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GECCO 2022: Boston, MA, USA
- Jonathan E. Fieldsend, Markus Wagner:
GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9 - 13, 2022. ACM 2022, ISBN 978-1-4503-9237-2
Ant colony optimization and swarm intelligence
- Anoushka Alavilli, Mai Vu:
PLAN: a leafcutter ant colony optimization algorithm for ride-hailing services. 4-12 - Samia Sammoud
, Inès Alaya:
A new Ant colony optimization metaheuristic based on pheromone guided local search instead of constructive approach. 13-21 - Itshak Tkach, Tim Blackwell:
Measuring optimiser performance on a conical barrier tree benchmark. 22-30 - Fuda van Diggelen
Environment induced emergence of collective behavior in evolving swarms with limited sensing. 31-39 - Hong-Rui Wang, Chun-Hua Chen, Yun Li, Jun Zhang
Progressive sampling surrogate-assisted particle swarm optimization for large-scale expensive optimization. 40-48 - Qi-Te Yang
Social learning particle swarm optimization with two-surrogate collaboration for offline data-driven multiobjective optimization. 49-57
Complex systems (artificial life, artificial immune systems, generative and developmental systems, evolutionary robotics, evolvable hardware)
- Maxime Allard, Simón C. Smith, Konstantinos I. Chatzilygeroudis, Antoine Cully:
Hierarchical quality-diversity for online damage recovery. 58-67 - Sam Earle, Justin Snider, Matthew C. Fontaine, Stefanos Nikolaidis
Illuminating diverse neural cellular automata for level generation. 68-76 - Luca Grillotti, Antoine Cully:
Relevance-guided unsupervised discovery of abilities with quality-diversity algorithms. 77-85 - Bryan Lim, Alexander Reichenbach, Antoine Cully:
Learning to walk autonomously via reset-free quality-diversity. 86-94 - João Macedo, Lino Marques, Ernesto Costa:
Hybridizing bio-inspired strategies with infotaxis through genetic programming. 95-103 - Yoones Mirhosseini, Matan Yah Ben Zion
Adaptive phototaxis of a swarm of mobile robots using positive and negative feedback self-alignment. 104-112 - Eleni Nisioti, Clément Moulin-Frier:
Plasticity and evolvability under environmental variability: the joint role of fitness-based selection and niche-limited competition. 113-121 - Atoosa Parsa
Evolving programmable computational metamaterials. 122-129 - Joachim Winther Pedersen
Minimal neural network models for permutation invariant agents. 130-138 - Thomas Pierrot, Guillaume Richard, Karim Beguir, Antoine Cully:
Multi-objective quality diversity optimization. 139-147 - Federico Pigozzi, Yujin Tang, Eric Medvet, David Ha:
Evolving modular soft robots without explicit inter-module communication using local self-attention. 148-157 - Yulun Zhang
Deep surrogate assisted MAP-elites for automated hearthstone deckbuilding. 158-167 - Zonghao Huang, Quinn Wu, David Howard, Cynthia R. Sung:
EvoRobogami: co-designing with humans in evolutionary robotics experiments. 168-176
Evolutionary combinatorial optimization and metaheuristics
- Mohamed Elamine Athmani, Taha Arbaoui, Younes Mimene, Farouk Yalaoui:
Efficient heuristics and metaheuristics for the unrelated parallel machine scheduling problem with release dates and setup times. 177-185 - Jakob Bossek, Frank Neumann:
Exploring the feature space of TSP instances using quality diversity. 186-194 - Luke Branson, Andrew M. Sutton
Evolving labelings of graceful graphs. 195-203 - Lorenzo Canonne, Bilel Derbel:
Drils revisited: on the combination of perturbation with graybox optimization techniques. 204-212 - João Guilherme Cavalcanti Costa, Yi Mei
Guided local search with an adaptive neighbourhood size heuristic for large scale vehicle routing problems. 213-221 - Marcelo de Souza, Marcus Ritt:
