Effects of Using Two Neighborhood Structures in Cellular Genetic Algorithms for Function Optimization

We implement a cellular genetic algorithm with two neighborhood structures following the concept of structured demes: One is for interaction among individuals and the other is for mating. The effect of using these two neighborhood structures on the search ability of cellular genetic algorithms is examined through computational experiments on function optimization problems. Experimental results show that good results are obtained from the combination of a small interaction neighborhood and a large mating neighborhood. This relation in the size of the two neighborhood structures coincides with many cases of biological evolution in nature such as plants and territorial animals. It is also shown that the search ability of cellular genetic algorithms is deteriorated by the opposite combination of the two neighborhood structures.