计算机科学与探索 ›› 2022, Vol. 16 ›› Issue (10): 2330-2344.DOI: 10.3778/j.issn.1673-9418.2203112
收稿日期:
2022-03-25
修回日期:
2022-06-08
出版日期:
2022-10-01
发布日期:
2022-10-14
通讯作者:
+ E-mail: baixiaobo@xpu.edu.cn作者简介:
白晓波(1983—),男,陕西勉县人,硕士,高级工程师,硕士生导师,CCF专业会员,主要研究方向为信息融合、智能信息处理等。基金资助:
BAI Xiaobo1,2,+(), SHAO Jingfeng1, WANG Tieshan1, LI Bo1,2
Received:
2022-03-25
Revised:
2022-06-08
Online:
2022-10-01
Published:
2022-10-14
About author:
BAI Xiaobo, born in 1983, M.S., senior engineer, M.S. supervisor, professional member of CCF. His research interests include information fusion, intelligent information processing, etc.Supported by:
摘要:
为了解决纺织企业智能化资源配置中的多参数多目标优化问题,提出了Multi-P-LevyFOA。首先,建立纺织企业智能化转型的多参数多目标资源配置模型。然后,在迭代次数小于等于2/3总迭代数时,基于Levy飞行的随机数更新种群位置,扩大搜寻范围,避免陷入局部最优。在迭代大于2/3总次数时,使用均匀分布的随机数更新种群位置,缩小搜寻范围,避免跳出最优值范围。对算法在不同迭代时刻全局和局部寻优能力进行了分析,对Multi-P-LevyFOA的算法时间复杂度进行了分析并与标准FOA和5个改进的FOA进行比较,并证明了其收敛性。将Multi-P-LevyFOA与其他4种改进的FOA进行了性能对比,重点分析了算法阈值SEP在22个benchmark函数上的影响,研究了Levy飞行中
结果
中图分类号:
白晓波, 邵景峰, 王铁山, 李勃. 分段搜索的果蝇算法及其对纺织企业资源配置[J]. 计算机科学与探索, 2022, 16(10): 2330-2344.
BAI Xiaobo, SHAO Jingfeng, WANG Tieshan, LI Bo. Fruit Fly Optimization Algorithm Based on Segmented Search and Resource Allo-cation to Textile Enterprise[J]. Journal of Frontiers of Computer Science and Technology, 2022, 16(10): 2330-2344.
| 均值(Avg) | 标准差(Std) | 最好值(Best) | 最差值(Worst) |
---|---|---|---|---|
0 | -319.40 | 178.16 | -421.14 | -3.95 |
1/5 | -1 582.15 | 199.72 | -2 236.40 | -1 141.24 |
1/4 | -1 585.57 | 195.66 | -2 163.92 | -1 180.22 |
1/3 | -1 550.14 | 195.56 | -2 271.48 | -1 263.22 |
2/5 | -1 595.62 | 203.36 | -2 250.27 | -1 198.90 |
1/2 | -1 580.25 | 209.15 | -2 366.24 | -1 228.63 |
3/5 | -1 599.31 | 222.23 | -2 240.62 | -1 253.24 |
2/3 | -1 598.84 | 182.73 | -2 178.72 | -1 277.98 |
3/4 | -1 594.96 | 214.57 | -2 584.38 | -1 134.37 |
4/5 | -1 549.62 | 171.49 | -2 031.10 | -1 137.61 |
1 | -1 556.10 | 181.97 | -2 058.19 | -1 169.58 |
表1 不同阈值 S E P对寻优结果的影响
Table 1 Influence of different S E P on search results
| 均值(Avg) | 标准差(Std) | 最好值(Best) | 最差值(Worst) |
---|---|---|---|---|
0 | -319.40 | 178.16 | -421.14 | -3.95 |
1/5 | -1 582.15 | 199.72 | -2 236.40 | -1 141.24 |
1/4 | -1 585.57 | 195.66 | -2 163.92 | -1 180.22 |
1/3 | -1 550.14 | 195.56 | -2 271.48 | -1 263.22 |
