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作 者:王晔娇 周晖[1] Wang Yejiao;Zhou Hui(School of Electronics&Information,Nantong University,Nantong Jiangsu 226019,China)
出 处:《计算机应用研究》2018年第10期3003-3006,共4页Application Research of Computers
基 金:国家自然科学基金资助项目(61501264)
摘 要:针对RFID网络规划问题,综合考虑其整体性能,建立约束多目标优化的网络规划模型;提出混合萤火虫多目标优化算法,在算法中引入新的搜索机制和非支配排序方法,以加强其搜索能力,并更有效逼近Pareto前沿。仿真研究表明,所提算法可以有效提高RFID网络的整体性能,即在保证标签覆盖率的同时,提高网络经济效益,降低阅读器冲突,平衡网络负载,实现对RFID网络的优良规划。For the problem of RFID network planning,considered the overall performance,and established the multi-objective optimization model of the network planning with constraints,this paper proposed a new hybridized firefly algorithm by incorporating an new searching mechanism and non-dominated sorting strategy into the firefly algorithm to improve the searching capability,and approximated the Pareto front.Simulation results show that the proposed algorithm can effectively improve the overall performance of RFID network,namely improve the economic efficiency,reduce the reader interference,balance the network load,and guarantee the coverage at the same time,and achieve the good planning of RFID network.
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