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GECCO 2020: Cancún, Mexico
- Carlos Artemio Coello Coello:
GECCO '20: Genetic and Evolutionary Computation Conference, Cancún Mexico, July 8-12, 2020. ACM 2020, ISBN 978-1-4503-7128-5
Ant colony optimization and swarm intelligence
- Daniel Abitz, Tom Hartmann, Martin Middendorf:
A weighted population update rule for PACO applied to the single machine total weighted tardiness problem. 4-12 - Lucas Groleaz, Samba Ndojh Ndiaye
, Christine Solnon:
ACO with automatic parameter selection for a scheduling problem with a group cumulative constraint. 13-21 - Ismail Mohamed
A multiobjective optimization approach for market timing. 22-30 - Clodomir J. Santana Jr., Edward C. Keedwell, Ronaldo Menezes:
An approach to assess swarm intelligence algorithms based on complex networks. 31-39 - Valéria de Carvalho Santos, Fernando E. B. Otero, Colin G. Johnson
Exploratory path planning for mobile robots in dynamic environments with ant colony optimization. 40-48
Complex systems (artificial life/artificial immune systems/generative and developmental systems/evolutionary robotics/evolvable hardware)
- David M. Bossens
Learning behaviour-performance maps with meta-evolution. 49-57 - Jonathan C. Brant, Kenneth O. Stanley:
Diversity preservation in minimal criterion coevolution through resource limitation. 58-66 - Cédric Colas, Vashisht Madhavan, Joost Huizinga, Jeff Clune:
Scaling MAP-Elites to deep neuroevolution. 67-75 - David Rushing Dewhurst, Yi Li, Alexander Bogdan, Jasmine Geng:
Evolving ab initio trading strategies in heterogeneous environments. 76-84 - Stéphane Doncieux, Giuseppe Paolo
Novelty search makes evolvability inevitable. 85-93 - Matthew C. Fontaine, Julian Togelius
Covariance matrix adaptation for the rapid illumination of behavior space. 94-102 - Adam Gaier, Alexander Asteroth
Discovering representations for black-box optimization. 103-111 - Eric Medvet, Alberto Bartoli, Andrea De Lorenzo, Giulio Fidel:
Evolution of distributed neural controllers for voxel-based soft robots. 112-120 - Jean-Baptiste Mouret, Glenn Maguire:
Quality diversity for multi-task optimization. 121-129 - Huanneng Qiu
Towards crossing the reality gap with evolved plastic neurocontrollers. 130-138
Digital entertainment technologies and arts
- Jacob Schrum, Vanessa Volz, Sebastian Risi:
CPPN2GAN: combining compositional pattern producing networks and GANs for large-scale pattern generation. 139-147 - Jacob Schrum, Jake Gutierrez, Vanessa Volz, Jialin Liu
Interactive evolution and exploration within latent level-design space of generative adversarial networks. 148-156
Evolutionary combinatorial optimization and metaheuristics
- Mohamad Alissa
A deep learning approach to predicting solutions in streaming optimisation domains. 157-165 - Jakob Bossek
Dynamic bi-objective routing of multiple vehicles. 166-174 - Alex Guimarães Cardoso de Sá, Cristiano Guimarães Pimenta, Gisele Lobo Pappa, Alex Alves Freitas
A robust experimental evaluation of automated multi-label classification methods. 175-183 - Michael Foster
Do sophisticated evolutionary algorithms perform better than simple ones? 184-192 - Elaine Guerrero-Peña
Solving constrained combinatorial reverse auctions using MOEAs: a comparative study. 193-200 - Leticia Hernando, Alexander Mendiburu
Journey to the center of the linear ordering problem. 201-209 - Pavel Krömer, Jan Platos, Václav Snásel:
Solving the single row facility layout problem by differential evolution. 210-218 - Marcella S. R. Martins, Mohamed El Yafrani
Multi-layer local optima networks for the analysis of advanced local search-based algorithms. 219-227 - Sergey Polyakovskiy
Just-in-time batch scheduling subject to batch size. 228-235 - Yasha Pushak, Holger H. Hoos:
Advanced statistical analysis of empirical performance scaling. 236-244 - Yasha Pushak, Holger H. Hoos:
Golden parameter search: exploiting structure to quickly configure parameters in parallel. 245-253 - Swetha Varadarajan, L. Darrell Whitley, Gabriela Ochoa:
