Similar Kruskal-based Hybrid Particle Swarm Optimization Algorithm for Traveling Salesman Problem
Chao Wang · Yunchou yu guanli · 2014
This paper proposes a hybrid particle swarm optimization algorithm called SKHPSO to solve traveling salesman problem( TSP) by overcoming the premature convergence and low search efficiency of the standard particle swarm optimization algorithm( PSO). SKHPSO uses a similar Kruskal-based algorithm by which a specific means of implementation for Greedy Heuristic is given to get an initial feasible solution,as a member of the population in the PSO,then SKHPSO carries out the heuristic search with hybrid PSO algorithm combining the local search based on Lin-Kernighan local neighbor search operation and the global search,such as cross and replacement operations in single individual,which is used in genetic algorithm. The instances in the standard library,TSPLIB,are tested to verify our proposed algorithm. The results have shown that SKHPSO is effective to enhance the quality and efficiency of the solution.