Performance Evaluation of Distributed GA Applying Different Genetic Operations with Selective Immigration

Abstract

In optimization process of genetic algorithm application, early convergence often happens through iterations of the generation alternation. In order to avoid such situation, individuals in GA should be sufficiently varied in whole generations(Diversity maintaining). Distributed genetic algorithm(DGA) is a promised approach for the diversity maintaining as well as acceleration of the calculation. This paper presents a DGA applying different genetic operations to each group(island) with selective immigration strategy. We discuss the performance especially resulting from the selective manner of immigration, through numerical experiments of traveling salesman problem, in terms of accuracy and diversity of the solutions.