r02.rtf

机械优化设计中的约束随机法

                          常用优化方法 ——约束随机法
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                                                                               
一、初始数据
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   设计变量个数     N = 2           不等式约束个数  KG = 5
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   随机方向个数   NSR = 5
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   初始步长        T0 = 0.01          收敛精度     EPS = 1E-8
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   设计变量初始点 X0:
			X[1]=1
			X[2]=1
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   设计变量下界 BL:
			BL[1]=0
			BL[2]=0
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   设计变量上界 BU:
			BU[1]=6
			BU[2]=8
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   初始点目标函数值 F(X0)= 47
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   初始点处的不等约束函数值 G(X0):
				GX[1]= -1.000000E+00
				GX[2]= -1.000000E+00
				GX[3]= -5.000000E+00
				GX[4]= -7.000000E+00
				GX[5]= -9.000000E+00
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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]= 1.006974E+00
			X[2]= 1.005689E+00
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   目标函数值 F(X)= 15.0128266632634
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   设计变量迭代点 X:                           迭代次数  ITE = 2
			X[1]= 5.799832E+00
			X[2]= 4.912752E+00
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   目标函数值 F(X)= 11.0486291399274
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   设计变量迭代点 X:                           迭代次数  ITE = 3
			X[1]= 5.994612E+00
			X[2]= 4.998818E+00
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   目标函数值 F(X)= 11.0161871258091
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   设计变量迭代点 X:                           迭代次数  ITE = 4
			X[1]= 5.999708E+00
			X[2]= 4.995669E+00
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   目标函数值 F(X)= 11.0008940107916
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   设计变量迭代点 X:                           迭代次数  ITE = 5
			X[1]= 5.999989E+00
			X[2]= 4.997073E+00
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   目标函数值 F(X)= 11.0000426299974
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   设计变量迭代点 X:                           迭代次数  ITE = 6
			X[1]= 6.000000E+00
			X[2]= 4.997129E+00
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   目标函数值 F(X)= 11.0000085718491
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   设计变量迭代点 X:                           迭代次数  ITE = 6
			X[1]= 6.000000E+00
			X[2]= 4.997130E+00
  -----------------------------------------------------------------------------
   目标函数值 F(X)= 11.0000082398635
  -----------------------------------------------------------------------------
                                                                               
三、优化结果__数据
===============================================================================
   迭代次数   ITE = 6         目标函数计算次数     IFX = 1292
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   设计变量最优点 X*:
			X[1]= 6.000000E+00
			X[2]= 4.997130E+00
  -----------------------------------------------------------------------------
   最优值 F(X*)= 11.000008239668
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   最优点处的不等约束函数值 G(X*):
				GX[1]= -6.000000E+00
				GX[2]= -4.997130E+00
				GX[3]= -1.136957E-11
				GX[4]= -3.002870E+00
				GX[5]= -2.870476E-03
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--- STOP ---