上海交通大学学报

上海交通大学学报 ›› 2019, Vol. 53 ›› Issue (1): 69-76.doi: 10.16183/j.cnki.jsjtu.2019.01.010

• 学报（中文） • 上一篇    下一篇

集装箱进出口码头泊位-堆场协同分配的动态决策

韩笑乐，鞠留红，钱丽娜，陆志强   

  1. 同济大学 机械与能源工程学院， 上海 201804
  • 出版日期:2019-01-28 发布日期:2019-01-28
  • 通讯作者: 陆志强，男，教授，博士生导师，电话(Tel.)：021-69589803；E-mail：zhiqianglu@tongji.edu.cn.
  • 作者简介:韩笑乐(1983-)，男，江苏省江阴市人，博士，助理教授，研究方向为集装箱码头运营优化.E-mail：hanxiaole@tongji.edu.cn.
  • 基金资助:
    国家自然科学基金(71502129，61473211)

Dynamic Decision Making for the Integrated Allocation of Berth and Yard Resources at Import/Export Container Terminals

HAN Xiaole,JU Liuhong,QIAN Lina,LU Zhiqiang   

  1. School of Mechanical Engineering, Tongji University, Shanghai 201804, China
  • Online:2019-01-28 Published:2019-01-28

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摘要： 针对集装箱进出口码头泊位-堆场的调度问题，考虑船舶到港时间不确定性因素影响的资源协同分配多阶段决策过程，兼顾其鲁棒性与灵活性要求，提出基于两阶段近似的动态决策框架.在各个滚动决策点，通过信息和操作的动态分析，提出了船舶分类方法，建立基于随机场景的混合整数规划模型，其中包含固定性决策及各样本场景下的可调整预决策，并以最小化船舶总在港时间的期望值为目标.同时，针对决策逻辑设计了两阶段禁忌搜索算法以求解各个滚动决策点的优化问题，通过数值实验验证所提决策方法的有效性.

关键词: 集装箱码头, 动态决策, 调度, 不确定性

Abstract: The multi-stage decision process of integrated resource reallocation at import/export container terminals is addressed, considering the uncertainty of vessel arrival time at operational level. To satisfy both robustness and flexibility requirement, a dynamic decision framework based on 2-stage approximation is proposed. At each decision point, the dynamics of information and operation are analyzed, based on which the vessel classification is proposed and a stochastic-scenarios-based mixed integer programming model is established. The model is to determine both the 1st-stage fixed decisions and the 2nd-stage adjustable pre-decisions, with the objective of minimizing expected dwelling time of all vessels. Dependent on such decision logic, a two-stage Tabu Search is proposed to solve the optimization problem at each decision point. Numerical experiments verify the efficiency and effectiveness of the proposed decision method, which makes better utilization of updating certain and uncertain information.

Key words: container terminal, dynamic decision-making, scheduling, uncertainty

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