Why many travelling salesman problem instances are easier than you think. 254-262 - Jake Weiner, Andreas T. Ernst, Xiaodong Li, Yuan Sun
Automatic decomposition of mixed integer programs for lagrangian relaxation using a multiobjective approach. 263-270 - Yue Xie, Aneta Neumann
Specific single- and multi-objective evolutionary algorithms for the chance-constrained knapsack problem. 271-279
Evolutionary machine learning
- Eseoghene Ben-Iwhiwhu
Evolving inborn knowledge for fast adaptation in dynamic POMDP problems. 280-288 - Garrett Bingham, William Macke, Risto Miikkulainen:
Evolutionary optimization of deep learning activation functions. 289-296 - Victor Costa
Exploring the evolution of GANs through quality diversity. 297-305 - Grant Dick, Caitlin A. Owen
Feature standardisation and coefficient optimisation for effective symbolic regression. 306-314 - AbdElRahman ElSaid
Improving neuroevolutionary transfer learning of deep recurrent neural networks through network-aware adaptation. 315-323 - Benjamin P. Evans
Improving generalisation of AutoML systems with dynamic fitness evaluations. 324-332 - Germán González-Almagro
Improving constrained clustering via decomposition-based multiobjective optimization with memetic elitism. 333-341 - Motoki Horiuchi, Masaya Nakata:
Self-adaptation of XCS learning parameters based on learning theory. 342-349 - Mojan Javaheripi, Mohammad Samragh, Tara Javidi
GeneCAI: genetic evolution for acquiring compact AI. 350-358 - Pawel Liskowski, Krzysztof Krawiec
Program synthesis as latent continuous optimization: evolutionary search in neural embeddings. 359-367 - Yi Liu, Will N. Browne
Absumption and subsumption based learning classifier systems. 368-376 - Trung B. Nguyen
Relatedness measures to aid the transfer of building blocks among multiple tasks. 377-385 - Damien O'Neill, Bing Xue, Mengjie Zhang:
Neural architecture search for sparse DenseNets with dynamic compression. 386-394 - Abubakar Siddique, Will N. Browne
Lateralized learning for robustness against adversarial attacks in a visual classification system. 395-403 - Anthony Stein
XCS classifier system with experience replay. 404-413 - Yujin Tang, Duong Nguyen, David Ha:
Neuroevolution of self-interpretable agents. 414-424 - Jamal Toutouh, Erik Hemberg, Una-May O'Reilly:
Re-purposing heterogeneous generative ensembles with evolutionary computation. 425-434 - Thomas Uriot, Dario Izzo:
Safe crossover of neural networks through neuron alignment. 435-443 - Hang Xu, Bing Xue, Mengjie Zhang:
Segmented initialization and offspring modification in evolutionary algorithms for bi-objective feature selection. 444-452 - Connor Yates, Reid Christopher, Kagan Tumer:
Multi-fitness learning for behavior-driven cooperation. 453-461
Evolutionary multiobjective optimization
- Nicolas Berveglieri, Bilel Derbel, Arnaud Liefooghe
Designing parallelism in surrogate-assisted multiobjective optimization based on decomposition. 462-470 - Martin Binder, Julia Moosbauer, Janek Thomas, Bernd Bischl:
Multi-objective hyperparameter tuning and feature selection using filter ensembles. 471-479 - Salvador Botello-Aceves
Computation of the improvement directions of the Pareto front and its application to MOEAs. 480-488 - Jonathan E. Fieldsend:
Data structures for non-dominated sets: implementations and empirical assessment of two decades of advances. 489-497 - Linjun He, Auraham Camacho, Hisao Ishibuchi:
Another difficulty of inverted triangular pareto fronts for decomposition-based multi-objective algorithms. 498-506 - Hisao Ishibuchi, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima
Effects of dominance resistant solutions on the performance of evolutionary multi-objective and many-objective algorithms. 507-515 - Sumit Mishra
If unsure, shuffle: deductive sort is Θ(MN3), but O(MN2) in expectation over input permutations. 516-523 - Yang Nan, Ke Shang, Hisao Ishibuchi:
What is a good direction vector set for the R2-based hypervolume contribution approximation. 524-532 - Yoshihiko Ozaki
Multiobjective tree-structured parzen estimator for computationally expensive optimization problems. 533-541 - Geoffrey Pruvost
Surrogate-assisted multi-objective combinatorial optimization based on decomposition and walsh basis. 542-550 - Vahid Roostapour, Jakob Bossek, Frank Neumann:
Runtime analysis of evolutionary algorithms with biased mutation for the multi-objective minimum spanning tree problem. 551-559 - Xiaoran Ruan, Ke Li, Bilel Derbel, Arnaud Liefooghe
Surrogate assisted evolutionary algorithm for medium scale multi-objective optimisation problems. 560-568 - Michal K. Tomczyk
On the elicitation of indirect preferences in interactive evolutionary multiple objective optimization. 569-577 - Pablo Valledor Pellicer, Miguel Iglesias Escudero, Silvino Fernández Alzueta, Kalyanmoy Deb:
Gap finding and validation in evolutionary multi- and many-objective optimization. 578-586 - Xilu Wang, Yaochu Jin
Transfer learning for gaussian process assisted evolutionary bi-objective optimization for objectives with different evaluation times. 587-594 - Saúl Zapotecas Martínez
Constraint handling within MOEA/D through an additional scalarizing function. 595-602
Evolutionary numerical optimization
- Anton Bouter, Stefanus C. Maree, Tanja Alderliesten
Leveraging conditional linkage models in gray-box optimization with the real-valued gene-pool optimal mixing evolutionary algorithm. 603-611 - Ryan Dieter Lang, Andries P. Engelbrecht:
Distributed random walks for fitness landscape analysis. 612-619 - Jialin Liu
Versatile black-box optimization. 620-628 - Jesús-Adolfo Mejía-de-Dios
A surrogate-assisted metaheuristic for bilevel optimization. 629-635 - Naoki Sakamoto, Eiji Semmatsu, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto:
Deep generative model for non-convex constraint handling. 636-644 - Ryoji Tanabe:
Analyzing adaptive parameter landscapes in parameter adaptation methods for differential evolution. 645-653 - Diederick Vermetten
Towards dynamic algorithm selection for numerical black-box optimization: investigating BBOB as a use case. 654-662
Genetic algorithms
- Marwan F. Abdelatti, Manbir Singh Sodhi:
An improved GPU-accelerated heuristic technique applied to the capacitated vehicle routing problem. 663-671 - Pedro Carvalho
AutoLR: an evolutionary approach to learning rate policies. 672-680 - Anh Viet Do
Evolving diverse sets of tours for the travelling salesperson problem. 681-689 - Yohanes Bimo Dwianto
Adaptively preserving solutions in both feasible and infeasible regions on generalized multiple constraint ranking. 690-698 - Elena Gutiérrez, Takamasa Okudono, Masaki Waga
Genetic algorithm for the weight maximization problem on weighted automata. 699-707 - Marcin M. Komarnicki
Comparative mixing for DSMGA-II. 708-716 - Alberto Francisco Kummer Neto, Luciana S. Buriol, Olinto César Bassi de Araújo:
A biased random key genetic algorithm applied to the VRPTW with skill requirements and synchronization constraints. 717-724 - Tien Thanh Nguyen, Nang Van Pham
Multi-layer heterogeneous ensemble with classifier and feature selection. 725-733 - Gustavo Post Sabin, Telma Woerle de Lima, Anderson da Silva Soares:
New search operators for node-depth based encoding. 734-741 - Michal Witold Przewozniczek
On measuring and improving the quality of linkage learning in modern evolutionary algorithms applied to solve partially additively separable problems. 742-750 - German Treimun-Costa, Elizabeth Montero, Gabriela Ochoa, Nicolás Rojas-Morales:
Modelling parameter configuration spaces with local optima networks. 751-759 - L. Darrell Whitley, Hernán E. Aguirre, Andrew M. Sutton
Understanding transforms of pseudo-boolean functions. 760-768
General evolutionary computation and hybrids
- Adefunke Akinola, Mark Wineberg:
Using implicit multi-objectives properties to mitigate against forgetfulness in coevolutionary algorithms. 769-777 - Jakob Bossek, Carola Doerr