2/5 | -1 595.62 | 203.36 | -2 250.27 | -1 198.90 |
1/2 | -1 580.25 | 209.15 | -2 366.24 | -1 228.63 |
3/5 | -1 599.31 | 222.23 | -2 240.62 | -1 253.24 |
2/3 | -1 598.84 | 182.73 | -2 178.72 | -1 277.98 |
3/4 | -1 594.96 | 214.57 | -2 584.38 | -1 134.37 |
4/5 | -1 549.62 | 171.49 | -2 031.10 | -1 137.61 |
1 | -1 556.10 | 181.97 | -2 058.19 | -1 169.58 |
算法 | 时间复杂度 |
---|---|
Multi-P-LevyFOA | |
标准FOA | |
CSFOA[ | |
QTFOA[ | |
TEFOA[ | |
MSAD-FOA[ | |
HarmonyFOA[ | |
表2 时间复杂度对比
Table 2 Comparison of time complexity
算法 | 时间复杂度 |
---|---|
Multi-P-LevyFOA | |
标准FOA | |
CSFOA[ | |
QTFOA[ | |
TEFOA[ | |
MSAD-FOA[ | |
HarmonyFOA[ | |
名称 | 函数 | 搜索区间 | 维数 | 最小值 |
---|---|---|---|---|
Shpere | | [-100,100] | 30 | 0 |
Schwefel’s function 2.21 | | [-10,10] | 30 | 0 |
Schwefel’s function 1.2 | | [-100,100] | 30 | 0 |
Schwefel’s function 2.22 | | [-100,100] | 30 | 0 |
Ellipsoid | | [-100,100] | 30 | 0 |
Sum of different powers | | [-1,1] | 30 | 0 |
Dejong’s noisy | | [-1.28,1.28] | 30 | 0 |
Zakharow | | [-5,10] | 30 | 0 |
表3 普通单峰函数
Table 3 Universal unimodal functions
名称 | 函数 | 搜索区间 | 维数 | 最小值 |
---|---|---|---|---|
Shpere | | [-100,100] | 30 | 0 |
Schwefel’s function 2.21 | | [-10,10] | 30 | 0 |
Schwefel’s function 1.2 | | [-100,100] | 30 | 0 |
Schwefel’s function 2.22 | | [-100,100] | 30 | 0 |
Ellipsoid | | [-100,100] | 30 | 0 |
Sum of different powers | | [-1,1] | 30 | 0 |
Dejong’s noisy | | [-1.28,1.28] | 30 | 0 |
Zakharow | | [-5,10] | 30 | 0 |
名称 | 函数 | 搜索区间 | 维数 | 最小值 |
---|---|---|---|---|
Easom | | [-100,100] | 2 | 0 |
Matyas | | [-10,10] | 2 | 0 |
表4 低维度单峰函数
Table 4 Low-dimensional unimodal functions
名称 | 函数 | 搜索区间 | 维数 | 最小值 |
---|---|---|---|---|
Easom | | [-100,100] | 2 | 0 |
Matyas | | [-10,10] | 2 | 0 |
名称 | 函数 | 搜索区间 | 维数 | 最小值 |
---|---|---|---|---|
Schwefel | | [-500,500] | 30 | -418.982 9 |
Rastringin | | [-5.12,5.12] | 30 | 0 |
Ackley | | [-32,32] | 30 | 0 |
Griewank | | [-600,600] | 30 | 0 |
Levy | | [-10,10] | 30 | 0 |
Powell | | [-4,5] | 30 | 0 |
Syblinski-Tang | | [-5,5] | 30 | -39.165 99 |
表5 普通多峰函数
Table 5 Universal multimodal functions
名称 | 函数 | 搜索区间 | 维数 | 最小值 |
---|---|---|---|---|
Schwefel | | [-500,500] | 30 | -418.982 9 |
Rastringin | | [-5.12,5.12] | 30 | 0 |
Ackley | | [-32,32] | 30 | 0 |
