Island Model Cooperating with Speciation for Multimodal Optimization

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 GA 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.

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