考虑返回可能性的多停车场车辆路径问题的Tabu搜索算法数学模型

IF 1.8 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Alim Al Ayub Ahmed, S. Singhal, A. S. Prakaash, Johnry Dayupay, Irwan Rahadi, Haydar Abdulameer Marhoon, A. H. Iswanto, Saja Fadhil Abbas, S. Aravindhan
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引用次数: 0

摘要

摘要当前的研究考察了一种基本类型的车辆路径问题(VRP)。这种类型的车辆由来自多个停车场的容量有限的车辆为客户提供服务,被称为多停车场容量车辆路线问题(MDCVRP)。这项研究的新颖之处在于,在目前的情况下,汽车在离开停车场后,可以回到任何其他停车场。这些问题似乎发生在大多数真实世界的问题中,其中信息、消息或新闻是从某个地方以电子方式发送的。该问题的目的是将与路由相关的成本降至最低。关于这些问题的文献,在以前的研究和研究中已经证明,这些问题属于难NP问题,并且使用元启发式方法来解决这些问题,确切的方法是合理的。在改变基本模型后,本研究开发了一种禁忌搜索(TS)算法。研究结果表明,如果设备可以返回任何仓库,与设备被迫返回其仓库的情况相比,成本显著降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Mathematical Model for the Vehicles Routing Problem with Multiple Depots, Considering the Possibility of Return Using the Tabu Search Algorithm
Abstract The current study examines an essential type of vehicle routing problem (VRP). This type is one where customers are served by limited-capacity vehicles from multiple depots and is known as Multi-Depot Capacitated Vehicle Routing Problem (MDCVRP). The novelty of this study is that in the present case, cars, after Leaving the Depot, can go back to any other depot. Those issues seem to occur in most real-world issues where information, messages, or news are sent electronically from somewhere. The purpose of the problem is to minimize the costs associated with routing. Regarding the literature on such issues, it has been proven in previous studies and research that these problems are among the hard-NP problems, and to solve them using the metaheuristic method, the exact methods justify it. After changing the basic model, this study developed a Tabu Search (TS) algorithm. The study results demonstrate that if the equipment can return to any depot, the cost is significantly reduced in contrast to the case where equipment is forced to return to their depot.
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来源期刊
Foundations of Computing and Decision Sciences
Foundations of Computing and Decision Sciences COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
2.20
自引率
9.10%
发文量
16
审稿时长
29 weeks
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