Development of Island Model Genetic Algorithms with Different Genetic Operators

The genetic algorithms (GA) are evolutionary algorithms that imitate the evolution process of many living things. GA operates multipoint search, therefore the parallelization of the genetic operators are effective to shorten computational time. The island model GA is one of extended model of GA such that introducing parallel computation. This paper develops new algorithm of island model GA by introducing the concept of TCPSO (Two-swarm Cooperative Particle Swarm Optimization). In the proposed method, the individuals are updated by using different procedures which are determined depending on the categorized groups. Additionally, this paper conducts numerical experiments and the result indicates the effectiveness of the proposed algorithm. © 2021 The Institute of Electrical Engineers of Japan.