Improved regression models for algorithm configuration. 222-231 - Lucas Kletzander, Tommaso Mannelli Mazzoli
Metaheuristic algorithms for the bus driver scheduling problem with complex break constraints. 232-240 - Albert López Serrano, Christian Blum:
A biased random key genetic algorithm applied to target set selection in viral marketing. 241-250 - Ole Jakob Mengshoel, Eirik Lund Flogard, Tong Yu, Jon Riege:
Understanding the cost of fitness evaluation for subset selection: Markov chain analysis of stochastic local search. 251-259 - Adel Nikfarjam, Aneta Neumann, Frank Neumann:
On the use of quality diversity algorithms for the traveling thief problem. 260-268 - Michal Witold Przewozniczek, Renato Tinós, Bartosz Frej, Marcin M. Komarnicki:
On turning black - into dark gray-optimization with the direct empirical linkage discovery and partition crossover. 269-277 - Guillem Rodríguez Corominas, Christian Blum, Maria J. Blesa:
Negative learning Ant colony optimization for network alignment. 278-286 - Sarah L. Thomson
On funnel depths and acceptance criteria in stochastic local search. 287-295 - Renato Tinós, Michal Witold Przewozniczek, Darrell Whitley:
Iterated local search with perturbation based on variables interaction for pseudo-boolean optimization. 296-304 - Hao Tong, Leandro L. Minku
What makes the dynamic capacitated Arc routing problem hard to solve: insights from fitness landscape analysis. 305-313 - Shaolin Wang
Local ranking explanation for genetic programming evolved routing policies for uncertain capacitated Arc routing problems. 314-322
Evolutionary machine learning
- Jordan T. Bishop, Marcus Gallagher
Pittsburgh learning classifier systems for explainable reinforcement learning: comparing with XCS. 323-331 - Joshua Cook, Kagan Tumer:
Fitness shaping for multiple teams. 332-340 - Giuseppe Cuccu
DiBB: distributing black-box optimization. 341-349 - Gaurav Dixit, Everardo Gonzalez, Kagan Tumer:
Diversifying behaviors for learning in asymmetric multiagent systems. 350-358 - Aaryan Dubey, Alexandre Hoppe Inoue, Pedro Terra Fernandes Birmann, Sammuel Ramos da Silva:
Evolutionary feature selection: a novel wrapper feature selection architecture based on evolutionary strategies. 359-366 - Diana Flores, Erik Hemberg, Jamal Toutouh, Una-May O'Reilly:
Coevolutionary generative adversarial networks for medical image augumentation at scale. 367-376 - David Howard, Humphrey Munn, Davide Dolcetti, Josh Kannemeyer, Nicole L. Robinson:
Assessing evolutionary terrain generation methods for curriculum reinforcement learning. 377-384 - Yuchen Liu, Sun-Yuan Kung, David Wentzlaff:
Evolving transferable neural pruning functions. 385-394 - Samuel López-Ruiz
Multi-objective framework for quantile forecasting in financial time series using transformers. 395-403 - Filip Matzner
Hyperparameter tuning in echo state networks. 404-412 - David Pätzel, Jörg Hähner:
The Bayesian learning classifier system: implementation, replicability, comparison with XCSF. 413-421 - Hiroki Shiraishi
Absumption based on overgenerality and condition-clustering based specialization for XCS with continuous-valued inputs. 422-430 - Hiroki Shiraishi
Can the same rule representation change its matching area?: enhancing representation in XCS for continuous space by probability distribution in multiple dimension. 431-439 - E. M. C. Sijben, Tanja Alderliesten
Multi-modal multi-objective model-based genetic programming to find multiple diverse high-quality models. 440-448 - Matheus Cândido Teixeira, Gisele L. Pappa:
Understanding AutoML search spaces with local optima networks. 449-457 - Thomas Uriot, Marco Virgolin, Tanja Alderliesten
On genetic programming representations and fitness functions for interpretable dimensionality reduction. 458-466
