why ga become infeasible after increasing the size of variables

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Hi, I am trying to use ga to solve a mixed integer optimization problem. I have a problem that ga became infeasible after i enlarged the size of my varibles. For example, if the number of varibles are 80 or 150, ga runs very good. But when it comes to 252 variables, ga immediately becomes infeasible.In my problem, i set my number of variables to "N" which can be changed before the optimization.
Thank you!
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Walter Roberson
Walter Roberson on 7 Sep 2019
Could you post your complete adjusted totalcost file?
My testing before strongly suggested that your linear constraints cannot be met, so it would not matter what your function calculated (provided the result was not infinite or nan) and you would still get told it was infeasible.
BOWEN LI
BOWEN LI on 7 Sep 2019
Sure no problem. totalcost912019.m is the adjusted file.
I put my constraints in the thesis_code2 file.
My linear constriants basically says that:
A1: yi(: , :, t) - yi(:, :, t-1) >= 0 (t=2:N)
A1sub: sij(: , :, t) - sij(:, :, t-1) >= 0 (t=2:N)
A2: for each sij(:, :, t) matrix, the upper and lower half that symmetry to the diagonal are same
A3: negative of A2
A4: for each time period(t), if yi to yj are all "1", then sij is 1, 0 otherwise.
Since the constraints are created based on the paper I referenced which has A1 but not A2 A3 and A4. And based on my x outcome, at least A1 is met. However, A2 - A4, especially A4, should be met in my problem.
Thank you!

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