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Charging path optimization for wireless rechargeable sensor network

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Abstract

In wireless rechargeable sensor networks(WRSNs), charging path planning becomes more and more important. In this paper, a charging path planning model based on high-dimensional multi-objective optimization is proposed, which takes life cycle, distance, energy consumption and charging time into consideration. At the same time, an improved algorithm is proposed to improve the crossover mode and diversity of the reference-point-based many-objective evolutionary algorithm following non-dominated sorting genetic algorithm(NSGA)&NSGA-II framework(we call it NSGA-III) for charging path planning. In the end, the validity of the charging process and the rationality of the charging path are verified by experimental comparison.

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Acknowledgments

This work is supported by Key R&D program of Shanxi Province under Grant NO.201903D421048.

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Authors and Affiliations

  1. School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan, 030024, China

    Qian Wang, Zhihua Cui & Lifang Wang

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  1. Qian Wang
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  2. Zhihua Cui
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Correspondence to Zhihua Cui.

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Wang, Q., Cui, Z. & Wang, L. Charging path optimization for wireless rechargeable sensor network. Peer-to-Peer Netw. Appl. 14, 497–506 (2021). https://doi.org/10.1007/s12083-020-01005-1

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