Radio network planning is a core problem in cellular networks. It includes coverage, capacity and parameter planning. This paper investigates the Antenna Positioning Problem (APP) which is a main task in cellular networks planning. The aim is to find a trade-off between maximizing coverage and minimizing costs. APP is the task of selecting a subset of potential locations where installing the base stations to cover the entire area. In theory, the APP is NP-hard. To solve it in practice, we propose a new meta-heuristic called Evolutionary Iterated Local Search that merges the local search method and some evolutionary operations of crossover and mutation. The proposed method is implemented and evaluated on realistic, synthetic and random instances of the problem of different sizes. The numerical results and the comparison with the state-of-the-art show that the proposed method succeeds in finding good results for the considered problem.

中文翻译：

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蜂窝网络中天线定位问题的进化迭代局部搜索元启发式

无线网络规划是蜂窝网络的核心问题。它包括覆盖、容量和参数规划。本文研究了作为蜂窝网络规划的主要任务的天线定位问题（APP）。目的是在最大化覆盖范围和最小化成本之间找到平衡。APP 的任务是选择安装基站以覆盖整个区域的潜在位置子集。理论上，APP 是 NP 难的。为了在实践中解决这个问题，我们提出了一种新的元启发式算法，称为进化迭代局部搜索，它融合了局部搜索方法和一些交叉和变异的进化操作。所提出的方法在不同大小问题的现实、合成和随机实例上实施和评估。