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A Node Flow Model for the Inflexible Visitation Liner Shipping Fleet Repositioning Problem with Cargo Flows

机译:具有货流的非柔性探班班轮运输舰队重定位问题的节点流模型

摘要

We introduce a novel, node flow based mathematical modelfor the fixed-time version of a central problem in the liner shipping industry called the Liner Shipping Fleet Repositioning Problem (LSFRP). We call this version of the problem the Inflexible Visitation LSFRP (IVLSFRP).During repositioning, vessels are moved between routes in a linershipping network. Shipping lines wish to reposition vessels as cheaply as possible without disrupting the cargo flows of the network. The LSFRP is characterized by chains of interacting activities with a multi-commodity flow over paths defined by the activities chosen. We introduce two versions of a node flow based model that exploit the fixed activity timesof the IVLSFRP’s graph to handle cargo demands on the nodes of the graph, instead of the arcs, significantly reducing the number of variables.Using this model in CPLEX, we are able to solve 12 previously unsolved IVLSFRP instances to optimality. Additionally, we improve the solution time on every instance in the IVLSFRP dataset, sometimes by several orders of magnitude.
机译:我们针对班轮运输业中一个称为班轮运输机队再定位问题(LSFRP)的核心问题的固定时间版本,引入了一种基于节点流的新颖数学模型。我们将此问题称为“不灵活探访LSFRP”(IVLSFRP)。在重新定位期间,船只在班轮运输网络中的路线之间移动。航运公司希望在不中断网络货运的情况下,尽可能便宜地重新安置船只。 LSFRP的特征是,交互活动的链与所选活动定义的路径上的多商品流交互。我们介绍了两个版本的基于节点流的模型,这些模型利用IVLSFRP图的固定活动时间来处理图的节点上的货物需求(而不是弧),从而显着减少了变量数量。在CPLEX中使用此模型能够最大程度地解决12个以前未解决的IVLSFRP实例。此外,我们将IVLSFRP数据集中每个实例的求解时间缩短了几个数量级。

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