FMINCON with multiple constraints

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Hello, I am new with the optimization tool of MATLAB and I have two question regarding my optimization function. I have a function with a vector P[1x6] as input and only one scalar output which I want to optimize. Before setting the constraints, I already have a error:
FMINCON requires all values returned by functions to be of data type double.
But my output it's an scalar, so I'm a bit confused. Here my code:
fun = @facturade;
A = []; b = []; Aeq = []; beq = [];
lb = [0 0 0 0 0 0];
ub = [150 150 150 150 150 150];
x0 = [100 100 100 100 100 100];
%nonlcon = @const;
[x,fval] = fmincon(fun,x0,A,b,Aeq,beq,lb,ub)
Then, I would like to know how to write multiple constrains for the problem, such as:
P(1)<=P(2); P(2)<=P(3); P(3)<=P(4); P(4)<=P(5); P(5)<=P(6);
For what I've seen, it's posible with nonlcon function, but as P it's my input vector for my function fun, I'm not sure how to write the function.
  6 个评论
Torsten
Torsten 2021-5-20
编辑:Torsten 2021-5-20
Insert a print command for the calculated scalar directly in function facturade. What is the output to the screen ?
Further, it seems facturade returns a result of type single, not double. I don't know how this happens since on the terminal where I work, I'm not able to download and read your function file.

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Alan Weiss
Alan Weiss 2021-5-20
I think that your fracturade function is returning data type SINGLE. Perhaps the quickest fix is to include the following call just before the end of the function:
y = double(y);
A better fix would be to determine why the output is single to begin with and fix that. But calling double will enable you to get on with your work.
Alan Weiss
MATLAB mathematical toolbox documentation
  3 个评论
Víctor García
Víctor García 2021-5-20
It workd with y = double(y); but the solution it's the initial point, not an optimal at all!
Alan Weiss
Alan Weiss 2021-5-20
Torsten's comment indicates the reason why: the finite difference steps are too small to get a nonzero gradient estimate. You really need more precision in your calculation.
Barring that, set larger finite difference steps as explained here.
Alan Weiss
MATLAB mathematical toolbox documentation

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