Abstract: In the logistics and transportation industry, container transportation has become a major transport businesses of ports along the Yangtze River. Container handling process, and especially the container stowing process has directly affected the liner transport efficiency. The stowage planning development is essential for liner transportation. In this paper, the linear programming problem is solved by CPLEX, and a Greedy Method (GM) and a Genetic Algorithm (GA) are designed to solve the problem of the large-scale container ship stowing problem. In the simulation experiment, GA can obtain the same solution with CPLEX in small cases and the validity of the GA is verified. In large-scale cases, CPLEX cannot solve this problem, but the result of GA is superior to the GM, It is proved that the result of GA is superior to the solution of GM and the efficiency of liner transportation also improves and reduces the cost of shipping companies, which can guide the formulation of container stowing plan for ports along the Yangtze River.

Key words: stowage planning, genetic algorithm, greedy method, multiple container ports, reshuffle

摘要： 在物流运输行业中,集装箱运输已经成为我国长江沿岸各大港口的主要运输业务。集装箱的处理流程,尤其是集装箱的配载过程直接影响着班轮的运输效率,配载方案的制定对班轮运输起着至关重要的作用。本文针对多港口集装箱船的配载情况,利用CPLEX对该线性规划问题进行求解,并设计遗传算法和贪婪算法对长江沿岸多港口集装箱船配载情形进行对比。通过仿真实验,在小规模时遗传算法与CPLEX求解的精确解相同,验证了遗传算法的有效性。并且在大规模运输情形下,遗传算法得出的结果明显优于贪婪策略,进一步说明了遗传算法是行之有效的。得出的解决方案降低了班轮公司的运输成本,提高了港口的工作效率,对我国长江沿岸港口集装箱配载计划的制定具有一定的指导作用。

关键词: 配载计划, 遗传算法, 贪婪策略, 多港口, 翻箱