Examining the Effect of Elitism in Cellular Genetic Algorithms Using Two Neighborhood Structures
Elitism has a large effect on the search ability of evolutionary algorithms. Many studies, however, did not discuss its different implementations in cellular algorithms. Usually a replacement policy called “replace-if-better” is applied to each cell in cellular algorithms as a kind of elitism. In this paper, we examine three implementations of elitism. One is global elitism where a prespecified number of the best individuals in the entire population are viewed as being the elite. The replace-if-better policy is applied only to the globally best individuals. Another scheme is local elitism where an individual is viewed as being the elite if it is the best among its neighbors. The replace-if-better policy is applied only to the locally best individuals. The other scheme is cell-wise elitism where the replace-if-better policy is applied to all individuals. Effects of elitism are examined through computational experiments using a cellular genetic algorithm with two neighborhood structures. One is for local competition among neighbors. This competition neighborhood is used in the local elitism to determine the locally best individuals. The other is for local selection of parents. This selection neighborhood is also called the mating neighborhood. Since we have the two neighborhood structures, we can specify the size of the competition neighborhood for the implementation of the local elitism independent of the selection neighborhood for mating. Experimental results show that the use of the replace-if-better policy at all cells is not always the best choice.
KeywordsKnapsack Problem Neighborhood Structure Good Individual Local Selection Local Competition
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