Griewank | | [-600,600] | 30 | 0 |
Levy | | [-10,10] | 30 | 0 |
Powell | | [-4,5] | 30 | 0 |
Syblinski-Tang | | [-5,5] | 30 | -39.165 99 |
名称 | 函数 | 搜索区间 | 维数 | 最小值 |
---|---|---|---|---|
Cross-in-tray | | [-10,10] | 2 | -2.062 60 |
Drop-wave | | [-5.12,5.12] | 2 | -1.000 00 |
Schaffer function N.2 | | [-100,100] | 2 | 0 |
Hartman1 | | [1,3] | 3 | -3.860 00 |
Hartman2 | | [0,1] | 6 | -3.320 00 |
表6 低维度多峰函数
Table 6 Low-dimensional multimodal functions
名称 | 函数 | 搜索区间 | 维数 | 最小值 |
---|---|---|---|---|
Cross-in-tray | | [-10,10] | 2 | -2.062 60 |
Drop-wave | | [-5.12,5.12] | 2 | -1.000 00 |
Schaffer function N.2 | | [-100,100] | 2 | 0 |
Hartman1 | | [1,3] | 3 | -3.860 00 |
Hartman2 | | [0,1] | 6 | -3.320 00 |
函数 | Multi-P-LevyFOA | CSFOA[ | QTFOA[ | TEFOA[ | HarmonyFOA[ | |||||
---|---|---|---|---|---|---|---|---|---|---|
Avg | Std | Avg | Std | Avg | Std | Avg | Std | Avg | Std | |
| 0 | 0 | 1.69E-03 | 1.69E-03 | 0 | 0 | 5.82E-03 | 2.71E-03 | 1.50E-03 | 1.51E-07 |
| 0 | 0 | 2.26E+00 | 2.26E+00 | 0 | 0 | 2.66E+00 | 3.70E-01 | 2.11E+00 | 9.31E-04 |
| 0 | 0 | 5.32E-01 | 5.32E-01 | 0 | 0 | 1.23E+00 | 2.67E-01 | 4.72E-01 | 5.50E-05 |
| 0 | 0 | 9.06E-03 | 9.06E-03 | 0 | 0 | 5.14E-02 | 4.40E-02 | 7.07E-03 | 1.76E-18 |
| 0 | 0 | 0.026 7 | 0.002 4 | 0 | 0 | 0.138 1 | 0.232 3 | 0.023 2 | 0 |
| 0 | 3.26E-05 | 1.71E+00 | 6.78E-16 | 0 | 0 | 1.71E+00 | 6.78E-16 | 1.34E+00 | 5.92E-02 |
| 3.21E-04 | 5.05E-04 | 4.33E+01 | 2.58E-05 | 1.40E-05 | 1.47E-05 | 1.00E+02 | 1.49E+02 | 3.93E+01 | 3.68E-01 |
| 0 | 0 | 332 844.189 6 | 211 786.588 2 | 0 | 0 | 174 426.286 9 | 166 459.09 | 72 042.38 | 165.013 3 |
| -0.904 2 | 0.204 4 | -3.17E-09 | 2.08E-10 | 1 | 2.92E-08 | -2.49E-06 | 1.27E-05 | -6.29E-07 | 4.24E-07 |
| 0 | 0 | 2.38E-04 | 4.16E-05 | 2.23E-231 | 0 | 1.25E-03 | 1.91E-03 | 1.85E-04 | 3.28E-06 |
| -1.71E+03 | 147.142 0 | -4.18E-03 | 3.00E-03 | 1.25E+01 | 3.56E-02 | -2.40E+00 | 11.610 0 | -3.62E+01 | 7.744 0 |
| 0 | 0 | 125.095 7 | 12.962 6 | 0 | 0 | 143.584 7 | 27.998 6 | 102.523 5 | 0.836 5 |
| 8.88E-16 | 0 | 1.26E-01 | 7.69E-03 | 8.88E-16 | 0 | 2.24E-01 | 9.05E-02 | 1.14E-01 | 2.14E-05 |
| 6.12E-07 | 2.52E-06 | 3.18E-06 | 3.13E-07 | 0 | 0 | 2.36E-05 | 3.40E-05 | 2.78E-06 | 1.03E-10 |
