Parallel Genetic Algorithm Based on Construction of Gene Pool in the Ordinary Network for TSP

Abstract

Though using parallel evolutionary algorithm to solve large-scale TSP problems is efficient, the parallel computer costs too much and the algorithm is not easy to expand. To address this issue, I propose a parallel genetic algorithm based on a gene pool under the existing network. To replace the group-genes in the evolutionary algorithm with the genes from the gene pool, the algorithm conducts greedy algorithm. The host process conducts greedy algorithm and improved evolutionary algorithm of Inver-over operator while the child process performs the improved hybrid genetic algorithms. Simulation results demonstrate that this algorithm achieves a better solution.