怎么用matlab求解一个优化问题（目标函数非线性，约束函数线性）
问题min f(x)=12*x(1)+21*x(2)+21*x(3)+13*x(4)+20*x(5)+23*x(6)+15*x(7)+17*x(8)+27*x(9)+17*x(10)+19*x(11)+31*x(12)+200*[(x(1)+x(2)+x(3))^0.6+(x(4)+x(5)+x(6))^0.6+(x(7)+x(8)+x(9))^0.6+(x(10)+x(11)+x(12))^0.6]
s.t. x(1)+x(2)+x(3)<=183.55;
x(4)+x(5)+x(6)<=283.55;
x(7)+x(8)+x(9)<=383.55;
x(10)+x(11)+x(12)<=183.55;
x(1)+x(4)+x(7)+x(10)>=116.45;
x(2)+x(5)+x(8)+x(11)>=316.45;
x(3)+x(6)+x(9)+x(12)>=416.45;
x(1),…x(12)>=0;
我是这样求的：
目标函数（运行显示下标不对）
function f=myobj(x)
c = ;
size(x) = ;
y = c.*x;
y = sum(y(:));
s = 0;
for i = 1:4
sg = sum(x(i,:));
s = s+sg^0.6;
end
f = y+200*s;
command window
A= [1,1,1,0,0,0,0,0,0,0,0,0;
0,0,0,1,1,1,0,0,0,0,0,0;
0,0,0,0,0,0,1,1,1,0,0,0;
0,0,0,0,0,0,0,0,0,1,1,1;
-1,0,0,-1,0,0,-1,0,0,-1,0,0;
0,-1,0,0,-1,0,0,-1,0,0,-1,0;
0,0,-1,0,0,-1,0,0,-1,0,0,-1]
b=[200-1.645*10;
300-1.645*10;
400-1.645*10;
200-1.645*10;
-100-1.645*10;
-300-1.645*10;
-400-1.645*10]
x0=;
lb=;
ub=[];
=fmincon(@myobj,x0,A,b,[],[],lb,ub)
运行显示：
Warning: Large-scale (trust region) method does not currently solve this type of problem,
switching to medium-scale (line search).
> In fmincon at 260
??? Error using ==> fmincon
FMINCON cannot continue because user supplied objective function failed with the following error:
Subscript indices must either be real positive integers or logicals.
请热心人士帮忙看下怎么改？谢谢！
[ 本帖最后由 eight 于 2007-7-25 13:10 编辑 ] 加上：
options = optimset('LargeScale','off');
=fmincon(@myobj,x0,A,b,[],[],lb,ub,options) ;
再试试
[ 本帖最后由 花如月 于 2007-7-25 12:25 编辑 ]
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