| 130.885 0 | 11.028 6 | 211.326 0 | 9.876 9 | 2.726 0 | 0.104 0 | 168.895 0 | 13.018 8 | 110.509 2 | 39.082 9 |
| 0 | 0 | 28.055 4 | 4.071 8 | 0 | 0 | 62.960 7 | 79.915 1 | 19.214 5 | 0.098 2 |
| -289.503 6 | 39.322 6 | -34.022 4 | 14.724 9 | -10.780 0 | 8.015 0 | -105.477 8 | 19.792 5 | -148.658 3 | 88.187 8 |
| -2.062 2 | 0.000 4 | -0.142 9 | 0.134 9 | -1.809 0 | 9.03E-02 | -0.617 7 | 0.739 3 | -2.182 8 | 0.061 7 |
| -4.000 0 | 0 | 3.827 0 | 0.157 8 | 0 | 0 | 3.724 0 | 0.141 3 | -4.000 0 | 0 |
| 0 | 0 | 1.08E-07 | 1.21E-08 | 0 | 0 | 5.44E-07 | 1.59E-06 | 9.93E-08 | 2.98E-10 |
| -3.856 9 | 0.401 1 | -0.727 5 | 0.408 7 | 0.357 0 | 0.272 0 | -2.305 3 | 0.439 6 | -3.713 8 | 0.039 2 |
| -3.065 5 | 0.606 9 | -0.000 9 | 0.002 1 | 0.986 0 | 0.439 0 | -0.014 1 | 0.001 9 | -0.343 1 | 0.214 8 |
胜: 18, 败: 4 | 胜: 15, 败: 7 |
表7 Multi-P-LevyFOA与4个算法结果对比
Table 7 Multi-P-LevyFOA compared with 4 algorithms
函数 | Multi-P-LevyFOA | CSFOA[ | QTFOA[ | TEFOA[ | HarmonyFOA[ | |||||
---|---|---|---|---|---|---|---|---|---|---|
Avg | Std | Avg | Std | Avg | Std | Avg | Std | Avg | Std | |
| 0 | 0 | 1.69E-03 | 1.69E-03 | 0 | 0 | 5.82E-03 | 2.71E-03 | 1.50E-03 | 1.51E-07 |
| 0 | 0 | 2.26E+00 | 2.26E+00 | 0 | 0 | 2.66E+00 | 3.70E-01 | 2.11E+00 | 9.31E-04 |
| 0 | 0 | 5.32E-01 | 5.32E-01 | 0 | 0 | 1.23E+00 | 2.67E-01 | 4.72E-01 | 5.50E-05 |
| 0 | 0 | 9.06E-03 | 9.06E-03 | 0 | 0 | 5.14E-02 | 4.40E-02 | 7.07E-03 | 1.76E-18 |
| 0 | 0 | 0.026 7 | 0.002 4 | 0 | 0 | 0.138 1 | 0.232 3 | 0.023 2 | 0 |
| 0 | 3.26E-05 | 1.71E+00 | 6.78E-16 | 0 | 0 | 1.71E+00 | 6.78E-16 | 1.34E+00 | 5.92E-02 |
| 3.21E-04 | 5.05E-04 | 4.33E+01 | 2.58E-05 | 1.40E-05 | 1.47E-05 | 1.00E+02 | 1.49E+02 | 3.93E+01 | 3.68E-01 |
| 0 | 0 | 332 844.189 6 | 211 786.588 2 | 0 | 0 | 174 426.286 9 | 166 459.09 | 72 042.38 | 165.013 3 |
| -0.904 2 | 0.204 4 | -3.17E-09 | 2.08E-10 | 1 | 2.92E-08 | -2.49E-06 | 1.27E-05 | -6.29E-07 | 4.24E-07 |
| 0 | 0 | 2.38E-04 | 4.16E-05 | 2.23E-231 | 0 | 1.25E-03 | 1.91E-03 | 1.85E-04 | 3.28E-06 |
| -1.71E+03 | 147.142 0 | -4.18E-03 | 3.00E-03 | 1.25E+01 | 3.56E-02 | -2.40E+00 | 11.610 0 | -3.62E+01 | 7.744 0 |
| 0 | 0 | 125.095 7 | 12.962 6 | 0 | 0 | 143.584 7 | 27.998 6 | 102.523 5 | 0.836 5 |
| 8.88E-16 | 0 | 1.26E-01 | 7.69E-03 | 8.88E-16 | 0 | 2.24E-01 | 9.05E-02 | 1.14E-01 | 2.14E-05 |
