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Efficient genetic algorithms for solving hard constrained optimization problems

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3 Author(s)
Sareni, B. ; CEGELY, Ecully, France ; Krahenbuhl, L. ; Nicolas, A.

This paper studies many Genetic Algorithm strategies to solve hard-constrained optimization problems. It investigates the role of various genetic operators to avoid premature convergence. In particular, an analysis of niching methods is carried out on a simple function to show advantages and drawbacks of each of them. Comparisons are also performed on an original benchmark based on an electrode shape optimization technique coupled with a charge simulation method

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Magnetics, IEEE Transactions on  (Volume:36 ,  Issue: 4 )