Title :
A genetic algorithm for solving multi-constrained function optimization problems based on KS function
Author :
Xiao, Jianhua ; Xu, Jin ; Shao, Zehui ; Jiang, Congfeng ; Pan, Linqiang
Author_Institution :
Huazhong Univ. of Sci. & Technol., Wuhan
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.
Keywords :
genetic algorithms; KS function; agglomeration features; genetic algorithm; multiconstrained function optimization; Constraint optimization; Genetic algorithms; Industrial engineering; Mathematical model; Mathematics; Operations research; Optimization methods; Quadratic programming; Robustness; Testing;
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
Electronic_ISBN :
978-1-4244-1340-9
DOI :
10.1109/CEC.2007.4425060
