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Efficient citywide planning of open WiFi access networks using novel grouping harmony search heuristics

机译:使用新型分组和声搜索启发式方法在全市范围内有效规划开放的WiFi接入网络

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摘要

This paper proposes the application of a novel meta-heuristic algorithm to the metropolitan wireless local area network deployment problem. In this problem, the coverage level of the deployed network must be maximized while meeting an assigned maximum budget, set beforehand. Specifically, we propose an approach based on the Harmony Search (HS) algorithm, with three main technical contributions: (1) the adaptation of the HS algorithm to a grouping scheme; (2) the adaptation of the improvisation operators driving the algorithm to the specific characteristics of the optimization problem to be tackled; and (3) its performance assessment via a simulated experiment inspired by real statistics in the city of Bilbao (Basque Country, northern Spain). Moreover, a comparison study of the proposed algorithm with a previous published grouping genetic algorithm is carried out, to further validate its performance. In light of the simulation results obtained from extensive experiments and several complexity considerations, we conclude that the proposed algorithm outperforms its genetically inspired counterpart, not only in terms of computation time, but also in the coverage level of the solution obtained.
机译:本文提出了一种新颖的元启发式算法在城市无线局域网部署问题中的应用。在此问题中,必须在满足预先设置的分配的最大预算的同时最大化部署网络的覆盖范围。具体而言,我们提出了一种基于谐波搜索(HS)算法的方法,该方法具有三个主要的技术贡献:(1)将HS算法应用于分组方案; (2)使驱动算法的即兴运算符适应要解决的优化问题的特定特征; (3)通过在毕尔巴鄂市(西班牙北部巴斯克地区)的真实统计数据启发下进行的模拟实验对其效果进行评估。此外,该算法与先前发表的分组遗传算法进行了比较研究,以进一步验证其性能。根据从大量实验中获得的模拟结果以及一些复杂性的考虑,我们得出结论,该算法不仅在计算时间方面,而且在所获得解决方案的覆盖范围上均优于其遗传方法。

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