摘要
在港口作业过程中,集卡作为一种重要的基础设施工具,在港岸和堆场之间起着运输集装箱的重要作用。同时,作为集装箱的存储、转运基地,堆场空间安排的科学性、有效性是影响集卡运输,乃至整个港口运作的关键因素。传统的关于集卡调度的研究往往建立在堆场可用位置静态化的基础上,但是在现实环境中,堆场的可用位置是随着集装箱的进出口作业动态变化的。本文在考虑堆场可用位置动态变化的基础上,对集卡调度问题进行了研究。鉴于调度问题是典型的NP-hard问题,以及粒子群优化算法(PSO)在应用问题求解上的较好表现,本文采用四种不同改进机制的PSO算法对此问题进行优化求解,并对其优化效果进行对比分析。
During the port operation, the truck, a basic fundamental tool, is playing a significant role in transporting containers between seaside and yard storage. The yard being used for container storage and transshipment, the appropriateness and effectiveness of its special arrangement is a key factor significantly influencing the truck transportation and even the operation of the whole port. The traditional research is generally based on the container yard of static data of location, while in reality, the location available varies according to the import and export of containers. This paper, with the dynamic positions of container yard taken into consideration, studies the truck dispatch. As this is a typical NP-hard issue which has been proved, and particle swarm optimization can be well applied in application problem settlement, this paper explores the solution using particle swarm optimization. Meanwhile, to test the effect of this method, this paper selected four improved methods based on PSO to deal with the problem and the researcher conducts a comparative analysis of the optimized results. According to the results, the comprehensive learning mechanism-based particle swarm optimization proves to be the most appropriate method.
出处
《中国管理科学》
CSSCI
北大核心
2016年第S1期217-224,共8页
Chinese Journal of Management Science
基金
国家自然科学基金资助项目(71571120
71271140
71471158
71461027)
广东省自然科学基金资助项目(2016 A030310074)
深圳大学学生创新发展基金重点资助项目(16XSCX04)
关键词
堆场
集卡调度
智能优化
yard
truck scheduling
intelligent optimization
