资产平衡约束下服务网络设计的快速大邻域搜索

Ruibin Bai, J. Woodward, N. Subramanian
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引用次数: 1

摘要

服务网络设计问题是货物综合运输中的一个基础性问题。它包括确定一个有效的运输网络和相应服务的调度细节。与车辆路线问题相比,SNDP可以模拟多式联运货运网络上的转移和合并。该问题通常被表述为一个混合整数规划问题,并且是NP-Hard。在这项研究中,我们提出了一个新的高效的大邻域搜索函数,可以更有效地处理约束。在禁忌搜索元启发式(TS)和GLS引导局部搜索(GLS)方法中对新邻域的有效性进行了评估。基于一组众所周知的基准实例的实验结果表明,新邻域的性能明显优于之前的弧形翻转邻域。邻域函数也适用于其他具有类似离散约束的优化问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new fast large neighbourhood search for service network design with asset balance constraints
The service network design problem (SNDP) is a fundamental problem in consolidated freight transportation. It involves the determination of an efficient transportation network and the scheduling details of the corresponding services. Compared to vehicle routing problems, SNDP can model transfers and consolidations on a multi-modal freight network. The problem is often formulated as a mixed integer programming problem and is NP-Hard. In this research, we propose a new efficient large neighbourhood search function that can handle the constraints more efficiently. The effectiveness of this new neighbourhood is evaluated in a tabu search metaheuristic (TS) and a GLS guided local search (GLS) method. Experimental results based on a set of well-known benchmark instances show that the new neighbourhood performs significantly better than the previous arc-flipping neighbourhood. The neighbourhood function is also applicable in other optimisation problems with similar discrete constraints.
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