Selfish-gene Tolerant Generic Algorithms to solve large-scale constraint TSPs

Abstract

Large-scale distribution network simulation applicable to supply-chain management requires to solve hundreds of time-constraint large-scale (max 2000 cities) Traveling Salesman Problems (TSP) within interactive response time, with practicable optimality. To meet this requirement, a selfish-gene tolerant type GA is proposed. Here, each gene of an individual satisfies only its constraints selfishly, disregarding the constraints of other genes in the same individual. Further, to some extent, even individuals that violate constraints can survive over generations and are given the chance of improvement. Our experiment proves that this method provides expert-level solutions for time constraint largescale TSPs within a few seconds.