📄 r09.rtf
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常用优化方法 ——约束随机法
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一、初始数据
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设计变量个数 N = 4 不等式约束个数 KG = 8
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随机方向个数 NSR = 8
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初始步长 T0 = 0.01 收敛精度 EPS = 1E-10
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设计变量初始点 X0:
X[1]=-3
X[2]=-1
X[3]=-3
X[4]=-1
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设计变量下界 BL:
BL[1]=-10
BL[2]=-10
BL[3]=-10
BL[4]=-10
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设计变量上界 BU:
BU[1]=10
BU[2]=10
BU[3]=10
BU[4]=10
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初始点目标函数值 F(X0)= 19175.2
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初始点处的不等约束函数值 G(X0):
GX[1]= -7.000000E+00
GX[2]= -9.000000E+00
GX[3]= -7.000000E+00
GX[4]= -9.000000E+00
GX[5]= -1.300000E+01
GX[6]= -1.100000E+01
GX[7]= -1.300000E+01
GX[8]= -1.100000E+01
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二、计算过程__数据
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设计变量迭代点 X: 迭代次数 ITE = 1
X[1]= -2.992846E+00
X[2]= -9.941641E-01
X[3]= -3.000754E+00
X[4]= -1.003768E+00
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目标函数值 F(X)= 12937.2519249148
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设计变量迭代点 X: 迭代次数 ITE = 10
X[1]= -2.335398E+00
X[2]= 5.481249E+00
X[3]= -1.492622E-02
X[4]= -6.291197E-01
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目标函数值 F(X)= 118.892162545086
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设计变量迭代点 X: 迭代次数 ITE = 20
X[1]= -2.216670E+00
X[2]= 5.059995E+00
X[3]= -5.242606E-03
X[4]= -3.914180E-01
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目标函数值 F(X)= 85.8521255576237
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设计变量迭代点 X: 迭代次数 ITE = 30
X[1]= -2.002269E+00
X[2]= 4.018351E+00
X[3]= -2.980363E-01
X[4]= -3.297709E-01
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目标函数值 F(X)= 39.2482665935216
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设计变量迭代点 X: 迭代次数 ITE = 40
X[1]= -1.936563E+00
X[2]= 3.741277E+00
X[3]= -8.289524E-02
X[4]= -2.200708E-01
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目标函数值 F(X)= 29.5508610523938
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设计变量迭代点 X: 迭代次数 ITE = 50
X[1]= -1.801427E+00
X[2]= 3.234589E+00
X[3]= 6.095722E-02
X[4]= -1.920003E-01
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目标函数值 F(X)= 14.6446675751079
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设计变量迭代点 X: 迭代次数 ITE = 60
X[1]= -1.491243E+00
X[2]= 2.191424E+00
X[3]= -7.159497E-02
X[4]= 8.206872E-02
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目标函数值 F(X)= 2.50128376123086
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设计变量迭代点 X: 迭代次数 ITE = 70
X[1]= -1.482222E+00
X[2]= 2.187785E+00
X[3]= -3.819460E-02
X[4]= -1.102521E-02
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目标函数值 F(X)= 1.62255860249718
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设计变量迭代点 X: 迭代次数 ITE = 80
X[1]= -1.415502E+00
X[2]= 1.995796E+00
X[3]= 9.531801E-02
X[4]= 1.622355E-02
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目标函数值 F(X)= 1.02651509549803
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设计变量迭代点 X: 迭代次数 ITE = 90
X[1]= -1.395406E+00
X[2]= 1.953674E+00
X[3]= 1.967627E-01
X[4]= 3.255794E-02
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目标函数值 F(X)= 0.839270427008787
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设计变量迭代点 X: 迭代次数 ITE = 100
X[1]= -1.389918E+00
X[2]= 1.938086E+00
X[3]= 2.568037E-01
X[4]= 6.742805E-02
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目标函数值 F(X)= 0.731670393002662
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设计变量迭代点 X: 迭代次数 ITE = 110
