电子测量与仪器学报

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

DOI：

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

作者	单位
赵苏磊	1.合肥工业大学计算机与信息学院
张建军	1.合肥工业大学计算机与信息学院，2.安全关键工业测控技术教育部工程研究中心
魏振春	1.合肥工业大学计算机与信息学院，2.安全关键工业测控技术教育部工程研究中心
吕增威	1.合肥工业大学计算机与信息学院
石雷	1.合肥工业大学计算机与信息学院，2.安全关键工业测控技术教育部工程研究中心
潘杰	1.合肥工业大学计算机与信息学院

Author	Institution
Zhao Sulei	1.School of Computer and Information, Hefei University of Technology
Zhang Jianjun	1.School of Computer and Information, Hefei University of Technology，2.Engineering Research Center of Safety Critical Industrial Measurement and Control Technology, Ministry of Education
Wei Zhenchun	1.School of Computer and Information, Hefei University of Technology，2.Engineering Research Center of Safety Critical Industrial Measurement and Control Technology, Ministry of Education
Lv Zengwei	1.School of Computer and Information, Hefei University of Technology
Shi Lei	1.School of Computer and Information, Hefei University of Technology，2.Engineering Research Center of Safety Critical Industrial Measurement and Control Technology, Ministry of Education
Pan Jie	1.School of Computer and Information, Hefei University of Technology

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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%。

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 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.

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