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.

在无线可充电传感器网络（WRSN）中，充电路径规划变得越来越重要。本文提出了一种基于高维多目标优化的充电路径规划模型，该模型考虑了生命周期，距离，能耗和充电时间。同时，提出了一种改进的算法，以非支配排序遗传算法（NSGA）和NSGA-II为框架，改进了基于参考点的多目标进化算法的交叉模式和多样性。 ）进行充电路径规划。最后，通过实验比较验证了充电过程的有效性和充电路径的合理性。