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Based on differential evolution to research the control problem of area-coverage in WSNs

机译:基于差分进化的无线传感器网络区域覆盖控制问题研究

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Differential evolution (DE) is one of the most powerful stochastic real parameter optimizers of current interest. In this article, we aim to study the differential evolution and its' variants to research the area-coverage problem of wireless sensor networks (WSNs). Due to the area-coverage problem of WSNs is more important and pragmatic than the point coverage, we introduce a common method to generate test data set for area-coverage problem of WSNs firstly. Meanwhile, we propose a method that converts the area-coverage problem into point disjoint set covers problem. Then using DE and its' variants to solve the disjoint set covers problems. Namely we use DE and its' variants to research the area-coverage problems of WSNs. Finally, simulation comparison experiment are performed for the DE and its' variants. Results show that the JADE (an adaptive differential evolution proposed by Jingqiao and Arthur Sanderson) performance outperforms or same with others algorithms by solution quality, but the proposed variant has greatly better in terms of time complexity and optimization speed. The reason is that there combination operation can enhance the solution quality in early evolution.
机译:差分演化(DE)是当前关注的最强大的随机实参数优化器之一。在本文中,我们旨在研究差分演化及其变体,以研究无线传感器网络(WSN)的区域覆盖问题。由于无线传感器网络的覆盖问题比点覆盖更为重要和务实,因此,我们首先介绍一种通用的方法来生成无线传感器网络的覆盖问题的测试数据集。同时,我们提出了一种将面积覆盖问题转换为点不相交集覆盖问题的方法。然后使用DE及其变体来解决不相交集所涉及的问题。也就是说,我们使用DE及其变体来研究WSN的区域覆盖问题。最后,对DE及其变体进行了仿真比较实验。结果表明,JADE(由Jingqiao和Arthur Sanderson提出的自适应差分进化)的性能在解决方案质量方面优于或与其他算法相同,但是在时间复杂度和优化速度方面,该改进方案具有更好的性能。原因是组合操作可以在早期发展中提高解决方案的质量。

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