How to solve a constrained binary multi-objective optimization problem through genetic algorithm?
7 views (last 30 days)
Show older comments
Atamert Arslan
on 28 Dec 2016
Edited: Atamert Arslan
on 19 Mar 2017
Dear All,
I would like to solve a multi-objective problem that has both equality and inequality constraints and where the decision variables are binary. I would like to find the Pareto front with the help of a genetic algorithm.
The solver gamultiobj handles such binary multi-objective problems but ignores the constraints. Alternatively, I tried defining the variables' bounds to [0,1] and set all variables as integers but failed in that.
Does anybody know how to deal with this issue? Any other toolbox for MATLAB that is capable is also highly appreciated. Thank you!
1 Comment
Laila Qaisi
on 19 Mar 2017
If you have written the code would you please share it as iam trying to find the same. Thanks!
Accepted Answer
Walter Roberson
on 28 Dec 2016
You need to not tell it that you want integer constraints. Instead, you need to supply your own custom mutation and crossover and population files that happen to never generate non-binary values for those positions.
2 Comments
Walter Roberson
on 31 Jan 2017
Just pass A, b, Aeq, beq matrices as usual. Those are evaluated by plain multiplication, which does not need to know that the x values are restricted to integer since it is just multiplication and comparison.
More Answers (1)
Laila Qaisi
on 19 Mar 2017
If you have written the code would you please share it as iam trying to find the same. Thanks!
See Also
Categories
Find more on Genetic Algorithm in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!