期刊名称:International Journal of Distributed Sensor Networks
印刷版ISSN:1550-1329
电子版ISSN:1550-1477
出版年度:2015
卷号:2015
DOI:10.1155/2015/716291
出版社:Hindawi Publishing Corporation
摘要:Based on multiobjective particle swarm optimization, a localization algorithm named multiobjective particle swarm optimization localization algorithm (MOPSOLA) is proposed to solve the multiobjective optimization localization issues in wireless sensor networks. The multiobjective functions consist of the space distance constraint and the geometric topology constraint. The optimal solution is found by multiobjective particle swarm optimization algorithm. Dynamic method is adopted to maintain the archive in order to limit the size of archive, and the global optimum is obtained according to the proportion of selection. The simulation results show considerable improvements in terms of localization accuracy and convergence rate while keeping a limited archive size by a method using the global optimal selection operator and dynamically maintaining the archive.