How can I convert a function with multivariable input to a function with single vector input?

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Junho Kweon
Junho Kweon 2022-3-31
评论： Star Strider 2022-3-31
Hi, I want to use fmincon, and fmincon can deal with only function with single vector input.
When my formula is as below, it works well.
fun = @(x) x(1)^2+x(2)^2;
fmincon(fun,[1,1])
However, if the function form has multiple input as below, it does not work.
Is there any way to convert the fun2 below to the function with single vector input as the example above?
fun2 = @(x,y) x^2+y^2;
fmincon(fun2,[1,1]) % this does not work

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回答（1 个）

Star Strider
Star Strider 2022-3-31
Ran in:
Do essentially the same thing, creating it with another anonymous function around it —
fun2 = @(x,y) x^2+y^2;
fmincon(@(b)fun2(b(1),b(2)),[1,1]) % now it works!
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.
ans = 1×2
0 0
.
  2 个评论
Junho Kweon
Junho Kweon 2022-3-31
Thank you so much @Star Strider!!
Is there any generalized way for this for the case of there are n-number of input element without typing b(1), b(2),....b(n)?
Star Strider
Star Strider 2022-3-31
Ran in:
My pleasure!
I am not aware of any. The ‘shell’ anonymous function would have to be writen specifically for each funciton.
For example, if the function needed to have extra parameters passed to it:
fun2 = @(x,y,a,b) a*x^2+b*y^2;
a = 3;
b = 11;
fmincon(@(b)norm(fun2(b(1),b(2),a,b)),[1,1]) % now it works!
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.
ans = 1×2
1.0e-03 * 0.0019 -0.2844
There could not possibly be a general rule that would apply to all functions.
.

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