Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (19): 267-273.DOI: 10.3778/j.issn.1002-8331.2006-0107

Previous Articles     Next Articles

External Trucks’ Appointment Optimization of Delivering Containers from Outside at Container Terminal

DING Yi, ZHANG Chengcheng   

  1. Institute of Logistic Science and Engineering, Shanghai Maritime University, Shanghai 201306, China
  • Online:2021-10-01 Published:2021-09-29

集装箱码头送箱外集卡预约优化研究

丁一,张成成   

  1. 上海海事大学 物流研究中心,上海 201306

Abstract:

It is an effective way to relieve container terminal’s congestion by appointment. Concerning the interest of truck companies and terminal operators and the complexity of terminal operation system, this paper aims at reducing external trucks’ average queue length within the appointment time windows and the difference between the truck’s preferred and assigned appointment time windows. So it uses queuing theory and Point wise Stationary Fluid Flow Approximation(PSFFA) to set up a multi-objective programming model to determine an optimal scheduling plan which can benefit the truck companies and terminal operators. The paper introduces fact data to solve the model with CPLEX and compares the results with Monte Carlo simulation’s results. Also, it adjusts parameters to optimize appointment mode. The results show that the appointment optimization model can effectively describe the queue of trucks at terminal, and minimize the external truck’s average queue length and the difference between the truck’s preferred and assigned appointment time windows.

Key words: container terminal, truck appointment system, multi-objective programming model, appointment time window, average queue length

摘要:

通过预约缓解集装箱码头拥堵是提高港口运作效率的有效途径。考虑集卡公司和码头运营商双方的利益以及码头内部作业系统的复杂性,以减小外集卡在预约时间窗内的平均排队长度和集卡公司期望到达的预约时间窗与被调配到的预约时间窗间的差异为目标,运用排队论相关知识和逐点固定流体近似方法(PSFFA),建立了多目标规划模型,以确定一个使集卡公司和码头运营商双赢的集卡调度计划。引入实例数据,利用CPLEX求解模型,并将结果与蒙特卡罗仿真结果作比较,以验证模型的有效性,并在此基础上调节参数优化预约模式。算例结果表明,集卡预约多目标规划模型能有效描述集卡在闸口和堆场的排队情况,最小化外集卡在码头排队长度和集卡公司期望到达的预约时间窗与被调配到的预约时间窗之间的差异。

关键词: 集装箱码头, 集卡预约系统, 多目标规划模型, 预约时间窗, 平均排队长度