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Optimizing the Location Areas Planning in the SUMATRA Network with an Adaptation of the SPEA2 Algorithm

机译:用SPEA2算法改编优化Sumatra网络中规划的位置区域

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This paper presents our adaptation of the Strength Pareto Evolutionary Algorithm 2 (SPEA2, a Multi-Objective Evolutionary Algorithm) to optimize the Location Areas Planning Problem. Location Areas is a strategy widely used to manage one of the most important issues of the Public Land Mobile Networks: the mobile location management. In contrast to previous works, we propose a multi-objective approach with the goal of avoiding the drawbacks associated with the linear aggregation of the objective functions. The main advantage of a multi-objective approach is that this kind of algorithm provides a wide range of solutions among which the network operator could select the solution that best adjusts to the network real state at each moment. Furthermore, in order to obtain realistic results, we apply our proposal to the SUMATRA network, a test network that stores real-time information of the users' mobile activity in the San Francisco Bay (USA). Experimental results show that our proposal outperforms the results obtained in other works and, at the same time, it achieves a great spread of solutions.
机译:本文提出了我们对强度帕累托进化算法2(SPEA2,多目标进化算法)的适应,以优化定位区域规划问题。位置区域是广泛用于管理公共土地移动网络最重要问题之一的策略:移动位置管理。与以前的作品相比,我们提出了一种多目标方法,其目的是避免与目标函数的线性聚集相关的缺点。多目标方法的主要优点是这种算法提供了广泛的解决方案,其中网络运营商可以选择最佳调整到每时每刻的网络实际状态的解决方案。此外,为了获得现实的结果,我们将我们的建议应用于苏门答腊网络,这是一个测试网络,该测试网络存储旧金山湾(美国)在旧金山湾(美国)的用户移动活动的实时信息。实验结果表明,我们的提案优于其他作品中获得的结果,同时实现了解决方案的巨大传播。

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