Initial design strategies and their effects on sequential model-based optimization: an exploratory case study based on BBOB. 778-786 - George De Ath
ϵ-shotgun: ϵ-greedy batch bayesian optimisation. 787-795 - Benjamin Doerr, Martin S. Krejca:
Bivariate estimation-of-distribution algorithms can find an exponential number of optima. 796-804 - Benjamin Doerr, Weijie Zheng:
From understanding genetic drift to a smart-restart parameter-less compact genetic algorithm. 805-813 - Olivier Francon, Santiago Gonzalez, Babak Hodjat, Elliot Meyerson, Risto Miikkulainen, Xin Qiu, Hormoz Shahrzad:
Effective reinforcement learning through evolutionary surrogate-assisted prescription. 814-822 - George T. Hall
Analysis of the performance of algorithm configurators for search heuristics with global mutation operators. 823-831 - Mario Alejandro Hevia Fajardo
On the choice of the parameter control mechanism in the (1+(λ, λ)) genetic algorithm. 832-840 - Anja Jankovic, Carola Doerr
Landscape-aware fixed-budget performance regression and algorithm selection for modular CMA-ES variants. 841-849 - Alexandre D. Jesus
Algorithm selection of anytime algorithms. 850-858 - Marcin Karmelita, Tomasz P. Pawlak:
CMA-ES for one-class constraint synthesis. 859-867 - Frederik Rehbach, Martin Zaefferer, Boris Naujoks
Expected improvement versus predicted value in surrogate-based optimization. 868-876 - Jakob Richter, Junjie Shi, Jian-Jia Chen
Model-based optimization with concept drifts. 877-885 - Dolly Sapra
An evolutionary optimization algorithm for gradually saturating objective functions. 886-893 - Julian Schulte, Volker Nissen:
Sensitivity analysis in constrained evolutionary optimization. 894-902 - Diederick Vermetten
Integrated vs. sequential approaches for selecting and tuning CMA-ES variants. 903-912
Genetic programming
- Baligh Al-Helali, Qi Chen
Multi-tree genetic programming for feature construction-based domain adaptation in symbolic regression with incomplete data. 913-921 - Qi Chen
Improving symbolic regression based on correlation between residuals and variables. 922-930 - Léo Françoso Dal Piccol Sotto, Paul Kaufmann, Timothy Atkinson, Roman Kalkreuth
A study on graph representations for genetic programming. 931-939 - David Hodan, Vojtech Mrazek
Semantically-oriented mutation operator in cartesian genetic programming for evolutionary circuit design. 940-948 - Stephen Kelly, Jacob Newsted, Wolfgang Banzhaf, Cedric Gondro:
A modular memory framework for time series prediction. 949-957 - Jirí Kubalík, Erik Derner, Robert Babuska:
Symbolic regression driven by training data and prior knowledge. 958-966 - William G. La Cava
Genetic programming approaches to learning fair classifiers. 967-975 - Uriel López, Leonardo Trujillo, Sara Silva
Unlabeled multi-target regression with genetic programming. 976-984 - Luca Manzoni, Domagoj Jakobovic, Luca Mariot, Stjepan Picek, Mauro Castelli
Towards an evolutionary-based approach for natural language processing. 985-993 - Edward R. Pantridge, Lee Spector:
Code building genetic programming. 994-1002 - Christian Raymond, Qi Chen
Adaptive weighted splines: a new representation to genetic programming for symbolic regression. 1003-1011 - Jonas Schmitt
Constructing efficient multigrid solvers with genetic programming. 1012-1020 - Omar M. Villanueva, Leonardo Trujillo, Daniel E. Hernández
Novelty search for automatic bug repair. 1021-1028 - Thomas Welsch, Vitaliy Kurlin
Synthesis through unification genetic programming. 1029-1036 - David Wittenberg
DAE-GP: denoising autoencoder LSTM networks as probabilistic models in estimation of distribution genetic programming. 1037-1045
Real world applications
- Philipp Back
Towards sustainable forest management strategies with MOEAs. 1046-1054 - Alessandro Calò, Paolo Arcaini
Simultaneously searching and solving multiple avoidable collisions for testing autonomous driving systems. 1055-1063 - Marko Djurasevic, Domagoj Jakobovic, Stjepan Picek:
