A Particle Swarm Optimization Algorithm with Ant Search for Solving Traveling Salesman Problem

摘要

By integrating the advantages of both PSO algorithm and ant colony algorithm, we present a hybrid discrete PSO algorithm with ant search for solving traveling salesman problem (TSP). In this algorithm, particle swarm search firstly, and worse chromosomes of the particle swarm is replaced by solutions obtained from ant colony search, so as to increase the diversity and improve the quality of the particle swarm . By setting the initial pheromone trail based on the best chromosome of all particles, the accumulation process of pheromone trail is greatly shortened, and the searching speed of ants is quickened. The numerical tests show that this algorithm is effective.