Evolutionary multiobjective optimization
- Mayowa Ayodele
Multi-objective QUBO solver: bi-objective quadratic assignment problem. 467-475 - Fodil Benali, Damien Bodénès, Cyril De Runz, Nicolas Labroche:
An enhanced adaptive geometry evolutionary algorithm using stochastic diversity mechanism. 476-483 - Vandana Bharti, Aryan Singhal, Anant Saxena, Bhaskar Biswas, Kaushal Kumar Shukla
Parallelization of corner sort with CUDA for many-objective optimization. 484-492 - Raphaël Cosson
Cost-vs-accuracy of sampling in multi-objective combinatorial exploratory landscape analysis. 493-501 - Raphaël Cosson
Multi-objective NK landscapes with heterogeneous objectives. 502-510 - Roy de Winter, Bas van Stein
Multi-point acquisition function for constraint parallel efficient multi-objective optimization. 511-519 - Benjamin Doerr, Omar El Hadri, Adrien Pinard:
The (1 + (λ, λ)) global SEMO algorithm. 520-528 - Daniel Herring
Reproducibility and baseline reporting for dynamic multi-objective benchmark problems. 529-537 - Yuri Cossich Lavinas, Marcelo Ladeira, Gabriela Ochoa, Claus Aranha:
Component-wise analysis of automatically designed multiobjective algorithms on constrained problems. 538-546 - Zhuo Liu, Xiaolin Xiao, Feng-Feng Wei
A classification-assisted level-based learning evolutionary algorithm for expensive multiobjective optimization problems. 547-555 - Manu Manuel
Region of interest based non-dominated sorting genetic algorithm-II: an invite and conquer approach. 556-564 - Annibale Panichella:
An improved Pareto front modeling algorithm for large-scale many-objective optimization. 565-573 - Vishal Singh Roha, Naveen Saini, Sriparna Saha, José G. Moreno:
Unsupervised framework for comment-based multi-document extractive summarization. 574-582 - Carlos Hernández, Oliver Schütze
A bounded archive based for bi-objective problems based on distance and e-dominance to avoid cyclic behavior. 583-591 - Lennart Schäpermeier
MOLE: digging tunnels through multimodal multi-objective landscapes. 592-600 - Ryoji Tanabe, Youhei Akimoto, Ken Kobayashi
A two-phase framework with a bézier simplex-based interpolation method for computationally expensive multi-objective optimization. 601-610 - Weijie Zheng, Benjamin Doerr:
Better approximation guarantees for the NSGA-II by using the current crowding distance. 611-619
Evolutionary numerical optimization
- Gjorgjina Cenikj, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korosec, Tome Eftimov:
SELECTOR: selecting a representative benchmark suite for reproducible statistical comparison. 620-629 - Armand Gissler
Learning rate adaptation by line search in evolution strategies with recombination. 630-638 - Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa:
CMA-ES with margin: lower-bounding marginal probability for mixed-integer black-box optimization. 639-647 - Ana Kostovska, Diederick Vermetten
The importance of landscape features for performance prediction of modular CMA-ES variants. 648-656 - Moritz Vinzent Seiler, Raphael Patrick Prager, Pascal Kerschke
A collection of deep learning-based feature-free approaches for characterizing single-objective continuous fitness landscapes. 657-665
Genetic algorithms
- Brahim Aboutaib, Andrew M. Sutton:
The influence of noise on multi-parent crossover for an island model GA. 666-674 - Anton Bouter, Peter A. N. Bosman:
GPU-accelerated parallel gene-pool optimal mixing in a gray-box optimization setting. 675-683 - Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann:
Niching-based evolutionary diversity optimization for the traveling salesperson problem. 684-693 - Preston Dunton, Darrell Whitley:
Reducing the cost of partition crossover on large MAXSAT problems: the PX-preprocessor. 694-702 - Arthur Guijt
