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A Genetic Algorithm for the Global Planning Problem of UMTS Networks

机译:UMTS网络全球规划问题的遗传算法

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The ultimate objective of network planning is to achieve the best performance and profitability with the minimum network investment. In this paper, we investigate the use of the genetic algorithm in order to find "good" feasible solution for the global topology planning problem of Universal Mobile Telecommunications System (UMTS) networks. The latter has been shown to be NP-hard as it is composed of three different subproblems (each one being NP-hard): the cell planning problem, the access network planning problem and the core network planning problem. As a result, we concentrate our effort on the development of an approximate approach based on the genetic algorithm. Numerical results show that quasi-optimal solutions (on average, within 2.56 ± 1.01% citIV optimal solution) can be found by using the genetic algorithm with a 'relatively short computation time compared to CPLEX.
机译:网络规划的最终目标是实现最低网络投资的最佳性能和盈利能力。在本文中,我们调查了遗传算法的使用,以便为全球移动电信系统(UMTS)网络的全球拓扑规划问题找到“良好”可行的解决方案。后者已被证明是NP - 困难,因为它由三个不同的子问题组成(每个都是NP-Hard):电池规划问题,接入网络规划问题和核心网络规划问题。因此,我们专注于基于遗传算法的近似方法的开发。数值结果表明,可以通过使用具有“与CPLEX相对短的计算时间相对短的计算时间的遗传算法来找到准优化解决方案(平均而言,在2.56±1.01%的CITIV最佳解决方案中)。

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