赵苏磊,张建军,魏振春,吕增威,石雷,潘杰.基于分解多目标烟花算法的WRSN[J].电子测量与仪器学报,2019,33(1):23-30 |
基于分解多目标烟花算法的WRSN |
Multi MCs charging planning method based on MOFWA/D in wireless rechargeable sensor network |
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DOI: |
中文关键词: 无线可充电传感器网络 多MC 充电规划 多目标优化算法 |
英文关键词:wireless rechargeable sensor network multiple mobile chargers charging planning multi objective optimization algorithm |
基金项目:国家自然科学基金(61502142, 61501161)、国家国际科技合作专项(2015DFI12950)资助 |
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中文摘要: |
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3349%, 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1139%、MOEA/D算法4367%和Schedule算法7929%。 |
英文摘要: |
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 3349%, 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 1139% of MOFWA algorithm, 4367% of MOEA/D algorithm and 7929% of schedule algorithm. |
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