Optimizing Truck Visits to Container Terminals with Consideration of Multiple Drays of Individual Drivers

IF 1 Q3 ENGINEERING, MULTIDISCIPLINARY Journal of Optimization Pub Date : 2018-09-17 DOI:10.1155/2018/5165124
R. Jovanovic
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引用次数: 6

Abstract

In this paper a new approach for designing a truck appointment system (TAS) at container terminals is proposed. While the vast majority of published research analyzes the TAS from the perspective of drayage companies and terminal operations, in this work this topic is centered around truck drivers. The objective of this approach is to show that it is possible to increase the satisfaction of drivers which will maintain the positive effects that the TAS provides to the port. To be more precise, the focus is on exploiting the fact that individual truck drivers perform multiple visits to the container terminal in a day. Based on this information, a scheduling problem is defined and the corresponding integer programming model is developed. The potential benefits of the proposed approach are evaluated for the ports of Los Angeles and the port of Seattle. This has been done by generating problem instances based on the distribution of the number of daily truck visits to the port, number of daily working hours of drivers, and distances (lengths) of individual dray moves for the corresponding ports. The results of the conducted computational experiments show that using the proposed approach can positively affect gate waiting times and truck driver satisfaction. Further, it is shown that this type of approach favors more experienced drivers, which has a potential to provide additional benefits to the port.
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考虑个体司机多天行程的集装箱码头货车优化
本文提出了一种设计集装箱码头车辆预约系统的新方法。虽然绝大多数已发表的研究都是从运输公司和码头运营的角度分析运输服务,但在这项工作中,该主题以卡车司机为中心。这种方法的目的是表明,提高司机的满意度是可能的,这将保持交通运输系统为港口提供的积极影响。更准确地说,重点是利用单个卡车司机在一天内多次访问集装箱码头的事实。在此基础上,定义了调度问题,并建立了相应的整数规划模型。对洛杉矶港和西雅图港拟议方法的潜在效益进行了评估。这是通过生成问题实例来完成的,这些问题实例是基于每天到达港口的卡车数量的分布、司机的每日工作小时数以及相应港口的单个拖车移动距离(长度)。计算实验结果表明,采用该方法可以显著提高登机口等待时间和卡车司机满意度。此外,研究表明,这种方法有利于更有经验的司机,这有可能为港口提供额外的好处。
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来源期刊
Journal of Optimization
Journal of Optimization ENGINEERING, MULTIDISCIPLINARY-
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