcin M. Komarnicki, Peter A. N. Bosman, Dirk Thierens, Bartosz Frej, Ngoc Hoang Luong:
Hybrid linkage learning for permutation optimization with Gene-pool optimal mixing evolutionary algorithms. 1442-1450 - Olivier Regnier-Coudert, Guillaume Povéda:
An empirical evaluation of permutation-based policies for stochastic RCPSP. 1451-1458 - Thomas Weise, Xinlu Li, Yan Chen, Zhize Wu:
Solving job shop scheduling problems without using a bias for good solutions. 1459-1466
Workshop: Evolutionary data mining and optimization over graphs
- Kateryna Konotopska, Giovanni Iacca:
Graph-aware evolutionary algorithms for influence maximization. 1467-1475 - Eneko Osaba, Esther Villar-Rodriguez, Izaskun Oregi, Aitor Moreno-Fernandez-de-Leceta:
Focusing on the hybrid quantum computing - Tabu search algorithm: new results on the Asymmetric Salesman Problem. 1476-1482
Workshop: Evolutionary reinforcement learning
- Hendrik Baier, Michael Kaisers:
Novelty and MCTS. 1483-1487 - Augusto Lopez Dantas, Alexander Fiabane do Rego, Aurora T. R. Pozo:
Using deep Q-network for selection hyper-heuristics. 1488-1492 - Maximilian Hüttenrauch, Gerhard Neumann:
Coordinate ascent MORE with adaptive entropy control for population-based regret minimization. 1493-1497 - Léni K. Le Goff, Emma Hart:
On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme. 1498-1502 - José Quevedo, Marwan F. Abdelatti, Farhad Imani, Manbir Sodhi:
Using reinforcement learning for tuning genetic algorithms. 1503-1507 - Shibei Zhu, Francesco Belardinelli, Borja Gonzalez León:
Evolutionary reinforcement learning for sparse rewards. 1508-1512
Workshop: Evolutionary computation software systems
- Kory Becker, Justin Gottschlich:
AI programmer: autonomously creating software programs using genetic algorithms. 1513-1521 - Johann Dréo, Arnaud Liefooghe, Sébastien Vérel, Marc Schoenauer, Juan Julián Merelo Guervós, Alexandre Quemy, Benjamin Bouvier, Jan Gmys:
Paradiseo: from a modular framework for evolutionary computation to the automated design of metaheuristics: 22 years of Paradiseo. 1522-1530 - João A. Duro, Daniel C. Oara, Ambuj K. Sriwastava, Yiming Yan, Shaul Salomon, Robin C. Purshouse:
Component-based design of multi-objective evolutionary algorithms using the Tigon optimization library. 1531-1539 - Pawel Renc, Patryk Orzechowski, Aleksander Byrski, Jaroslaw Was, Jason H. Moore:
EBIC.JL: an efficient implementation of evolutionary biclustering algorithm in Julia. 1540-1548
Workshop: Industrial applications of metaheuristics
- Jan Burak, Ole Jakob Mengshoel:
A multi-objective genetic algorithm for jacket optimization. 1549-1556 - Samuel Carvalho, Joe Sullivan, Douglas Mota Dias, Enrique Naredo, Conor Ryan:
Using grammatical evolution for modelling energy consumption on a computer numerical control machine. 1557-1563 - Vinícius Gandra, Hatice Çalik, Tony Wauters, Greet Vanden Berghe:
A heuristic approach to feasibility verification for truck loading. 1564-1569 - Daniel Hein, Daniel Labisch:
Trustworthy AI for process automation on a Chylla-Haase polymerization reactor. 1570-1578 - Kathrin Kefer, Roland Hanghofer, Patrick Kefer, Markus Stöger, Bernd Hofer, Michael Affenzeller, Stephan M. Winkler:
Multi tree operators for genetic programming to identify optimal energy flow controllers. 1579-1586 - Christian Klanke, Dominik R. Bleidorn, Christian Koslowski, Christian Sonntag, Sebastian Engell:
Simulation-based scheduling of a large-scale industrial formulation plant using a heuristics-assisted genetic algorithm. 1587-1595 - Anna V. Kononova, Ofer M. Shir, Teus Tukker, Pierluigi Frisco, Shutong Zeng, Thomas Bäck:
Addressing the multiplicity of solutions in optical lens design as a niching evolutionary algorithms computational challenge. 1596-1604 - William Reid, Aneta Neumann, Simon Ratcliffe, Frank Neumann:
Advanced mine optimisation under uncertainty using evolution. 1605-1613 - Moisés Silva-Muñoz, Gonzalo Calderon, Alberto Franzin, Hugues Bersini:
Determining a consistent experimental setup for benchmarking and optimizing databases. 1614-1621 - Okan Tunali, Ahmet Tugrul Bayrak, Víctor Sánchez-Anguix, Reyhan Aydogan:
