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First and foremost, I appreciate your valuable comment @optimizationf
Allow me to provide an overview of approaches for handling constraints, and you can easily find more comprehensive information on this topic through a simple Internet search. There are several methods available for dealing with constraints, which I will outline below:
Constraint-Remove: Ensuring that the condition imposed by the constraint is satisfied.
Solution-Repair: Making necessary modifications or repairs to the answer based on the constraint.
Penalty-Function: Employing a penalty function that assigns penalties based on violations of the constraints criteria. This function can be additive or multiplicative, depending on the nature of your problem.
Multi-objective optimization: Optimizing multiple objectives simultaneously, considering both the main objective and the constraint-related objectives.
Multilayer or co-evolutionary optimization: Utilizing advanced optimization techniques that involve multiple layers or co-evolutionary algorithms to address constraint-related challenges.
For each of the mentioned approaches, I have projects available on my Github page. In the event that there isn't a project covering a specific case mentioned above, I plan to add it to my personal page in the near future.
Hi,
How can we define constraint conditions? Do you think we can do this with the definition of the penalty coefficient?
By the way, thank you for share.
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