| 6.12E-07 | 2.52E-06 | 3.18E-06 | 3.13E-07 | 0 | 0 | 2.36E-05 | 3.40E-05 | 2.78E-06 | 1.03E-10 |
| 130.885 0 | 11.028 6 | 211.326 0 | 9.876 9 | 2.726 0 | 0.104 0 | 168.895 0 | 13.018 8 | 110.509 2 | 39.082 9 |
| 0 | 0 | 28.055 4 | 4.071 8 | 0 | 0 | 62.960 7 | 79.915 1 | 19.214 5 | 0.098 2 |
| -289.503 6 | 39.322 6 | -34.022 4 | 14.724 9 | -10.780 0 | 8.015 0 | -105.477 8 | 19.792 5 | -148.658 3 | 88.187 8 |
| -2.062 2 | 0.000 4 | -0.142 9 | 0.134 9 | -1.809 0 | 9.03E-02 | -0.617 7 | 0.739 3 | -2.182 8 | 0.061 7 |
| -4.000 0 | 0 | 3.827 0 | 0.157 8 | 0 | 0 | 3.724 0 | 0.141 3 | -4.000 0 | 0 |
| 0 | 0 | 1.08E-07 | 1.21E-08 | 0 | 0 | 5.44E-07 | 1.59E-06 | 9.93E-08 | 2.98E-10 |
| -3.856 9 | 0.401 1 | -0.727 5 | 0.408 7 | 0.357 0 | 0.272 0 | -2.305 3 | 0.439 6 | -3.713 8 | 0.039 2 |
| -3.065 5 | 0.606 9 | -0.000 9 | 0.002 1 | 0.986 0 | 0.439 0 | -0.014 1 | 0.001 9 | -0.343 1 | 0.214 8 |
胜: 18, 败: 4 | 胜: 15, 败: 7 |
函数 | | | | | | | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Avg | Std | Avg | Std | Avg | Std | Avg | Std | Avg | Std | Avg | Std | |
| 8.79E-03 | 4.17E-03 | 2.62E-82 | 8.29E-82 | 2.42E-234 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 4.37E+00 | 8.53E-01 | 8.87E-08 | 1.20E-07 | 2.35E-27 | 8.30E-27 | 1.38E-55 | 2.50E-56 | 2.11E-104 | 7.79E-105 | 4.44E-83 | 1.14E-82 |
| 1.14E-01 | 7.33E-02 | 1.70E-80 | 2.67E-80 | 1.19E-221 | 0 | 1.35E-303 | 0 | 0 | 0 | 0 | 0 |
| 3.59E-02 | 1.20E-02 | 4.09E-37 | 1.29E-36 | 1.18E-117 | 5.10E-117 | 0 | 0 | 0 | 0 | 0 | 0 |
| 0.145 9 | 0.084 3 | 9.35E-83 | 2.81E-82 | 9.35E-240 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1.76E+01 | 2.108 8 | 2.40E-07 | 5.25E-07 | 6.61E-53 | 1.37E-52 | 2.13E-113 | 3.63E-113 | 1.51E-211 | 0 | 6.25E-40 | 1.98E-39 |
| 4.28E+02 | 9.93E+01 | 9.73E-05 | 1.13E-04 | 1.16E-04 | 1.66E-04 | 1.83E-04 | 1.81E-04 | 3.79E-04 | 3.79E-04 | 1.69E-03 | 9.21E-04 |
| 9.705 0 | 3.598 3 | 7.29E-10 | 1.28E-09 | 7.28E-51 | 1.10E-50 | 3.47E-110 | 1.84E-110 | 8.36E-208 | 0 | 1.99E-145 | 6.30E-145 |
| -0.960 9 | 0.028 9 | -0.802 0 | 0.204 1 | -0.896 8 | 0.063 1 | -0.821 8 | 0.152 0 | -0.880 2 | 0.119 4 | -0.792 3 | 0.128 1 |
| 1.68E-05 | 0 | 1.49E-14 | 0 | 5.04E-54 | 0 | 1.48E-115 | 0 | 5.15E-213 | 0 | 4.79E-208 | 0 |