Solving multi-structured problems by introducing linkage kernels into GOMEA. 703-711 - Liang-Jung Huang, Tian-Li Yu:
TAGA: a transfer-based black-box adversarial attack with genetic algorithms. 712-720 - Akarsh Kumar, Bo Liu, Risto Miikkulainen, Peter Stone:
Effective mutation rate adaptation through group elite selection. 721-729 - Erwan Lecarpentier, Paul Templier, Emmanuel Rachelson, Dennis G. Wilson:
LUCIE: an evaluation and selection method for stochastic problems. 730-738 - Elliot Meyerson, Xin Qiu, Risto Miikkulainen:
Simple genetic operators are universal approximators of probability distributions (and other advantages of expressive encodings). 739-748 - Adel Nikfarjam, Aneta Neumann, Frank Neumann:
Evolutionary diversity optimisation for the traveling thief problem. 749-756 - Darrell Whitley, Gabriela Ochoa:
Local optima organize into lattices under recombination: an example using the traveling salesman problem. 757-765
General evolutionary computation and hybrids
- André Biedenkapp
Theory-inspired parameter control benchmarks for dynamic algorithm configuration. 766-775 - George De Ath
MBORE: multi-objective Bayesian optimisation by density-ratio estimation. 776-785 - Finley J. Gibson, Richard M. Everson, Jonathan E. Fieldsend:
Guiding surrogate-assisted multi-objective optimisation with decision maker preferences. 786-795 - Mario Alejandro Hevia Fajardo
Hard problems are easier for success-based parameter control. 796-804 - Jonatan Klosko, Mateusz Benecki, Grzegorz Wcislo, Jacek Dajda, Wojciech Turek
High performance evolutionary computation with tensor-based acceleration. 805-813 - Youngmin Kim
Are evolutionary algorithms safe optimizers? 814-822 - Atsuhiro Miyagi, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Black-box min-max continuous optimization using CMA-ES with worst-case ranking approximation. 823-831 - Aneta Neumann, Denis Antipov, Frank Neumann:
Coevolutionary Pareto diversity optimization. 832-839 - Stefan Pricopie, Richard Allmendinger, Manuel López-Ibáñez, Clyde Fare, Matt Benatan, Joshua D. Knowles:
Expensive optimization with production-graph resource constraints: a first look at a new problem class. 840-848 - Penny Faulkner Rainford
Using phylogenetic analysis to enhance genetic improvement. 849-857 - Roberto Santana, Arnaud Liefooghe, Bilel Derbel:
Boomerang-shaped neural embeddings for NK landscapes. 858-866 - Diederick Vermetten, Hao Wang, Manuel López-Ibáñez, Carola Doerr, Thomas Bäck:
Analyzing the impact of undersampling on the benchmarking and configuration of evolutionary algorithms. 867-875 - Dmitry Vinokurov, Maxim Buzdalov
On optimal static and dynamic parameter choices for fixed-target optimization. 876-883 - Mateusz Zaborski, Jacek Mandziuk:
Improving LSHADE by means of a pre-screening mechanism. 884-892
Genetic programming
- Marko Durasevic, Lucija Planinic, Francisco Javier Gil Gala
Novel ensemble collaboration method for dynamic scheduling problems. 893-901 - Muhammad Sarmad Ali, Meghana Kshirsagar, Enrique Naredo, Conor Ryan:
Automated grammar-based feature selection in symbolic regression. 902-910 - Illya Bakurov, Marco Buzzelli, Mauro Castelli
Genetic programming for structural similarity design at multiple spatial scales. 911-919 - Fabrício Olivetti de França:
Transformation-interaction-rational representation for symbolic regression. 920-928 - Allan de Lima
Lexi2: lexicase selection with lexicographic parsimony pressure. 929-937 - Christian Haider, Fabrício Olivetti de França, Gabriel Kronberger, Bogdan Burlacu:
Comparing optimistic and pessimistic constraint evaluation in shape-constrained symbolic regression. 938-945 - Baihe He
