关键词: 粒子群算法, 无水港, 多周期, 选址

Abstract: Traditional dry port location research often regard the dry port as a general logisticscenter, focusing on static location problem, failing to reflect dynamic planning process. Moreover, traditional Particle Swarm Optimization （PSO） algorithm is easy to fall into local optimum when dealing with discrete problems. A multi-stage?dry port location model from the perspective of “mighty seaport” is established, with the objective function of maximizing total return. Transit ratio constraint and service time constraint are considered in the constraint condition. An improved?PSO is designed to solve this problem. The result shows the exact locations of various stages. It is concluded that the improved algorithm enhances the local search ability and the global search ability. The feasibility and validity of the algorithm are also verified at the same time.

Key words: Particle Swarm Optimization（PSO）, dry port, multi-stage, location