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作 者:许波桅 刘小艳 杨勇生 李军军[2] XU Bowei;LIU Xiaoyan;YANG Yongsheng;LI Junjun(Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai 201306, China;College of Merchant Marine, Shanghai Maritime University, Shanghai 201306, China)
机构地区:[1]上海海事大学物流科学与工程研究院,上海201306 [2]上海海事大学商船学院,上海201306
出 处:《计算机集成制造系统》2020年第10期2851-2863,共13页Computer Integrated Manufacturing Systems
基 金:国家社科基金一般资助项目(18BGL109)。
摘 要:城市早晚高峰期拥堵增加了集卡运输时间的不确定性,现有集卡预约系统(TAS)尚不能有效解决集卡拥堵问题。综合考虑集卡公司预约变更成本、闸口排队等候成本、早晚高峰期拥堵成本及怠速排放成本等因素及各成本的相关约束,建立了一种基于混合整数非线性规划(MINLP)的集卡预约多约束调度模型。以集卡公司及港务公司的综合运营成本最低为目标,利用Lingo软件求解小、中规模问题的精确解;设计动态调整旋转角机制,提出一种自适应量子遗传算法对大规模问题优化求解,获得相应的最佳的集卡调度方案。仿真实验结果表明,多约束TAS与常规TAS相比,能更好地服务于集卡公司和港务公司,有效地降低集卡公司和港务公司的综合运营成本。Congestion in the morning and evening peak periods increases the uncertainty of the time of truck transportation,and the existing Truck Appointment System(TAS)cannot effectively solve the problem of truck congestion.To reduce container truck congestion,more and more container ports are adopting the use of TAS.A multi-constrained scheduling model based on Mixed Integer Nonlinear Programming(MINLP)was proposed for designing a novel TAS.The appointment change cost,gate queuing cost,congestion cost and idle emission cost in the morning and evening peak periods were considered comprehensively to minimize the overall operating cost for both container truck companies and port companies.The lingo commercial software was used to obtain the exact solutions for small and medium scale problems,and a self-adaptive quantum genetic algorithm was proposed to solve the large-scale problem and obtain the corresponding optimal truck scheduling scheme.Experimental results indicated that the proposed TAS could outperform the conventional TAS by better serving container truck companies and port companies and more effectively reducing their overall operating cost.
关 键 词:集卡预约系统 拥堵成本 排放成本 多约束调度模型 自适应量子遗传算法
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
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