| -421.000 0 | 190.410 0 | -1.70E+03 | 228.786 2 | -1.56E+03 | 217.547 1 | -1.57E+03 | 215.110 3 | -1.75E+03 | 223.040 6 | -1.64E+03 | 203.394 7 |
| 207.505 6 | 12.216 5 | 0.000 1 | 0.000 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 4.05E-01 | 1.68E-01 | 8.88E-16 | 0 | 8.88E-16 | 0 | 8.88E-16 | 0 | 8.88E-16 | 0 | 8.88E-16 | 0 |
| 2.70E-05 | 3.19E-05 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 118.384 2 | 11.392 9 | 137.824 4 | 5.903 0 | 137.706 9 | 10.395 7 | 134.767 1 | 7.342 8 | 139.537 1 | 6.340 3 | 137.607 3 | 11.121 9 |
| 9.23E+01 | 42.264 3 | 1.26E-05 | 1.51E-05 | 7.71E-48 | 1.96E-48 | 1.45E-109 | 6.20E-110 | 9.09E-207 | 0 | 6.86E-82 | 1.18E-81 |
| -278.258 9 | 23.256 9 | -276.207 7 | 27.140 6 | -269.071 6 | 16.207 1 | -296.682 5 | 30.174 1 | -280.231 0 | 31.588 4 | -275.674 7 | 30.631 2 |
| -2.061 8 | 0.000 9 | -2.062 2 | 0.000 3 | -2.061 6 | 0.001 1 | -2.062 1 | 0.000 5 | -2.061 8 | 0.000 7 | -2.061 4 | 0.000 8 |
| -4.000 0 | 0 | -4.000 0 | 0 | -4.000 0 | 0 | -4.000 0 | 0 | -4.000 0 | 0 | -4.000 0 | 0 |
| 5.92E-09 | 3.78E-09 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| -2.517 2 | 0.629 9 | -3.844 4 | 0.025 5 | -3.817 0 | 0.143 9 | -3.818 6 | 0.130 1 | -3.824 7 | 0.113 0 | -3.860 0 | 0.002 9 |
| -0.945 2 | 0.994 3 | -2.775 6 | 0.585 9 | -2.780 7 | 0.454 7 | -2.780 2 | 0.543 7 | -2.912 6 | 0.345 7 | -3.020 2 | 0.279 2 |
胜:3,败:19,波动:1 | 胜:6,败:16,波动:5 | 胜:5,败:17,波动:6 | 胜: 9,败:13,波动:7 | 胜:15,败:9,波动:6 | 胜:11,败:11,波动:4 |
表8 S E P对Multi-P-LevyFOA的影响
Table 8 Influence of value of S E P on Multi-P-LevyFOA
函数 | | | | | | | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Avg | Std | Avg | Std | Avg | Std | Avg | Std | Avg | Std | Avg | Std | |
| 8.79E-03 | 4.17E-03 | 2.62E-82 | 8.29E-82 | 2.42E-234 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 4.37E+00 | 8.53E-01 | 8.87E-08 | 1.20E-07 | 2.35E-27 | 8.30E-27 | 1.38E-55 | 2.50E-56 | 2.11E-104 | 7.79E-105 | 4.44E-83 | 1.14E-82 |
| 1.14E-01 | 7.33E-02 | 1.70E-80 | 2.67E-80 | 1.19E-221 | 0 | 1.35E-303 | 0 | 0 | 0 | 0 | 0 |
| 3.59E-02 | 1.20E-02 | 4.09E-37 | 1.29E-36 | 1.18E-117 | 5.10E-117 | 0 | 0 | 0 | 0 | 0 | 0 |
