Parallel Genetic Algorithm Based Crowding Scheme Using Neighbouring Net Topology

Abstract

In this article, the notion of crowding is employed to maintain stable subpopulations at niches of a multi modal nonlinear function. In this work, we have attempted to parallelize the crowding scheme and hence, propose new concepts of net topology while devising the parallel scheme based on coarse grained parallelization. Besides, we have also proposed a new interconnection model which takes care of the intra deme migration. The use of Generalized Crossover (GC) operator is found to be superior to that of the scheme using two point crossover operators. The effect of different net topology, based on the neighbourhood structure, upon the solution is investigated. It was found that the net topology with second order neighbourhood structure is good enough to yield satisfactory results.