离散无能力$p$中值问题新发展的元启发式的比较研究

2022 8th International Conference on Control, Decision and Information Technologies (CoDIT) Pub Date : 2022-05-17 DOI:10.1109/CoDIT55151.2022.9804107

Muhammad Sulaman, Mahmoud Golabi, Mathieu Brévilliers, Julien Lepagnot, L. Idoumghar

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引用次数: 1

摘要

作为设施选址问题最突出的变体之一，p中值问题旨在确定建立p个设施的最佳位置，从而使客户的总运输成本最小。由于p中值问题被归类为np困难，因此应用元启发式方法来解决它是不可避免的。考虑到元启发式的快速发展，选择最合适的算法来解决这一问题是一项艰巨的任务。因此，本研究对几种经典的和最近开发的受自然启发的优化算法进行了比较研究，以解决几个随机生成的不同尺寸和规格的测试实例上的离散无能力p中值问题。

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A comparative study of newly developed metaheuristics for the discrete uncapacitated $p$-median problem

As one of the most prominent variants of the facility location problem, the p-median problem aims to determine the best locations for establishing p number of facilities such that the aggregate customers' transportation cost is minimized. Since the p-median problem is classified as NP-hard, the application of metaheuristics to solve it is inevitable. Considering the fast development in metaheuristics, choosing the most appropriate algorithm to solve this problem is a difficult task. Therefore, this work presents a comparative study of several classical and recently developed nature-inspired optimization algorithms to solve the discrete uncapacitated p-median problem on several randomly generated test instances with different sizes and spec-ifications.

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2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)

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