X[1]= -1.383314E+00
X[2]= 1.907254E+00
X[3]= 3.485566E-01
X[4]= 1.131398E-01
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目标函数值 F(X)= 0.599711670827553
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设计变量迭代点 X: 迭代次数 ITE = 120
X[1]= -1.371852E+00
X[2]= 1.883040E+00
X[3]= 4.060850E-01
X[4]= 1.590979E-01
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目标函数值 F(X)= 0.522148525306093
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设计变量迭代点 X: 迭代次数 ITE = 130
X[1]= -1.342435E+00
X[2]= 1.801350E+00
X[3]= 4.676915E-01
X[4]= 2.155887E-01
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目标函数值 F(X)= 0.412891166029663
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设计变量迭代点 X: 迭代次数 ITE = 140
X[1]= -1.295095E+00
X[2]= 1.677037E+00
X[3]= 5.756242E-01
X[4]= 3.280636E-01
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目标函数值 F(X)= 0.27231366066593
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设计变量迭代点 X: 迭代次数 ITE = 150
X[1]= -1.280891E+00
X[2]= 1.645567E+00
X[3]= 5.969399E-01
X[4]= 3.541280E-01
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目标函数值 F(X)= 0.245221209457051
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设计变量迭代点 X: 迭代次数 ITE = 160
X[1]= -1.261681E+00
X[2]= 1.596943E+00
X[3]= 6.448201E-01
X[4]= 4.139554E-01
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目标函数值 F(X)= 0.200215543075587
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设计变量迭代点 X: 迭代次数 ITE = 170
X[1]= -1.202366E+00
X[2]= 1.445135E+00
X[3]= 7.625668E-01
X[4]= 5.812987E-01
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目标函数值 F(X)= 0.100672061797094
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设计变量迭代点 X: 迭代次数 ITE = 180
X[1]= -1.185840E+00
X[2]= 1.405066E+00
X[3]= 7.830088E-01
X[4]= 6.082665E-01
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目标函数值 F(X)= 0.0828359102463608
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设计变量迭代点 X: 迭代次数 ITE = 190
X[1]= -1.163499E+00
X[2]= 1.356328E+00
X[3]= 8.053511E-01
X[4]= 6.464745E-01
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目标函数值 F(X)= 0.0642383287637106
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设计变量迭代点 X: 迭代次数 ITE = 200
X[1]= -1.141165E+00
X[2]= 1.302726E+00
X[3]= 8.336351E-01
X[4]= 6.948500E-01
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目标函数值 F(X)= 0.0460935147074786
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设计变量迭代点 X: 迭代次数 ITE = 210
X[1]= -1.121846E+00
X[2]= 1.260337E+00
X[3]= 8.590289E-01
X[4]= 7.383653E-01
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目标函数值 F(X)= 0.0338524874273889
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设计变量迭代点 X: 迭代次数 ITE = 220
X[1]= -1.116017E+00
X[2]= 1.245636E+00
X[3]= 8.712287E-01
X[4]= 7.589779E-01
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目标函数值 F(X)= 0.0285398339546135
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设计变量迭代点 X: 迭代次数 ITE = 230
X[1]= -1.098236E+00
X[2]= 1.206381E+00
X[3]= 8.959011E-01
X[4]= 7.994768E-01
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目标函数值 F(X)= 0.0203630610233045
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设计变量迭代点 X: 迭代次数 ITE = 240
X[1]= -1.079812E+00
X[2]= 1.164709E+00
X[3]= 9.110776E-01
X[4]= 8.319539E-01
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目标函数值 F(X)= 0.0140410504902137
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设计变量迭代点 X: 迭代次数 ITE = 250
X[1]= -1.072299E+00
X[2]= 1.148904E+00
X[3]= 9.207507E-01
X[4]= 8.486938E-01
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目标函数值 F(X)= 0.0110040341053261
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设计变量迭代点 X: 迭代次数 ITE = 260
X[1]= -1.065604E+00
X[2]= 1.135485E+00
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