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A Multipopulation Genetic Algorithm Aimed at Multimodal Optimization by Patrick Siarry; Alain Pétrowski; Mourad Bessaou is a Engineering article available to read on EtoBox.

What is A Multipopulation Genetic Algorithm Aimed at Multimodal Optimization about?

This paper considers a new method that enables a genetic algorithm (GA) to identify and maintain multiple optima of a multimodal function, by creating subpopulations within the niches de®ned by the multiple optima, thus warranting a good `diversity'. The algorithm is based on a splitting of the traditional GA into a sequence of two processes. Since the GA behavior is determined by the exploration/exploitation balance, during the ®rst step (Exploration), the multipopulation GA coupled with a speciation method detects the potential niches by classifying `similar' individuals in the same population. Once the niches are detected, the algorithm achieves an intensi®cation (Exploitation), by allocating a separate portion of the search space to each population. These two steps are alternately performed at a given frequency. Empirical results obtained with F6 Schaffer`s function are then presented to show the reliability of the algorithm.

Who reads A Multipopulation Genetic Algorithm Aimed at Multimodal Optimization?

Author

Patrick Siarry; Alain Pétrowski; Mourad Bessaou

Publisher

Elsevier Science; Elsevier ; Elsevier Ltd.; Thomson Reuters; Elsevier BV (ISSN 0965-9978)

Published

2002

Language

EN

Field

Engineering (Physical Sciences)