Análise experimental de operadores de recombinação para o algorítimo de evolução diferencial

Detalhes bibliográficos
Ano de defesa: 2016
Autor(a) principal: Moises de Matos Botelho
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
UFMG
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/1843/BUBD-ADLLT3
Resumo: The search for improved solutions is a constant goal in all fields of engineering. Consequently, there is a great interest in the development of robust and efficient optimization techniques, to enable the solution of a wide range of problems in a fast and effective fashion. Amongst the algorithms commonly employed for the solution of optimization problems in engineering, Evolutionary Algorithms (EAs) are widespread across several disciplines. More specifically, the method known as Differential Evolution (DE) has yielded good performance for continuous optimization problems, particularly in low-dimensional spaces, and representsan interesting balance between simplicity of implementation and quality of the solutions found. As is the case with the vast majority of EA approaches, the performance of DE is strongly influenced by the specific variation operators (recombination and mutation) employed, aswell as by the values used for the algorithm parameters. This work presents a systematic investigation of the effects of sixteen recombination operators for real-coded spaces on the performanceof differential evolution. A unified notation is adopted for all operators, based on vector operations, and a modular, standardized implementation is presented in the form of an open-source package in R. The goal is to simplify the analysis of similarities among different operator variants, as well as the understanding of their effects on a population of candidate solutions. Another objective is to provide a standardized platform for the development and evaluation of new operators for Differential Evolution. To investigate and compare the performance of the recombination operators investigated in this work, a 28-problem benchmark set is used with dimensions 5 and 20. The results are discussed in terms of promising directions for the development of new operators for DE. The results also suggest that some recombination variants so far unused in the DE literature may be recommended in terms of improving the expected performance of the algorithm in problems of the two dimensions tested.