Local Minimum Possible Final Point Equals Initial Point The initial point seems to be a local minimum or solution because the first-order optimality measure is close to 0. You might be unhappy with this result, since the solver did not improve your initial point.
在命令窗口输入: fun = @(x)(x-1)^2 [x,fval] = fseminf(fun,0.2,1,@ seminfcon11_13) 输出结果如下: fun = @(x)(x-1)^2 Local minimum found that satisfies the constraints. Optimization completed because the objective function is non-decreasing in feasible directions, to within the ...
可以认为得到的局部极小值是最优解。因为 Local minimum found that satisfies the constraints. 这句提示说明，已得到满足约束条件的局部极小值。而 Optimization completed because the objective function is non-decreasing in feasible directions, to within the default value of the function tolerance...
message: '↵Local minimum found.↵↵Optimization completed because the size of the gradient is less than↵the value of the optimality tolerance.↵↵<stopping criteria details>↵↵Optimization completed: The first-order optimality measure, 7.685279e-07, is less ↵than options.OptimalityT...
Local minimum found that satisfies the constraints. Optimization completed because the objective function is non-decreasing in feasible directions, to within the value of the optimality tolerance, and constraints are satisfied to within the value of the constraint tolerance. ...
Local minimum found. Optimization completed because the size of the gradient is less than the default value of the function tolerance. <stopping criteria details> optTheta = 0.3000 0.8600 functionVal = 0.0720 exitFlag = 1 即得y=0.3+0.86x; 验证: function [ parameter ] = check...
Local minimum found. Optimization completed because the size of the gradient is less than the default value of the function tolerance. <stopping criteria details> a = -1.0000 1.0000 1.5708 -0.0000 ss = 8.7594e-29 >> xf=0:0.05:8; yfit=f(a,xf); plot(xf,sin(xf),'ro',xf,yfit,'b-'...
Local minimum found that satisfies the constraints.Optimization completed because the objective function is non-decreasing in feasible directions, to within the default value of the function tolerance,and constraints are satisfied to within the default value of the constraint tolerance.<stopping criteria ...
>> fminunc(@(x)100*(x(2)-x(1)^2)^2+(1-x(1))^2,[0 0])Warning: Gradient must be provided for trust-region algorithm; using quasi-newton algorithm instead. > In fminunc (line 403)Local minimum found.Optimization completed because the size of the gradient is less thanthe...
using active-set algorithm. You could also try the interior-point or sqp algorithms: set the Algorithm option to 'interior-point' or 'sqp' and rerun. For more help, see Choosing the Algorithm in the documentation.> In fmincon at 472 Local minimum found that satisfies the ...