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Advances in Operations Research(1)
GECCO 2015 - Proceedings of the 2015 Genetic and Evolutionary Computation Conference(1)
GECCO 2016 Companion - Proceedings of the 2016 Genetic and Evolutionary Computation Conference(1)
GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference(1)
GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion(1)
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scopus(9)
A set-oriented MOEA/D
Conference ObjectAbstract: The working principles of the well-established multi-objective evolutionary algorithm Moea/d reliesPalabras claves:Combinatorial optimization, decomposition, Evolutionary algorithms, many-objective optimization, Multi-Autores:Derbel B., Hernán E. Aguirre, Liefooghe A., Tanaka K., Verel S., Zhang Q.Fuentes:scopusDesigning parallelism in surrogate-assisted multiobjective optimization based on decomposition
Conference ObjectAbstract: On the one hand, surrogate-assisted evolutionary algorithms are established as a method of choice foPalabras claves:Multiobjective optimization, Parallelism benchmarking, SurrogatesAutores:Berveglieri N., Derbel B., Hernán E. Aguirre, Liefooghe A., Tanaka K., Zhang Q.Fuentes:scopusDynamic compartmental models for algorithm analysis and population size estimation
Conference ObjectAbstract: Dynamic Compartmental Models (DCM) can be used to study the population dynamics of Multi- and Many-oPalabras claves:compartmental models, empirical study, Genetic Algorithms, Modeling, multi-objective optimization, Working principles of evolutionary computingAutores:Derbel B., Hernán E. Aguirre, Liefooghe A., Monzón H., Tanaka K., Verel S.Fuentes:scopusMulti-objective local search based on decomposition
Conference ObjectAbstract: It is generally believed that Local search (Ls) should be used as a basic tool in multi-objective evPalabras claves:Autores:Derbel B., Hernán E. Aguirre, Liefooghe A., Tanaka K., Zhang Q.Fuentes:scopusPareto dominance-based MOEAs on problems with difficult pareto set topologies
Conference ObjectAbstract: Despite the extensive application of multi-objective evolutionary algorithms (MOEAs) to solve multi-Palabras claves:Differential Evolution, multi-objective optimization, Recombination operators, Selection, Working principles of evolutionary computingAutores:Derbel B., Hernán E. Aguirre, Liefooghe A., Marca Y., Tanaka K., Verel S., Zapotecas-Martínez S.Fuentes:scopusInjecting CMA-ES into MOEA/D
Conference ObjectAbstract: MOEA/D is an aggregation-based evolutionary algorithm which has been proved extremely efficient andPalabras claves:Covariance matrix adaption evolution strategy, Decomposition-based moeas, multi-objective optimizationAutores:Brockhoff D., Derbel B., Hernán E. Aguirre, Liefooghe A., Tanaka K., Zapotecas-Martínez S.Fuentes:scopusLearning Variable Importance to Guide Recombination on Many-Objective Optimization
Conference ObjectAbstract: There are numerous many-objective real-world problems in various application domains for which it isPalabras claves:evolutionary algorithm, Machine learning, many-objective optimization, multi-objective optimization, random forest, variable importanceAutores:Daolio F., Derbel B., Hernán E. Aguirre, Liefooghe A., Sagawa M., Tanaka K., Verel S.Fuentes:scopusLocal search move strategies within MOEA/D
Conference ObjectAbstract: Local search (LS) is at the cornerstone of many advanced heuristics for single-objective combinatoriPalabras claves:decomposition, local search, multi-objective optimizationAutores:Derbel B., Hernán E. Aguirre, Liefooghe A., Tanaka K., Zhang Q.Fuentes:scopusUnderstanding Population Dynamics in Multi- and Many-Objective Evolutionary Algorithms for High-Resolution Approximations
ArticleAbstract: Achieving a high-resolution approximation and hitting the Pareto optimal set with some if not all mePalabras claves:Autores:Derbel B., Hernán E. Aguirre, Liefooghe A., Monzón Maldonado H., Tanaka K., Verel S.Fuentes:scopus