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Variable Neighborhood Search for the Orienteering Problem

机译:定向越野问题的可变邻域搜索

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摘要

The Orienteering Problem (OP) is a version of TSP with profits in which instead of a cycle, a path is sought. In this paper, we consider three variations of Variable Neighborhood Search (VNS) and present the first algorithm solely based on VNS to solve the OP. The experimental results for the benchmark problems indicate that the algorithm, designed by using Reduced VNS instead of the local search phase of the traditional VNS, is the best amongst other variations of VNS we tried; it is the most robust and produces the best results, in terms of solution quality, within a reasonable amount of time. Moreover, it improves the best known results for several benchmark problems and reproduces the best results for others.
机译:定向越野问题(OP)是具有利润的TSP版本,在其中寻求一种替代循环的方法。在本文中,我们考虑了可变邻域搜索(VNS)的三种变体,并提出了仅基于VNS来解决OP的第一种算法。针对基准问题的实验结果表明,该算法是通过使用精简VNS而不是传统VNS的本地搜索阶段设计的,是我们尝试的其他VNS变体中最好的;就解决方案质量而言,它是最可靠的,并且可以在合理的时间内产生最佳的结果。此外,它改善了几个基准问题的最佳结果,并为其他问题重现了最佳结果。

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