关键词: 时间窗, 取送一体化, 油耗, 动态聚类, 混合拓扑结构, 粒子群算法

Abstract: Aiming at the problem that the classic logistics distribution model considers the target, the constraints are not comprehensive enough and there are certain defects in the practical application, a integrated pickup and distribution vehicle routing problem on the basis of the classical model considering time window and fuel consumption (PDVRPTF) is constructed. Hybrid topological structure of particle swarm optimization based on k-medoids dynamic clustering is designed, which solves the problem that classical particle swarm optimization is easy to fall into local optimal solution when solving such models. The simulation results show that the improved particle swarm optimization can jump out of the local optimal solution quickly and converge to the global optimal solution quickly, which solve the logistics distribution path optimization problem effectively.

Key words: time window, integrated pickup and distribution, fuel consumption, dynamic clustering, hybrid topological structure, particle swarm optimization