| 0.145 9 | 0.084 3 | 9.35E-83 | 2.81E-82 | 9.35E-240 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1.76E+01 | 2.108 8 | 2.40E-07 | 5.25E-07 | 6.61E-53 | 1.37E-52 | 2.13E-113 | 3.63E-113 | 1.51E-211 | 0 | 6.25E-40 | 1.98E-39 |
| 4.28E+02 | 9.93E+01 | 9.73E-05 | 1.13E-04 | 1.16E-04 | 1.66E-04 | 1.83E-04 | 1.81E-04 | 3.79E-04 | 3.79E-04 | 1.69E-03 | 9.21E-04 |
| 9.705 0 | 3.598 3 | 7.29E-10 | 1.28E-09 | 7.28E-51 | 1.10E-50 | 3.47E-110 | 1.84E-110 | 8.36E-208 | 0 | 1.99E-145 | 6.30E-145 |
| -0.960 9 | 0.028 9 | -0.802 0 | 0.204 1 | -0.896 8 | 0.063 1 | -0.821 8 | 0.152 0 | -0.880 2 | 0.119 4 | -0.792 3 | 0.128 1 |
| 1.68E-05 | 0 | 1.49E-14 | 0 | 5.04E-54 | 0 | 1.48E-115 | 0 | 5.15E-213 | 0 | 4.79E-208 | 0 |
| -421.000 0 | 190.410 0 | -1.70E+03 | 228.786 2 | -1.56E+03 | 217.547 1 | -1.57E+03 | 215.110 3 | -1.75E+03 | 223.040 6 | -1.64E+03 | 203.394 7 |
| 207.505 6 | 12.216 5 | 0.000 1 | 0.000 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 4.05E-01 | 1.68E-01 | 8.88E-16 | 0 | 8.88E-16 | 0 | 8.88E-16 | 0 | 8.88E-16 | 0 | 8.88E-16 | 0 |
| 2.70E-05 | 3.19E-05 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 118.384 2 | 11.392 9 | 137.824 4 | 5.903 0 | 137.706 9 | 10.395 7 | 134.767 1 | 7.342 8 | 139.537 1 | 6.340 3 | 137.607 3 | 11.121 9 |
| 9.23E+01 | 42.264 3 | 1.26E-05 | 1.51E-05 | 7.71E-48 | 1.96E-48 | 1.45E-109 | 6.20E-110 | 9.09E-207 | 0 | 6.86E-82 | 1.18E-81 |
| -278.258 9 | 23.256 9 | -276.207 7 | 27.140 6 | -269.071 6 | 16.207 1 | -296.682 5 | 30.174 1 | -280.231 0 | 31.588 4 | -275.674 7 | 30.631 2 |
| -2.061 8 | 0.000 9 | -2.062 2 | 0.000 3 | -2.061 6 | 0.001 1 | -2.062 1 | 0.000 5 | -2.061 8 | 0.000 7 | -2.061 4 | 0.000 8 |
| -4.000 0 | 0 | -4.000 0 | 0 | -4.000 0 | 0 | -4.000 0 | 0 | -4.000 0 | 0 | -4.000 0 | 0 |
| 5.92E-09 | 3.78E-09 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| -2.517 2 | 0.629 9 | -3.844 4 | 0.025 5 | -3.817 0 | 0.143 9 | -3.818 6 | 0.130 1 | -3.824 7 | 0.113 0 | -3.860 0 | 0.002 9 |
| -0.945 2 | 0.994 3 | -2.775 6 | 0.585 9 | -2.780 7 | 0.454 7 | -2.780 2 | 0.543 7 | -2.912 6 | 0.345 7 | -3.020 2 | 0.279 2 |
胜:3,败:19,波动:1 | 胜:6,败:16,波动:5 | 胜:5,败:17,波动:6 | 胜: 9,败:13,波动:7 | 胜:15,败:9,波动:6 | 胜:11,败:11,波动:4 |
项1 | 项2 | 项3 | 项4 | 项5 | 结果 |
---|---|---|---|---|---|
0.157 | 0.166 | 0.435 | 1.026 | 0.019 | 0 |
1.084 | 0.180 | 0.223 | 0.728 | 0.833 | 1 |
