用Kohonen地图方法解决取货和送货车辆路线问题

Meryem Moumou, R. Allaoui, K. Rhofir
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引用次数: 1

摘要

通常在车辆路线问题与交付和提取(VRPDP),我们与一个单一的中央仓库,车队的同质车辆和一组客户。客户分为两种类型:已知要从仓库交付的货物数量的客户和已知要收集到仓库的货物数量的客户。这项工作的目的是,提出一种VRPDP的变体,并最大限度地减少车队和旅行时间的总和,限制车辆必须有足够的能力来运输要交付的商品和那些在客户那里取走的商品,以便将它们送回仓库。我们提出了一种利用无监督竞争神经网络概念更新Kohonen地图算法的方法。该算法扩展了现有的研究,通过强化术语偏差来鼓励网络探索更多可行的解决方案,并通过众所周知的2-opt过程引入增强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Kohonen map approach for vehicle routing problem with pick-up and delivering
Generally in the vehicle routing problem with delivery and pick-up (VRPDP), we work with a single central depot, a fleet of homogeneous vehicles and a set of customers. Customers are divided into two types: customers with known quantity of goods to be delivered from a depot and customers with a known quantity of goods to be collected to a depot. The aim of this work is, to present a variant of VRPDP and to minimize the vehicle fleet and the sum of travel time, with the restriction that the vehicle must have enough capacity for transporting the commodities to be delivered and those ones picked-up at customers for returning them to the depot. We propose an approach to update the Kohonen map algorithm using unsupervised competitive neural network concepts. The proposed algorithm extends existing research by reinforcing the term bias in order to encourage the network to explore a greater number of feasible solutions and introducing an enhancement through the well-known 2-opt procedure.
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