期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2019
卷号：97
期号：2
页码：423-433
出版社：Journal of Theoretical and Applied
摘要：Studies pertaining to wireless sensor network deployment (WSND) have escalated in recent years due to its exceptional function in planning configurations for sensor networks in order to attain maximum coverage and lifetime in a cost-effective manner. Although the approach of meta-heuristic searching optimization has been commonly applied, it has failed in addressing several issues related to multiple objectives and intricate optimization surface. As such, this work developed a novel multi-objective optimization (MOO) called the lagged multi-objective jumping particle swarm optimization (LMOJPSO) in order to overcome the drawbacks of WSND. It aims at finding the best locations and configuration of sensors in 2D environment in order to prolong the life time of the network with obtaining the best coverage and other performance measures. Three types of Pareto front, which were global, iteration (including lag), and local, had been incorporated for optimization search. Upon application to WSND, the proposed algorithm appears to ascertain network coverage and connectivity. When the outcomes of LMOJPSO were compared with the state-of-the-art NSGA-II method, the proposed algorithm seemed to display superior outputs for (MOO).
