機(jī)械優(yōu)化設(shè)計(jì)課后程序考核題

1、機(jī)械優(yōu)化設(shè)計(jì)程序考核題1、一維搜索方法程序考核題最優(yōu)解：to = 5.0000fo = 112、無約束優(yōu)化方法程序考核題 初始點(diǎn)：最優(yōu)解：運(yùn)行結(jié)果：Warning: Gradient must be provided for trust-region method; using line-search method instead.> In fminunc at 241Optimization terminated: relative infinity-norm of gradient less than options.TolFun.Computing finite-differenc

2、e Hessian using user-supplied objective function.x = 5.0000 6.0000fval = 1.9895e-012exitflag = 1output = iterations: 7 funcCount: 24 stepsize: 1 firstorderopt: 2.8610e-006 algorithm: 'medium-scale: Quasi-Newton line search' message: 'Optimization terminated: relative infinity-norm of gra

3、dient less than options.TolFun.'grad = 1.0e-005 * 0.0763 -0.2861hessian = 8.0000 0 0 2.00003、約束優(yōu)化方法的程序考核題s.t. 初始點(diǎn)：最優(yōu)解：運(yùn)行結(jié)果 ：Warning: Large-scale (trust region) method does not currently solve this type of problem, switching to medium-scale (line search).> In fmincon at 260c = 6c = 6.0000c = 6

4、.0000c = 2.0000c = 2.0000c = 2.0000c = 9.9341e-009c = 3.9736e-008c = -4.9671e-009Optimization terminated: first-order optimality measure less than options.TolFun and maximum constraint violation is less than options.TolCon.Active inequalities (to within options.TolCon = 1e-006): lower upper ineqlin

5、ineqnonlin 1 1x = 1.0000 1.0000fval = 1.0000exitflag = 1output = iterations: 2 funcCount: 11 stepsize: 1 algorithm: 'medium-scale: SQP, Quasi-Newton, line-search' firstorderopt: 6.6227e-009 cgiterations: message: 1x143 charlambda = lower: 2x1 double upper: 2x1 double eqlin: 0x1 double eqnonlin: 0x1 double ineqlin: 0.6