A strategy adaptive genetic algorithm for solving the travelling salesman problem

摘要: This paper presents a Strategy adaptive Genetic Algorithm to address wide range of sequencing discrete optimization problems. As for the performance analysis, we have applied our algorithm on Travelling Salesman Problem(TSP).Here present an innovative crossover scheme which selects strategy from consortium three such strategies, choice being decided partly by ability produce fitter off springs and chance. We maintained account each in producing fit adopting model similar The Ant Colony Optimization. also propose new variant Order Crossover retains some best edges during inheritance process. Along with conventional mutation methods developed greedy inversion is incorporated only if operation leads more economical traversal. provides better results compared other heuristics, evident experimental their comparisons those obtained using algorithms.