计算机应用 ›› 2015, Vol. 35 ›› Issue (1): 247-251.DOI: 10.11772/j.issn.1001-9081.2015.01.0247

• 行业与领域应用 • 上一篇    下一篇

单船岸桥分配与调度集成优化模型

郑红星, 吴岳, 涂闯, 刘进平   

  1. 大连海事大学 交通运输管理学院, 辽宁 大连116026
  • 收稿日期:2014-07-31 修回日期:2014-09-20 出版日期:2015-01-01 发布日期:2015-01-26
  • 通讯作者: 郑红星
  • 作者简介:郑红星(1971-),男,河北迁安人,副教授,博士,主要研究方向:物流系统仿真与优化;吴岳(1990-),男,河北沧州人,硕士研究生,主要研究方向:物流系统仿真与优化;涂闯(1989-),男,辽宁葫芦岛人,硕士研究生,主要研究方向:物流系统仿真与优化;刘进平(1976-),女,辽宁海城人,讲师,博士研究生,主要研究方向:供应链管理.
  • 基金资助:

    国家自然科学基金资助项目(71371037, 71473024).

Quay crane allocation and scheduling joint optimization model for single ship

ZHENG Hongxing, WU Yue, TU Chuang, LIU Jinping   

  1. Transportation Management College, Dalian Maritime University, Dalian Liaoning 116026, China
  • Received:2014-07-31 Revised:2014-09-20 Online:2015-01-01 Published:2015-01-26

摘要:

针对集装箱码头泊位确定条件下的单船岸桥(QC)分配和调度问题,建立了线性规划模型.模型以船舶在泊作业时间最短为目标,考虑多岸桥作业过程中的干扰等待时间与岸桥间的作业量均衡,并设计了嵌入解空间切割策略的改进蚁群优化(IACO)算法进行模型求解.实验结果表明:与可用岸桥全部投放使用的方法相比,所提模型与算法求得结果平均能够节省31.86%的岸桥资源;IACO算法与Lingo求得的结果相比,船舶在泊作业时间的平均偏差仅为5.23%,但CPU处理时间平均降低了78.7%,表明了所提模型与算法的可行性和有效性.

关键词: 岸桥分配和调度, 整数线性规划, 作业量均衡, 干扰等待时间, 船舶在泊作业时间, 改进蚁群优化算法

Abstract:

This paper proposed a liner programming model to deal with the Quay Crane (QC) allocation and scheduling problem for single ship under the circumstance of fixed berth allocation. With the aim of minimizing the working time of the ship at berth, the model considered not only the disruptive waiting time when the quay cranes were working, but also the workload balance between the cranes. And an Improved Ant Colony Optimization (IACO) algorithm with the embedding of a solution space split strategy was presented to solve the model. The experimental results show that the proper allocation and scheduling of quay cranes from the model in this paper can averagely save 31.86% of the crane resource compared with full application of all available cranes. When comparing to the solution solved by Lingo, the results from IACO algorithm have an average deviation of 5.23%, while the average CPU (Central Processing Unit) computational time is reduced by 78.7%, which shows the feasibility and validity of the proposed model and the algorithm.

Key words: Quay Crane (QC) allocation and scheduling, integer linear programming, workload balance, disruptive waiting time, working time of ship at berth, Improved Ant Colony Optimization (IACO) algorithm

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