Multi-objective evolutionary product bundling: a case study. 1622-1629
Workshop: International workshop on learning classifier systems
- Jordan T. Bishop, Marcus Gallagher, Will N. Browne:
A genetic fuzzy system for interpretable and parsimonious reinforcement learning policies. 1630-1638 - Tim Hansmeier, Marco Platzner:
An experimental comparison of explore/exploit strategies for the learning classifier system XCS. 1639-1647 - David Pätzel, Michael Heider, Alexander R. M. Wagner:
An overview of LCS research from 2020 to 2021. 1648-1656
Workshop: Landscape-aware heuristic search
- Christopher W. Cleghorn, Gabriela Ochoa:
Understanding parameter spaces using local optima networks: a case study on particle swarm optimization. 1657-1664 - Thomas Feutrier, Marie-Eléonore Kessaci, Nadarajen Veerapen:
Investigating the landscape of a hybrid local search approach for a timetabling problem. 1665-1673 - Melike D. Karatas, Ozgur E. Akman, Jonathan E. Fieldsend:
Towards population-based fitness landscape analysis using local optima networks. 1674-1682 - William B. Langdon, Justyna Petke, David Clark:
Dissipative polynomials. 1683-1691 - Jarrod Moses, Katherine M. Malan, Anna S. Bosman:
Analysing the loss landscape features of generative adversarial networks. 1692-1699 - Bernhard Werth, Johannes Karder, Andreas Beham, Stefan Wagner:
Dynamic landscape analysis for open-ended stacking. 1700-1707
Workshop: Neuroevolution at work
- Ivanoe De Falco, Antonio Della Cioppa, Angelo Marcelli, Umberto Scafuri, Luca Stellaccio, Ernesto Tarantino:
Prediction of personalized blood glucose levels in type 1 diabetic patients using a neuroevolution approach. 1708-1716 - Li Ding, Lee Spector:
Evolving neural selection with adaptive regularization. 1717-1725 - Eugenio Lomurno, Stefano Samele, Matteo Matteucci, Danilo Ardagna:
Pareto-optimal progressive neural architecture search. 1726-1734 - Zimeng Lyu, Shuchita Patwardhan, David Stadem, James Langfeld, Steven A. Benson, Seth Thoelke, Travis Desell:
Neuroevolution of recurrent neural networks for time series forecasting of coal-fired power plant operating parameters. 1735-1743 - Giorgia Nadizar, Eric Medvet, Felice Andrea Pellegrino, Marco Zullich, Stefano Nichele:
On the effects of pruning on evolved neural controllers for soft robots. 1744-1752 - Jörg Stork, Martin Zaefferer, Nils Eisler, Patrick Tichelmann, Thomas Bartz-Beielstein, A. E. Eiben:
Behavior-based neuroevolutionary training in reinforcement learning. 1753-1761 - Gustavo Adolfo Vargas Hakim, Efrén Mezura-Montes, Héctor-Gabriel Acosta-Mesa:
Hybrid encodings for neuroevolution of convolutional neural networks: a case study. 1762-1770
Workshop: Parallel and distributed evolutionary inspired methods
- Darren M. Chitty:
A partially asynchronous global parallel genetic algorithm. 1771-1778 - Grasiele Regina Duarte, Beatriz Souza Leite Pires de Lima:
An operation to promote diversity in evolutionary algorithms in a dynamic hybrid island model. 1779-1787 - Noriyuki Fujimoto, Kouki Nanai:
Solving QUBO with GPU parallel MOPSO. 1788-1794 - Matthew Andres Moreno, Santiago Rodriguez Papa, Charles Ofria:
Conduit: a C++ library for best-effort high performance computing. 1795-1800 - Giuseppe Petrosino, Federico Bergenti, Gianfranco Lombardo, Monica Mordonini, Agostino Poggi, Michele Tomaiuolo, Stefano Cagnoni:
Island model in ActoDatA: an actor-based implementation of a classical distributed evolutionary computation paradigm. 1801-1808
Workshop: Real-world applications of continuous and mixed-integer optimization
- Fateme Azimlu, Shahryar Rahnamayan, Masoud Makrehchi:
House price prediction using clustering and genetic programming along with conducting a comparative study. 1809-1816 - Burak Boyaci, Muhammad Ali Nayeem, Ahmed Kheiri:
A matheuristic approach for finding effective base locations and team configurations for north west air ambulance. 1817-1824 - Kyle Robert Harrison, Saber M. Elsayed, Ruhul A. Sarker, Ivan L. Garanovich, Terence Weir, Sharon G. Boswell:
Project portfolio selection with defense capability options. 1825-1826 - Hao Qiu, Leonardo Lucio Custode, Giovanni Iacca:
Black-box adversarial attacks using evolution strategies. 1827-1833 - Dmitriy Semenchikov, Anna Filippova, Dmitriy Volf, Nikolai A. Kovrizhnykh, Maxim Mironov, Jinying Zou, Ronghui Luo, Yuanming Zhu, Dapeng Chai, Huang Wei:
Evolutionary algorithms in high-dimensional radio access network optimization. 1834-1841
Workshop: Surrogate-assisted evolutionary optimisation
- Alessio Benavoli, Dario Azzimonti, Dario Piga:
Preferential Bayesian optimisation with skew gaussian processes. 1842-1850 - Laurens Bliek, Arthur Guijt, Sicco Verwer, Mathijs de Weerdt:
Black-box mixed-variable optimisation using a surrogate model that satisfies integer constraints. 1851-1859 - George De Ath, Richard M. Everson, Jonathan E. Fieldsend:
How Bayesian should Bayesian optimisation be? 1860-1869 - Rommel G. Regis:
A two-phase surrogate approach for high-dimensional constrained discrete multi-objective optimization. 1870-1878 - Pouya Rezazadeh Kalehbasti, Michael D. Lepech, Samarpreet Singh Pandher:
Augmenting high-dimensional nonlinear optimization with conditional GANs. 1879-1880
Workshop: Genetic and evolutionary computation in defense, security, and risk management
- Rahul Dubey, Sushil J. Louis:
Multi-objective evolutionary algorithms for distributed tactical control of heterogeneous agents. 1881-1888 - Claudio Ferretti, Martina Saletta:
Deceiving neural source code classifiers: finding adversarial examples with grammatical evolution. 1889-1897 - Sean N. Harris, Daniel R. Tauritz:
Competitive coevolution for defense and security: Elo-based similar-strength opponent sampling. 1898-1906 - Ying Zhao, Erik Hemberg, Nate Derbinsky, Gabino Mata, Una-May O'Reilly:
Simulating a logistics enterprise using an asymmetrical wargame simulation with soar reinforcement learning and coevolutionary algorithms. 1907-1915
Workshop: Swarm intelligence algorithms: Foundations, perspectives and challenges
- Tomas Kadavy, Michal Pluhacek, Adam Viktorin, Roman Senkerik:
Self-organizing migrating algorithm with clustering-aided migration and adaptive perturbation vector control. 1916-1922 - Seyed Jalaleddin Mousavirad, Gerald Schaefer, Diego Oliva, Salvador Hinojosa:
HCS-BBD: an effective population-based approach for multi-level thresholding. 1923-1930 - Seyed Jalaleddin Mousavirad, Gerald Schaefer, Mahshid Helali Moghadam, Mehrdad Saadatmand, Mahdi Pedram:
A population-based automatic clustering algorithm for image segmentation. 1931-1936 - Victor Parque:
A differential particle scheme and its application to PID parameter tuning of an inverted pendulum. 1937-1943 - Michal Pluhacek, Anezka Kazikova, Tomas Kadavy, Adam Viktorin, Roman Senkerik:
Explaining SOMA: the relation of stochastic perturbation to population diversity and parameter space coverage. 1944-1952
Workshop: Visualisation methods in genetic and evolutionary computation
- Tomofumi Kitamura, Alex Fukunaga:
Visualizing fitnesses and constraint violations in single-objective optimization. 1953-1960 - Marius N. Varga, Swen E. Gaudl, David J. Walker:
Many-objective population visualisation with geons. 1961-1969
Workshop: Student workshop
- Sylvain Clay, Lucien Mousin, Nadarajen Veerapen, Laetitia Jourdan:
CLAHC - custom late acceptance hill climbing: first results on TSP. 1970-1973 - Albert López Serrano, Teddy Nurcahyadi, Salim Bouamama, Christian Blum:
Negative learning ant colony optimization for the minimum positive influence dominating set problem. 1974-1977 - Alejandro Marrero, Eduardo Segredo, Coromoto León:
A parallel genetic algorithm to speed up the resolution of the algorithm selection problem. 1978-1981 - Maxim Pikalov, Vladimir Mironovich:
Automated parameter choice with exploratory landscape analysis and machine learning. 1982-1985 - Matvey Shnytkin, Denis Antipov:
The lower bounds on the runtime of the (1 + (λ, λ)) GA on the minimum spanning tree problem. 1986-1989 - Anish Thite, Mohan Dodda, Alex Liu, Pulak Agarwal, Jason Zutty:
Concurrent neural tree and data preprocessing AutoML for image classification. 1990-1993 - Aymeric Vié:
Population network structure impacts genetic algorithm optimisation performance. 1994-1997
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