Modified particle swarm algorithm for vehicle routing optimization of smart logistics

Early convergence and falling into local minimization easily were the defects as to the common algorithms which are used to settle the VRP. According to the problems, the modified particle swarm algorithm which is based on the extension theory is employed to solve the vehicle routing problem for smart logistics and distribution. During the course of optimization, the extension model of particle is established. After every iteration, the extension clustering method is used to divide the populations into groups, the different individual changes its position and speed differently, and the extension correlative method is introduced to break the balance of inter-population in the local minimization and escape the local minimization. The result of computational experiment shows that the extension particle swarm algorithm finding the optimal or nearly optimal solution effectively in comparison with other meta-heuristic algorithms. So it is an efficient method for vehicle routing problem of smart logistics.