基于分解多目标烟花算法的WRSN多MC充电规划方法

Multi-MCs charging planning method based on MOFWA/D in wireless rechargeable sensor network

针对无线可充电传感器网络(WRSN)中多MC充电规划策略的能量利用率低以及多MC承担任务不均衡问题,首次联合考虑最大化多MC的能量利用率以及均衡多MC所承担任务,将WRSN中多MC充电规划问题建模为多目标优化问题,并提出基于分解的多目标烟花算法(MOFWA/D)对问题进行求解。结果表明,MOFWA/D算法得到的多MC充电能量与消耗总能量的比值最高达到了33. 49%,优于MOFWA、MOEA/D和Schedule算法,并且算法得到的多MC承担任务的均衡性指标上分别低于MOFWA算法11. 39%、MOEA/D算法43. 67%和Schedule算法79. 29%。

In view of the problem of low energy utilization and unbalanced task taken by multi-MCs in wireless rechargeable sensor network(WRSN),this paper jointly considers maximizing the energy utilization and balancing the tasks of multi-MCs for the first time,and builds the multi-MCs charging planning problem into multi-objective optimization problem,a multi-objective fireworks algorithm based on decomposition(MOFWA/D)is proposed to solve the problem.The experimental results show that the ratio of charging energy to the total energy consumption of the multi-MCs based on the MOFWA/D algorithm is up to 33.49%,which is better than MOFWA,MOEA/D and Schedule algorithm,and the balance index of the multi-MCs obtained by the proposed algorithm is lower than 11.39%of MOFWA algorithm,43.67%of MOEA/D algorithm and 79.29%of schedule algorithm.