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EVOW
2005
Springer

Self-Adapting Evolutionary Parameters: Encoding Aspects for Combinatorial Optimization Problems

10 years 6 months ago
Self-Adapting Evolutionary Parameters: Encoding Aspects for Combinatorial Optimization Problems
Abstract. Evolutionary algorithms are powerful tools in search and optimization tasks with several applications in complex engineering problems. However, setting all associated parameters is not an easy task and the adaptation seems to be an interesting alternative. This paper aims to analyze the effect of self-adaptation of some evolutionary parameters of genetic algorithms (GAs). Here we intend to propose a flexible GAbased algorithm where only few parameters have to be defined by the user. Benchmark problems of combinatorial optimization were used to test the performance of the proposed approach.
Marcos H. Maruo, Heitor S. Lopes, Myriam Regattier
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where EVOW
Authors Marcos H. Maruo, Heitor S. Lopes, Myriam Regattieri Delgado
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