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

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.