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Applying Differential Evolution to a Realistic Location Area Problem Using SUMATRA

机译:使用Sumatra将差分演变应用于现实位置区域问题

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The mobile networks are every day more common and useful, but the costs involved in its management are high. The Location Area partitioning is a strategy of location management that tries to minimize the involved costs. In this paper we present a new approach based on Differential Evolution algorithm applied to the Location Area partitioning, as a cost optimization problem. We use realistic data [1] for generating the test networks. This work has the objective of defining the best values to the Differential Evolution (DE) parameters and setting the DE scheme, which allows us to obtain better results when compared to classical strategies and the other authors' results. The best solution is obtained after the development of four distinct experiments, each one applied to one of the differential evolution parameters. The final results obtained by this approach are very good.
机译:移动网络每天都是更常见和有用的,但其管理中所涉及的成本很高。位置区域分区是一个位置管理的策略,它试图最大限度地减少所涉及的成本。本文介绍了一种基于应用于位置区域分区的差分演化算法的新方法,作为成本优化问题。我们使用现实数据[1]来生成测试网络。这项工作具有定义差分演进(DE)参数(DE)参数的最佳值并设置DE方案的目标,这使我们能够在与经典策略和其他作者的结果相比时获得更好的结果。在开发四个不同的实验之后获得最佳解决方案,每个实验施加到其中一个差分演进参数。通过这种方法获得的最终结果非常好。

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