One property to rule them all?: on the limits of trade-offs for S-boxes. 1064-1072 - V. Drouet, Sébastien Vérel
Surrogate-assisted asynchronous multiobjective algorithm for nuclear power plant operations. 1073-1081 - Thomas Gossuin, Didier Garray, Vincent Kelner:
Multi-objective optimal distribution of materials in hybrid components. 1082-1088 - Maxfield E. Green, Todd F. DeLuca, Karl WD. Kaiser:
Modeling wildfire using evolutionary cellular automata. 1089-1097 - Mohammad Haqqani, Xiaodong Li, Xinghuo Yu:
Non-deterministic journey planning in multi-modal transportation networks: a meta-heuristic approach. 1098-1106 - Ya-Hui Jia, Yi Mei
A memetic level-based learning swarm optimizer for large-scale water distribution network optimization. 1107-1115 - Matthew Barrie Johns, Herman A. Mahmoud
Adaptive augmented evolutionary intelligence for the design of water distribution networks. 1116-1124 - Mairin Kroes, Lucian Petrica, Sorin Cotofana
Evolutionary bin packing for memory-efficient dataflow inference acceleration on FPGA. 1125-1133 - Miguel Leon, Christoffer Parkkila, Jonatan Tidare
Impact of NSGA-II objectives on EEG feature selection related to motor imagery. 1134-1142 - Nuno Lourenço
Evolving energy demand estimation models over macroeconomic indicators. 1143-1149 - Mehdi Neshat
Optimisation of large wave farms using a multi-strategy evolutionary framework. 1150-1158 - Nirav Patel, N. S. Narayanaswamy, Alok Joshi:
Hybrid genetic algorithm for ridesharing with timing constraints: efficiency analysis with real-world data. 1159-1167 - Aaron Scott Pope, Daniel R. Tauritz
Automated design of multi-level network partitioning heuristics employing self-adaptive primitive granularity control. 1168-1176 - Frederik Rehbach, Lorenzo Gentile, Thomas Bartz-Beielstein
Variable reduction for surrogate-based optimization. 1177-1185 - Qurrat Ul Ain
A genetic programming approach to feature construction for ensemble learning in skin cancer detection. 1186-1194 - Zachary Wilkins, Nur Zincir-Heywood:
COUGAR: clustering of unknown malware using genetic algorithm routines. 1195-1203
Search-based software engineering
- Nasser M. Albunian, Gordon Fraser, Dirk Sudholt:
Causes and effects of fitness landscapes in unit test generation. 1204-1212 - Muhammad Sheraz Anjum
Scalability analysis of grammatical evolution based test data generation. 1213-1221 - Aitor Arrieta, Joseba Andoni Agirre, Goiuria Sagardui
Seeding strategies for multi-objective test case selection: an application on simulation-based testing. 1222-1231 - Mahmoud A. Bokhari
Towards rigorous validation of energy optimisation experiments. 1232-1240 - Ryan E. Dougherty
Genetic algorithms for redundancy in interaction testing. 1241-1249 - Diego Fernandes da Silva, Luiz Fernando Okada, Thelma Elita Colanzi, Wesley K. G. Assunção
Enhancing search-based product line design with crossover operators. 1250-1258
Theory
- Denis Antipov, Benjamin Doerr, Vitalii Karavaev:
The (1 + (λ, λ)) GA is even faster on multimodal problems. 1259-1267 - Denis Antipov, Maxim Buzdalov, Benjamin Doerr:
Fast mutation in crossover-based algorithms. 1268-1276 - Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt:
More effective randomized search heuristics for graph coloring through dynamic optimization. 1277-1285 - Jakob Bossek, Katrin Casel, Pascal Kerschke
The node weight dependent traveling salesperson problem: approximation algorithms and randomized search heuristics. 1286-1294 - Maxim Buzdalov, Benjamin Doerr, Carola Doerr, Dmitry Vinokurov:
Fixed-target runtime analysis. 1295-1303 - Benjamin Doerr:
Does comma selection help to cope with local optima? 1304-1313 - Amirhossein Rajabi
Self-adjusting evolutionary algorithms for multimodal optimization. 1314-1322 - Pietro S. Oliveto, Dirk Sudholt, Carsten Witt
A tight lower bound on the expected runtime of standard steady state genetic algorithms. 1323-1331
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