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HOPHS: A hyperheuristic that solves orienteering problem with hotel selection

机译:HOPHS:一种超启发式方法,可解决酒店选择中的定向运动问题

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We present a hyperheuristic approach designed to solve a real world problem: the Orienteering Problem with Hotel Selection (OPHS). This problem has recently been introduced as an extension of the well-known Orienteering Problem. In this problem, hotels must be selected from a pool of available hotels. Each trip starts and ends in one of the hotels. The goal is to maximize the total score computed by the sum of the score of the trips to the visit points of interest. We propose a hyperheuristic that is based on a hill-climbing procedure. The low-level heuristics have been selected focused on the different constraints of the problem. We have put special attention on the collaboration among the low-level heuristics, in order to guide the algorithm to the most promising areas, considering both the time constraints and the improvement of the score. We use the benchmarks instances including the hardest ones of the problem for testing. The results show that our technique is a very effective one in terms of the design and the quality of the solution found.
机译:我们提出了一种超启发式方法,旨在解决现实世界中的问题:酒店选择的定向越野问题(OPHS)。该问题最近作为众所周知的定向运动问题的扩展而引入。在此问题中,必须从可用酒店池中选择酒店。每次旅行都在其中一家酒店开始和结束。目的是使总得分最大化,该总得分由到感兴趣的访问点的行程得分之和计算得出。我们提出了一种基于爬山程序的超启发式方法。选择低级启发式方法的重点是问题的不同约束。我们特别关注低级启发式算法之间的协作,以便将算法引导到最有希望的领域,同时考虑时间限制和分数的提高。我们使用基准测试实例(包括最难解决的问题)进行测试。结果表明,就设计和解决方案的质量而言,我们的技术是一种非常有效的技术。

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