Constraint-handling in GA function optimization

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Article #55

#55

From: Peter Gage
Date: Wed, 27 Jan 1993 23:59

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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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From: peetah@leland.Stanford.EDU (Peter Gage)
Subject: Constraint-handling in GA function optimization
Message-ID: <1993Jan27.235948.6423@leland.Stanford.EDU>
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Date: Wed, 27 Jan 93 23:59:48 GMT
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