Multi functions multi variables optimization
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Hello, I am looking for a better optimization method or algorithm.
Here, I have some variables and some functions.
For example,
I have 5 variables: a, b, c, d, e.
And 4 functions(maybe not 4): 0<F(a,b,c,d,e)<=0.01, 0<G(a,b,c,d,e)<=0.01, 0.9<=H(a,b,c,d,e)<=0.95, I(a,b,c,d,e)=sqrt(1-H(a,b,c,d,e)^2).
BTW, the functions are nonlinear functions, it is complicate and contains cos(),sin().etc.
The variables have constraints:
1<a<2; 2<b<3; 3<c<4; 4<d<5; 5<e<6;
I would like to find the solution under these variable constraints.
I used fsolve before, But I think they are not suitable in this situation.
I am not familiar with optimization algorithm, could any one help me give me some suggestions to address this problem?
I am appreciate if you give me an example to solve those equations. Thank you very much!
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Accepted Answer
Torsten
on 16 Feb 2023
Moved: Torsten
on 16 Feb 2023
Use fmincon.
Define the constraints
1<a<2; 2<b<3; 3<c<4; 4<d<5; 5<e<6
in lb and ub,
define the constraints
0<F(a,b,c,d,e)<=0.01, 0<G(a,b,c,d,e)<=0.01, 0.9<=H(a,b,c,d,e)<=0.95, I(a,b,c,d,e)=sqrt(1-H(a,b,c,d,e)^2)
in the function nonlcon for nonlinear constraints in the array c.
Then simply define the objective function as "0" since you don't want to minimize anything, but you only want to find a feasible point a,b,c,d,e for your problem.
1 Comment
Alan Weiss
on 16 Feb 2023
Torsten is, as usual, spot on. I just want to add that this topic is addressed in the documentation:
and
Alan Weiss
MATLAB mathematical toolbox documentation
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