Nonlinear Constraints in Multijob optimization

Hello,

I am running a multijob optimization with some design variables (3 or even more like 15 let's say x1,x2,...,x15) and I want to minimize my objective function let's say f. With every set of (x1,x2,...,x15) a specific array can be computed (let's say Y) and I want my constraint to be the elements of Y be always descending (Y1<Y2<...<Yn) . I thought that the solution to this was to introduce a variable k that when it is equal to zero then Y would be descending and when it k equals to 1 then Y would not be descending but it did not work. I got results that did not take into consideration this constraint. How can I prevent matlab from giving me such a result?

Another relevant question is how to say to matlab that ''dont give me results that f (objective function) is biger than 0.2 for example...

Thank you

Answer 1

[Alan Weiss]

Your constraints can be formulated as nonlinear constraints. Make sure that you read and follow the note on that page.

Alan Weiss

MATLAB mathematical toolbox documentation

[Panagiotis Koronaios]

function [C Ceq] = nonlinear_constraints(x)

[....]

flag=0;

for i=1:numel(Y)-1

if Y(i+1)>Y(i)

flag=flag+1;

end

end

C = flg-5;

Ceq = [];

The truth is that my design variables and the restriction is not directly connected as you can see above. I want to prevent matlab from giving my results that C>=5 but this constraint is ignored. Do you know how to fix this?