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 defined 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 G A behavior is determined by the exploration/exploitation balance, during the first step (Exploration), the multipopulation genetic algorithm 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 intensification (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.
CITATION STYLE
Mourad, M. B., Pétrowski, A., & Siarry, P. (2000). Island model cooperating with speciation for multimodal optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1917, pp. 437–446). Springer Verlag. https://doi.org/10.1007/3-540-45356-3_43
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