Routing Optimization for Dispatching Vehicles Based on an Improved Discrete Particle Swarm Optimization Algorithm with Mutation Operation

The shortcomings of some existing Particle Swarm Optimization (PSO) algorithms are analyzed and an improved discrete PSO algorithm with wheels topology, which updates the particles' positions by using swap operator, swap sequence and partially matched crossover based on the local PSO, is proposed in the present study. A mutation process in which all the particles are reinitialized when the swarm is stagnated is also introduced. This improved discrete algorithm is then applied to solve the vehicle routing problem (VRP) and a comparison of experimental results from it and other methods is conducted. Results show that the proposed algorithm gets better global convergence and is an effective approach in optimizing the VRP.