文件名称:最优化实验乘子法
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最优化方法之乘子法,基本的拉格朗日乘子法就是求函数f(x1,x2,...)在约束条件g(x1,x2,...)=0下的极值的方法。
其主要思想是将约束条件函数与原函数联立,从而求出使原函数取得极值的各个变量的解。(The multiplier method of optimization method, the basic Lagrange multiplier method is to find the extreme value of function f (x1, X2,...) under the constraint condition g (x1, X2,...) =0.
The main idea is to combine the constraint condition function with the original function, so as to find out the solution of the variables that make the original function get the extreme value.)
其主要思想是将约束条件函数与原函数联立,从而求出使原函数取得极值的各个变量的解。(The multiplier method of optimization method, the basic Lagrange multiplier method is to find the extreme value of function f (x1, X2,...) under the constraint condition g (x1, X2,...) =0.
The main idea is to combine the constraint condition function with the original function, so as to find out the solution of the variables that make the original function get the extreme value.)
相关搜索: 最优化方法乘子法
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下载文件列表
文件名 | 大小 | 更新时间 |
---|---|---|
最优化实验乘子法 | 0 | 2017-11-15 |
最优化实验乘子法\bfgs.m | 906 | 2017-11-07 |
最优化实验乘子法\fun_f.m | 47 | 2017-11-07 |
最优化实验乘子法\fun_h.m | 41 | 2017-11-07 |
最优化实验乘子法\fun_onesearch.m | 99 | 2017-11-07 |
最优化实验乘子法\fun_phi.m | 115 | 2017-11-07 |
最优化实验乘子法\gfun_f.m | 45 | 2017-11-07 |
最优化实验乘子法\gfun_h.m | 35 | 2017-11-07 |
最优化实验乘子法\gfun_phi.m | 127 | 2017-11-07 |
最优化实验乘子法\main_multiplier.m | 759 | 2017-11-07 |