关键词: 车辆作业调度；智慧物流园区；改进粒子群算法

Abstract: In order to solve the problem of vehicle operation scheduling efficiency in freight serviceoriented logistics parks, this paper takes the shortest total operation time in the logistics park as the optimization goal, and establishes a vehicle operation scheduling model. By introducing the nonlinear dynamic inertia weight factor, an improved particle swarm optimization algorithm is designed to solve the problem, which can improve the solution efficiency and avoid falling into the local optimum. Numerical experiments verify that the vehicle operation scheduling scheme obtained by the improved particle swarm optimization algorithm has a good time optimization effect. At the same time, through the comparative analysis with the standard particle swarm optimization and genetic algorithm, it is verified that the optimized particle swarm optimization algorithm has higher solving efficiency and better solving results.

Key words: Vehicle operation scheduling; Smart logistics parks; Improvements to the particle swarm algorithm