Study of Multi-depots Goods Transhipment Vehicle Scheduling Problem Model and Its Particle Swarm and Ant Colony Optimization Hybrid Arithmetic

To obtain a global solution to the multi-depots goods transshipment vehicle scheduling problem (VSP), in this study, we established VSP models. The optimization course is as follows:First, set up a particle position vector to obtain a goods transshipment point and then assign goods to vehicles. Second, establish a Tabu list for the ant colony optimization (ACO) to obtain a vehicle route. The particle swarm arithmetic then evaluates and filters the vehicle scheduling results by optimization, which continues until it meets the terminate qualification. The hybrid arithmetic optimizes the transportation point and vehicle route, and the position and number of the transportation point are changeable, which makes it easy to obtain a global solution. Simulation results show that the hybrid arithmetic is effective for the multi-depots goods transshipment vehicle scheduling problem.