On the use of non-stationary penalty functions to solve nonlinear constrained optimization problems with GA's
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We discuss the use of non-stationary penalty functions to solve general nonlinear programming problems (NP) using real-valued GAs. The non-stationary penalty is a function of the generation number; as the number of generations increases so does the penalty. Therefore, as the penalty increases it puts more and more selective pressure on the GA to find a feasible solution. The ideas presented in this paper come from two basic areas: calculus-based nonlinear programming and simulated annealing. The non-stationary penalty methods are tested on four NP test cases and the effectiveness of these methods are reported.<<ETX>>
[1] Klaus Schittkowski,et al. Test examples for nonlinear programming codes , 1980 .
[2] Zbigniew Michalewicz,et al. Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.
[3] Gunar E. Liepins,et al. Some Guidelines for Genetic Algorithms with Penalty Functions , 1989, ICGA.