缩小大型 CVRP 问题规模的方法

IF 4.1 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0

摘要

我们通过引入一种缩小问题规模的新方法来解决有容量车辆路由问题(CVRP)。我们提出了生成称为 "节 "的节点短序列的方法,这些节点在缩小后的 CVRP 中有效地充当了单个节点,更快、更容易求解。我们比较了三种分段生成方法,并评估了解决方案质量与计算时间节省之间的权衡。我们发现,无论使用哪种优化算法,将问题规模缩小到原始问题规模的 60% 左右只会导致解决方案质量的适度下降,但却能显著减少计算时间。我们的研究结果凸显了问题聚合和缩小规模对大规模 CVRP 的潜在好处,并为进一步改进聚合方法提供了机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Problem size reduction methods for large CVRPs

We solve the Capacitated Vehicle Routing Problem (CVRP) by introducing a novel approach to problem size reduction. We propose the generation of short sequences of nodes called “sections”, which effectively act as single nodes in a reduced CVRP that is faster and easier to solve. Three section generation methods are compared, and the trade-off between solution quality and computation time savings is evaluated. We show that reduced problem sizes of up to around 60 percent of the original problem size, result in only modest decreases in solution quality, but allow for significant reductions of computation time, regardless of the optimization algorithm used. Our findings highlight the potential benefits of problem aggregation and size reduction for large-scale CVRPs and suggest opportunities for further improving aggregation methods.

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来源期刊
Computers & Operations Research
Computers & Operations Research 工程技术-工程:工业
CiteScore
8.60
自引率
8.70%
发文量
292
审稿时长
8.5 months
期刊介绍: Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.
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