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Locating multiple optima of a problem is an important and challenging task for many real-world applications. In this paper, a random walk mutation strategy is proposed for differential evolution (DE) to handle multimodal optimization problems. The mutation strategy is able to find a balance between exploitation and exploration. First, the neighborhood and fitness information of individuals is incorporated...
The performance of a multimodal evolutionary algorithm is highly sensitive to the setting of population size. This paper introduces a generic archive technique to reduce the importance of properly setting the population size parameter. The proposed archive technique contains two components: subpopulation identification and convergence detection. The first component is used to identify subpopulations...
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