指标 | 网络场景 | $\phi $ (%) | $\overline {\Delta \tau } $ (s) | ${\rm{RN}}$ | ${\rm{SP}}$ | $M_3^*$ | |||||||||
VN-MOAC | NSGA-II | VN-MOAC | NSGA-II | VN-MOAC | NSGA-II | VN-MOAC | NSGA-II | VN-MOAC | NSGA-II | ||||||
最优值 | L1 | 94.02 | 92.31 | 1663.82 | 1812.30 | 45 | 29 | 38.50 | 45.67 | 392.65 | 378.86 | ||||
L2 | 88.94 | 85.78 | 769.24 | 1176.02 | 35 | 25 | 161.93 | 180.14 | 391.60 | 342.24 | |||||
L3 | 95.85 | 93.36 | 1608.94 | 1813.72 | 49 | 27 | 85.69 | 105.50 | 373.73 | 294.36 | |||||
最差值 | L1 | 75.98 | 73.75 | 5184.72 | 5361.46 | 26 | 17 | 790.03 | 883.10 | 31.59 | 20.73 | ||||
L2 | 69.30 | 67.16 | 3784.31 | 3898.69 | 18 | 13 | 794.47 | 869.26 | 42.25 | 24.29 | |||||
L3 | 76.35 | 71.24 | 5197.55 | 5408.48 | 21 | 12 | 690.69 | 726.31 | 83.73 | 73.19 | |||||
平均值 | L1 | 85.01 | 83.47 | 3145.27 | 3359.45 | 38 | 21 | 389.43 | 510.69 | 192.43 | 167.94 | ||||
L2 | 80.17 | 75.44 | 2189.46 | 2411.95 | 26 | 18 | 391.85 | 416.68 | 220.62 | 202.72 | |||||
L3 | 85.98 | 82.76 | 3268.98 | 3333.71 | 37 | 20 | 363.16 | 393.92 | 187.60 | 166.90 | |||||
中值 | L1 | 84.86 | 82.84 | 3137.80 | 3145.03 | 38 | 22 | 410.53 | 527.60 | 125.62 | 95.47 | ||||
L2 | 82.34 | 74.66 | 2285.31 | 2329.71 | 27 | 19 | 352.32 | 406.76 | 204.86 | 171.06 | |||||
L3 | 87.81 | 82.48 | 3308.81 | 3365.68 | 38 | 21 | 347.66 | 384.47 | 182.56 | 172.99 |

Citation: Zengwei LÜ, Zhenchun WEI, Jianghong HAN, Renhao SUN, Chengkai XIA. A Mobile Charging and Data Collecting Algorithm Based on Multi-objective Optimization[J]. Journal of Electronics and Information Technology, 2019, 41(8): 1877-1884. doi: 10.11999/JEIT180897

基于多目标优化的无线传感器网络移动充电及数据收集算法
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关键词:
- 无线可充电传感器网络
- / 数据收集
- / 多目标优化
English
A Mobile Charging and Data Collecting Algorithm Based on Multi-objective Optimization
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[1]
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表 1 VN-MOAC算法和NSGA-II算法计算结果比较
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