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A Multi-start Iterated Local Search Algorithm with Variable Degree of Perturbation for the Covering Salesman Problem

机译:一种多开始迭代本地搜索算法,具有覆盖推销员问题的变量扰动

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The covering salesman problem (CSP) is a variant of the well-known traveling salesman problem (TSP), where there is no need to visit all the cities, but every city must be either visited or within a predetermined distance from at least one visited city in the tour. CSP, being a generalization of the TSP, is also NP-Hard. CSP finds important applications in emergency planning, disaster management, and rural healthcare. In this paper, we have proposed a multi-start iterated local search algorithm for the CSP. We also incorporated a variable degree of perturbation strategy to further improve the solution obtained through our approach. Computational results on a wide range of benchmark instances shows that our proposed approach is competitive with other state-of-the-art approaches for solving the CSP.
机译:覆盖推销员问题(CSP)是众所周知的旅行推销员问题(TSP)的变体,在那里没有必要访问所有城市,但必须访问每个城市或者在至少一个访问的预定距离内城市在旅游中。 CSP是TSP的泛化,也是NP-HARD。 CSP在应急计划,灾害管理和农村医疗保健中找到重要的应用。在本文中,我们提出了一种用于CSP的多开始迭代本地搜索算法。我们还包含一种可变程度的扰动策略,以进一步改善通过我们的方法获得的溶液。在各种基准实例上的计算结果表明,我们所提出的方法与解决CSP的其他最先进的方法具有竞争力。

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