Multi-Objective Mayfly Optimization Algorithm Based on Dimensional Swap Variation for RFID Network Planning

被引:6
|
作者
Xie, Xiaode [1 ]
Zheng, Jiali [1 ]
Feng, Minyu [1 ]
He, Siyi [1 ]
Lin, Zihan [1 ]
机构
[1] Guangxi Univ, Sch Comp Elect & Informat, Nanning 530004, Guangxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Optimization; Radiofrequency identification; Sensors; Planning; Linear programming; Interference; Pareto optimization; Multi-objective RFID network planning (MORNP); multi-objective mayfly optimization algorithm (MOMA); dimensional swap variation; pareto;
D O I
10.1109/JSEN.2022.3151932
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this study, a multi-objective mayfly optimization algorithm based on dimensional swap variation (DSV-MOMA) is proposed to solve Multi-objective RFID network planning problem (MORNP). The contributions of this work are as following: firstly, improving multi-objective mayfly optimization algorithm (MOMA)'s ability to solve high-dimensional nonlinear optimization problems; secondly, DSV-MOMA is used to solve the MORNP problem, and optimize two and three of the four objective functions simultaneously; lastly, the fuzzy decision mechanism is used to select an optimal solution objectively from pareto optimal solutions. The proposed DSV-MOMA algorithm contributes to having better diversity and convergence when solving high dimensional nonlinear and discontinuous test functions in comparison to other popular metaheuristic algorithms. DSV-MOMA also performs well when dealing with MORNP problems. In most experiments, DSV-MOMA can reduce interference effectively, and obtain satisfactory load balance and power while ensuring a higher coverage.
引用
收藏
页码:7311 / 7323
页数:13
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