Thread View: comp.ai.genetic
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Started by Peter Gage
Wed, 27 Jan 1993 23:59
Constraint-handling in GA function optimization
Author: Peter Gage
Date: Wed, 27 Jan 1993 23:59
Date: Wed, 27 Jan 1993 23:59
21 lines
1462 bytes
1462 bytes
Recently there was a request for information on appropriate penalty functions to use for constrained function optimization with genetic algorithms. (Unfortunately I discarded the original message.) I would like to extend the scope of this inquiry to include all methods for handling constraints. It seems that you lose information by shoving constraint violations and objective into a single scalar merit function, and I am interested in methods which treat constraints separately. I have noticed the mention of constraint-handling 'by repair', but it's not clear to me exactly what this means. Is this method used to make a viable genome (e.g. check that every city is represented in travelling salesman problem) so that fitness can be evaluated, or is it applied after fitness has been evaluated so that future fitness can be improved? Are there other methods for handling constraints 'out there'? Please e-mail to me, and I will summarise for the group. Peter Gage
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