Improved differential evolution to solve the two-objective coverage problem of wireless sensor networks

doi:10.1109/CCDC.2016.7531383

CORC > 北京大学 > 工学院

	Improved differential evolution to solve the two-objective coverage problem of wireless sensor networks
	Xu, Yulong ; Wang, Xiaohui ; Zhang, Han
	2016
DOI	10.1109/CCDC.2016.7531383
英文摘要	Differential evolution (DE) is one of the most powerful stochastic real parameter optimizers of current interest. In this article, we aim to study the multi-objective differential evolution and use the improved algorithm to solve a two-objective coverage problem of wireless sensor networks (WSNs). It is found that there are some redundant operations in the classic multi-objective evolution based on the Pareto sorting. Hence, we introduce a sorting method which only handles the highest rank individual in current population. The introduced method sorts the individuals meanwhile chooses some of them into next generation. When the next generation is achieved, the method will finish the evolution of the current population. We incorporate the proposed method into differential evolution to solve the two-objective coverage problem of WSN. We provide the optimization model of this two-objective coverage problem and offer the encoding style of chromosomes. Simulation result shows that the improved algorithm has better performance than the classic multi-objective algorithms. ? 2016 IEEE.; EI; 2379-2384
会议录	28th Chinese Control and Decision Conference, CCDC 2016
语种	英语
内容类型	会议论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/449347]
专题	工学院
推荐引用方式 GB/T 7714	Xu, Yulong,Wang, Xiaohui,Zhang, Han. Improved differential evolution to solve the two-objective coverage problem of wireless sensor networks[C]. 见:.