0.223 | 0.200 | 0.516 | 0.385 | 0.020 | 1 |
1.215 | 0.213 | 0.317 | 1.040 | 1.033 | 1 |
0.384 | 0.223 | 0.256 | 0.947 | 0.994 | 1 |
1.606 | 0.228 | 0.273 | 1.063 | 1.007 | 1 |
1.168 | 0.245 | 0.333 | 0.938 | 0.968 | 0 |
0.342 | 0.262 | 0.338 | 0.189 | 0.967 | 0 |
0.868 | 0.259 | 0.261 | 0.998 | 0.996 | 0 |
0.519 | 0.265 | 0.238 | 0.889 | 0.005 | 1 |
表9 测试数据
Table 9 Test data
项1 | 项2 | 项3 | 项4 | 项5 | 结果 |
---|---|---|---|---|---|
0.157 | 0.166 | 0.435 | 1.026 | 0.019 | 0 |
1.084 | 0.180 | 0.223 | 0.728 | 0.833 | 1 |
0.223 | 0.200 | 0.516 | 0.385 | 0.020 | 1 |
1.215 | 0.213 | 0.317 | 1.040 | 1.033 | 1 |
0.384 | 0.223 | 0.256 | 0.947 | 0.994 | 1 |
1.606 | 0.228 | 0.273 | 1.063 | 1.007 | 1 |
1.168 | 0.245 | 0.333 | 0.938 | 0.968 | 0 |
0.342 | 0.262 | 0.338 | 0.189 | 0.967 | 0 |
0.868 | 0.259 | 0.261 | 0.998 | 0.996 | 0 |
0.519 | 0.265 | 0.238 | 0.889 | 0.005 | 1 |
迭代次数 | 种群数 | | |||||
---|---|---|---|---|---|---|---|
| | | |||||
2 | 2 | 0.320 9 | 0.566 0 | 0.715 4 | |||
3 | 3 | 0.194 3 | 0.328 6 | 0.376 6 | |||
4 | 4 | 0.172 8 | 0.245 6 | 0.324 4 | |||
5 | 5 | 0.166 1 | 0.180 8 | 0.242 4 | |||
10 | 10 | 0.155 7 | 0.157 3 | 0.158 8 | |||
20 | 20 | 0.154 7 | 0.154 6 | 0.155 6 | |||
30 | 30 | 0.153 5 | 0.153 7 | 0.154 3 | |||
40 | 40 | 0.153 3 | 0.153 4 | 0.153 9 | |||
50 | 50 | 0.153 1 | 0.153 2 | 0.153 7 | |||
60 | 60 | 0.153 2 | 0.153 0 | 0.153 2 | |||
70 | 70 | 0.153 0 | 0.153 2 | 0.153 1 | |||
80 | 80 | 0.153 0 | 0.153 1 | 0.153 0 | |||
90 | 90 | 0.153 1 | 0.152 9 | 0.153 1 |
表10 β对Multi-P-LevyFOA的影响
Table 10 Influence of value of βon Multi-P-LevyFOA
迭代次数 | 种群数 | | |||||
---|---|---|---|---|---|---|---|
| | | |||||
2 | 2 | 0.320 9 | 0.566 0 | 0.715 4 | |||
3 | 3 | 0.194 3 | 0.328 6 | 0.376 6 | |||
4 | 4 | 0.172 8 | 0.245 6 | 0.324 4 | |||
5 | 5 | 0.166 1 | 0.180 8 | 0.242 4 | |||
10 | 10 | 0.155 7 | 0.157 3 | 0.158 8 | |||
20 | 20 | 0.154 7 | 0.154 6 | 0.155 6 | |||
30 | 30 | 0.153 5 | 0.153 7 | 0.154 3 | |||
40 | 40 | 0.153 3 | 0.153 4 | 0.153 9 | |||
50 | 50 | 0.153 1 | 0.153 2 | 0.153 7 | |||
60 | 60 | 0.153 2 | 0.153 0 | 0.153 2 | |||
70 | 70 | 0.153 0 | 0.153 2 | 0.153 1 | |||
80 | 80 | 0.153 0 | 0.153 1 | 0.153 0 | |||
90 | 90 | 0.153 1 | 0.152 9 | 0.153 1 |
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