Taylor genetic programming for symbolic regression. 946-954 - Zhixing Huang
Graph-based linear genetic programming: a case study of dynamic scheduling. 955-963 - William B. Langdon, Afnan A. Al-Subaihin, David Clark
Measuring failed disruption propagation in genetic programming. 964-972 - Dazhuang Liu, Marco Virgolin, Tanja Alderliesten
Evolvability degeneration in multi-objective genetic programming for symbolic regression. 973-981 - Yuanzhen Luo, Qiang Lu, Xilei Hu, Jake Luo, Zhiguang Wang:
Exploring hidden semantics in neural networks with symbolic regression. 982-990 - Jessica Mégane
Co-evolutionary probabilistic structured grammatical evolution. 991-999 - Edward R. Pantridge, Thomas Helmuth, Lee Spector:
Functional code building genetic programming. 1000-1008 - Jonas Schmitt, Harald Köstler:
Evolving generalizable multigrid-based helmholtz preconditioners with grammar-guided genetic programming. 1009-1018 - Dominik Sobania
Choose your programming copilot: a comparison of the program synthesis performance of github copilot and genetic programming. 1019-1027
Neuroevolution
- Michael Beukman
Procedural content generation using neuroevolution and novelty search for diverse video game levels. 1028-1037 - Alexander Chebykin
Evolutionary neural cascade search across supernetworks. 1038-1047 - Bryson Greenwood, Tyler McDonnell:
Surrogate-assisted neuroevolution. 1048-1056 - Santiago Miret, Vui Seng Chua, Mattias Marder, Mariano Phiellip, Nilesh Jain, Somdeb Majumdar:
Neuroevolution-enhanced multi-objective optimization for mixed-precision quantization. 1057-1065 - Yameng Peng
PRE-NAS: predictor-assisted evolutionary neural architecture search. 1066-1074 - Thomas Pierrot, Valentin Macé, Félix Chalumeau, Arthur Flajolet, Geoffrey Cideron, Karim Beguir, Antoine Cully, Olivier Sigaud, Nicolas Perrin-Gilbert:
Diversity policy gradient for sample efficient quality-diversity optimization. 1075-1083 - Kosmas Pinitas, Konstantinos Makantasis, Antonios Liapis, Georgios N. Yannakakis:
RankNEAT: outperforming stochastic gradient search in preference learning tasks. 1084-1092 - Nilotpal Sinha
Neural architecture search using progressive evolution. 1093-1101 - Bryon Tjanaka, Matthew C. Fontaine, Julian Togelius, Stefanos Nikolaidis
Approximating gradients for differentiable quality diversity in reinforcement learning. 1102-1111 - Kang Xu, Yan Ma, Wei Li:
Dynamics-aware novelty search with behavior repulsion. 1112-1120
Real world applications
- Mohammad Majid al-Rifaie, Tim Blackwell:
Swarm led tomographic reconstruction. 1121-1129 - Sebastian Angrick
Towards explainable real estate valuation via evolutionary algorithms. 1130-1138 - Rolando Armas, Hernán E. Aguirre, Daniel Orellana
Evolutionary bi-objective optimization for the electric vehicle charging stand infrastructure problem. 1139-1146 - Claude Carlet, Marko Djurasevic, Domagoj Jakobovic, Luca Mariot, Stjepan Picek:
Evolving constructions for balanced, highly nonlinear boolean functions. 1147-1155 - Tim Cofala, Oliver Kramer:
An evolutionary fragment-based approach to molecular fingerprint reconstruction. 1156-1163 - Zakaria Abdelmoiz Dahi
Genetic algorithm for qubits initialisation in noisy intermediate-scale quantum machines: the IBM case study. 1164-1172 - Leah R. M. Dickhoff
Adaptive objective configuration in bi-objective evolutionary optimization for cervical cancer brachytherapy treatment planning. 1173-1181 - Guanqiang Gao, Bin Xin, Yi Mei
A multi-objective evolutionary algorithm with new reproduction and decomposition mechanisms for the multi-point dynamic aggregation problem. 1182-1190 - Diksha Goel
Defending active directory by combining neural network based dynamic program and evolutionary diversity optimisation. 1191-1199 - Alexander Ivanov, Wesley Willett, Christian Jacob:
