Published in
2007 IEEE Congress on Evolutionary Computation
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A genetic algorithm for solving multi-constrained function optimization problems based on KS function
Proceedings article published in 2007 by
Jianhua H. Xiao,
Jianhua Xiao,
Jin Xu,
Jin Xu,
Zehui H. Shao,
Congfeng F. Jiang,
Congfeng Jiang,
Linqiang Q. Pan 
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Abstract
In this paper, a new genetic algorithm for solving multi-constrained optimization problems based on KS function is proposed. Firstly, utilizing the agglomeration features of KS function, all constraints of optimization problems are agglomerated to only one constraint. Then, we use genetic algorithm to solve the optimization problem after the compression of constraints. Finally, the simulation results on benchmark functions show the efficiency of our algorithm.