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An adaptive penalty scheme for genetic algorithms in structural optimization
A parameter-less adaptive penalty scheme for genetic algorithms applied to constrained optimization problems is proposed. Using feedback from the evolutionary process the procedure automatically defines a penalty parameter for each constraint. The user is thus relieved from the burden of having to determine sensitive parameter(s) when dealing with every new constrained optimization problem. The procedure is shown to be effective and robust when applied to test problems from the evolutionary computation literature as well as several optimization problems from the structural engineering literature.
An adaptive penalty scheme for genetic algorithms in structural optimization
A parameter-less adaptive penalty scheme for genetic algorithms applied to constrained optimization problems is proposed. Using feedback from the evolutionary process the procedure automatically defines a penalty parameter for each constraint. The user is thus relieved from the burden of having to determine sensitive parameter(s) when dealing with every new constrained optimization problem. The procedure is shown to be effective and robust when applied to test problems from the evolutionary computation literature as well as several optimization problems from the structural engineering literature.
An adaptive penalty scheme for genetic algorithms in structural optimization
Lemonge, Afonso C.C. (author) / Barbosa, Helio J.C. (author)
International Journal for Numerical Methods in Engineering ; 59 ; 703-736
2004
34 Seiten, 60 Quellen
Article (Journal)
English
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