不确定环境下集装箱码头泊位与岸桥联合调度

发布时间：2018-06-11 17:15

本文选题：连续泊位 + 随机　；参考：《计算机工程与应用》2017年07期

【摘要】：在集装箱码头操作系统中,有效的泊位岸桥调度计划有助于提高码头的运营效率和客户满意度。针对船舶到港时间和装卸作业时间随机的泊位岸桥联合调度问题,综合考虑了连续泊位下船舶偏离偏好泊位产生的惩罚时间,并通过添加延缓时间的方法来吸收不确定性因素带来的影响。为了体现调度计划的鲁棒性,将延缓时间添加在目标函数中,建立了以船舶在港总时间、偏离偏好泊位的惩罚时间、客户满意度和延缓时间之和最小化为目标的混合整数规划模型,提出一种自改变遗传算法和启发式靠泊相结合的改进遗传算法对模型进行求解;通过算例分析,证明了提出的改进遗传算法在计算不确定环境下的泊位岸桥联合调度问题的有效性。
[Abstract]:In the container terminal operating system, effective berth bridge scheduling is helpful to improve the terminal operation efficiency and customer satisfaction. In view of the problem of joint scheduling of berths and bridges with random arrival time and loading and unloading time, the penalty time caused by ship deviation from preferred berth under continuous berths is comprehensively considered. The effect of uncertainty factors is absorbed by adding delay time. In order to reflect the robustness of the scheduling plan, the delay time is added to the objective function, and the penalty time for the ship's total time in Hong Kong and deviation from the preferred berth is established. A hybrid integer programming model with the goal of minimizing the sum of customer satisfaction and delay time is proposed. An improved genetic algorithm combining self-changing genetic algorithm and heuristic berthing is proposed to solve the model. It is proved that the proposed improved genetic algorithm is effective in computing the joint scheduling problem of berths and bridges in uncertain environments.
【作者单位】：上海海事大学科学研究院物流研究中心;
【基金】：国家自然科学基金(No.71471110);国家自然科学基金青年项目(No.71301101) 上海市科委项目(No.14170501500)
【分类号】：U691.3;TP18

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