decline2.m

来自「非常经典的最优化程序」· M 代码 · 共 21 行

%最速下降法(不精确一维搜索,k＝1000,花费时间太多,精度远不能达到要求)
syms x1 x2;
f=50*(x2-x1^2)^2+(1-x1)^2;
v=[x1,x2];
df=jacobian(f,v);
df=df.';
epson=1e-12;x0=[0,0]';g1=subs(df,{x1,x2},{x0(1,1),x0(2,1)});k=0;mul_count=0;sum_count=0;
mul_count=mul_count+7;sum_count=sum_count+4;
while(norm(g1)>epson&k<1000)
    mul_count=mul_count+2;sum_count=sum_count+1;
    p=-g1;
    result=Usearch1(f,x1,x2,df,x0,p);
    arf=result(1);Mul=result(2);Sum=result(3);
    mul_count=mul_count+Mul;sum_count=sum_count+Sum;
    x0=x0+arf*p;
    g1=subs(df,{x1,x2},{x0(1,1),x0(2,1)});
    k=k+1;
    mul_count=mul_count+9;sum_count=sum_count+7;
end;
k
x0