Scheduling trucks in a multi-door cross-docking system with time windows

IF 1.2 4区 工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY
G. Ozden, Inci Sariçiçek
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引用次数: 2

Abstract

Cross-docking is a strategy that distributes products directly from a supplier or manufacturing plant to a customer or retail chain, reducing handling or storage time. This study focuses on the truck scheduling problem, which consists of assigning each truck to a door at the dock and determining the sequences for the trucks at each door considering the time-window aspect. The study presents a mathematical model for door assignment and truck scheduling with time windows at multi-door cross-docking centers. The objective of the model is to minimize the overall earliness and tardiness for outbound trucks. Simulated annealing (SA) and tabu search (TS) algorithms are proposed to solve largesized problems. The results of the mathematical model and of meta-heuristic algorithms are compared by generating test problems for different sizes. A decision support system (DSS) is also designed for the truck scheduling problem for multi-door cross-docking centers. Computational results show that TS and SA algorithms are efficient in solving large-sized problems in a reasonable time.
带时间窗的多门交叉对接系统中的货车调度
交叉对接是一种将产品直接从供应商或制造工厂分发给客户或零售链的策略,减少了处理或存储时间。本文主要研究卡车调度问题,该问题包括将每辆卡车分配到码头的一个门上,并考虑时间窗方面确定每个门上卡车的顺序。研究了多门交叉码头中心带时间窗的门分配和卡车调度数学模型。该模型的目标是最小化出站卡车的整体早到和迟到。提出了模拟退火(SA)和禁忌搜索(TS)算法来解决大规模问题。通过生成不同规模的测试问题,比较了数学模型和元启发式算法的结果。针对多门交叉对接中心的货车调度问题,设计了决策支持系统。计算结果表明,TS和SA算法能够在合理的时间内有效地求解大规模问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.80
自引率
16.70%
发文量
0
审稿时长
6-12 weeks
期刊介绍: The Bulletin of the Polish Academy of Sciences: Technical Sciences is published bimonthly by the Division IV Engineering Sciences of the Polish Academy of Sciences, since the beginning of the existence of the PAS in 1952. The journal is peer‐reviewed and is published both in printed and electronic form. It is established for the publication of original high quality papers from multidisciplinary Engineering sciences with the following topics preferred: Artificial and Computational Intelligence, Biomedical Engineering and Biotechnology, Civil Engineering, Control, Informatics and Robotics, Electronics, Telecommunication and Optoelectronics, Mechanical and Aeronautical Engineering, Thermodynamics, Material Science and Nanotechnology, Power Systems and Power Electronics.
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