An integer-coded chaotic particle swarm optimization for traveling salesman problem

Abstract

Traveling Salesman Problem (TSP) is one of NP-hard combinatorial optimization problems, which will experience "combination explosion" when the problem goes beyond a certain size. Therefore, it has been a hot topic to search an effective solving method. The general mathematical model of TSP is discussed, and its permutation and combination based model is presented. Based on these, Integer-coded Chaotic Particle Swarm Optimization for solving TSP is proposed. Where, particle is encoded with integer; chaotic sequence is used to guide global search; and particle varies its positions via "flying". With a typical 20-citys TSP as instance, the simulation experiment of comparing ICPSO with GA is carried out. Experimental results demonstrate that ICPSO is simple but effective, and better than GA at performance. © 2009 Springer-Verlag.