EvoIsland: interactive evolution via an island-inspired spatial user interface framework. 1200-1208 - Huijun Jin, Jieun Lee
RTune: a RocksDB tuning system with deep genetic algorithm. 1209-1217 - Luke Kelly, Martin Masek, Chiou Peng Lam:
Environment driven dynamic decomposition for cooperative coevolution of multi-agent systems. 1218-1226 - Fu Xing Long
Learning the characteristics of engineering optimization problems with applications in automotive crash. 1227-1236 - John MaGee, Viplove Arora, Mario Ventresca:
Identifying the source of an epidemic using particle swarm optimization. 1237-1244 - Santosh Kumar Mishra, Harshavardhan Kundarapu, Sayantan Mitra
Bug report summarization using multi-view multi-objective optimization framework. 1245-1253 - Ritwik Murali
Adapting novelty towards generating antigens for antivirus systems. 1254-1262 - Quentin Renau, Johann Dréo, Alain Peres, Yann Semet, Carola Doerr, Benjamin Doerr:
Automated algorithm selection for radar network configuration. 1263-1271 - Esteban Segarra Martinez, Stephen V. Maldonado, Annie S. Wu, Ryan P. McMahan, Xinliang Liu, Blake Oakley:
Effects of imputation strategy on genetic algorithms and neural networks on a binary classification problem. 1272-1280 - Daniel H. Stolfi, Grégoire Danoy:
Optimising autonomous robot swarm parameters for stable formation design. 1281-1289 - Matthew J. Turner
Analyzing multi-agent reinforcement learning and coevolution in cybersecurity. 1290-1298 - Aizaz Ul Haq, Niranjana Deshpande, AbdElRahman ElSaid, Travis Desell, Daniel E. Krutz:
Addressing tactic volatility in self-adaptive systems using evolved recurrent neural networks and uncertainty reduction tactics. 1299-1307 - Binxu Wang
High-performance evolutionary algorithms for online neuron control. 1308-1316
Search based software engineering
- Aitor Arrieta:
Is the revisited hypervolume an appropriate quality indicator to evaluate multi-objective test case selection algorithms? 1317-1326 - Aitor Arrieta:
Multi-objective metamorphic follow-up test case selection for deep learning systems. 1327-1335 - Pemma Reiter, Antonio M. Espinoza, Adam Doupé, Ruoyu Wang, Westley Weimer, Stephanie Forrest:
Improving source-code representations to enhance search-based software repair. 1336-1344 - Xinyi Wang, Tongxuan Yu, Paolo Arcaini
Mutation-based test generation for quantum programs with multi-objective search. 1345-1353
Theory
- Youhei Akimoto:
Monotone improvement of information-geometric optimization algorithms with a surrogate function. 1354-1362 - Samuel Baguley, Tobias Friedrich, Timo Kötzing, Xiaoyue Li, Marcus Pappik, Ziena Zeif:
Analysis of a gray-box operator for vertex cover. 1363-1371 - Duc-Cuong Dang, Anton V. Eremeev
Fast non-elitist evolutionary algorithms with power-law ranking selection. 1372-1380 - Benjamin Doerr, Amirhossein Rajabi, Carsten Witt
Simulated annealing is a polynomial-time approximation scheme for the minimum spanning tree problem. 1381-1389 - Benjamin Doerr, Yassine Ghannane
Towards a stronger theory for permutation-based evolutionary algorithms. 1390-1398 - Tobias Friedrich, Timo Kötzing, Aishwarya Radhakrishnan, Leon Schiller, Martin Schirneck, Georg Tennigkeit
Crossover for cardinality constrained optimization. 1399-1407 - Per Kristian Lehre:
Runtime analysis of competitive co-evolutionary algorithms for maximin optimisation of a bilinear function. 1408-1416 - Per Kristian Lehre, Xiaoyu Qin
Self-adaptation via multi-objectivisation: a theoretical study. 1417-1425 - Frank Neumann, Dirk Sudholt, Carsten Witt
The compact genetic algorithm struggles on Cliff functions. 1426-1433
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