TY - JOUR
T1 - The application of hybrid fish swarm algorithm for constrained nonlinear optimization
AU - Liu, Zhijun
AU - Gao, Yakui
AU - Zhang, Weiguo
AU - Hou, Mei
PY - 2014/9/30
Y1 - 2014/9/30
N2 - A hybrid algorithm which combines the augmented Lagrangian multiplier method with the fish swarm algorithm is presented to solve the problem of constrained nonlinear optimization. The method approximately solves the optimal solution of the augmented Lagrangian function with the fish swarm algorithm, and the solution is applied to update the Lagrangian multipliers and penalty parameters. Stochastic convergence of the artificial fish swarm is analyzed. Compared with an adaptive penalty method for genetic algorithms, simulation results verify the superiority and validity of the proposed hybrid algorithm.
AB - A hybrid algorithm which combines the augmented Lagrangian multiplier method with the fish swarm algorithm is presented to solve the problem of constrained nonlinear optimization. The method approximately solves the optimal solution of the augmented Lagrangian function with the fish swarm algorithm, and the solution is applied to update the Lagrangian multipliers and penalty parameters. Stochastic convergence of the artificial fish swarm is analyzed. Compared with an adaptive penalty method for genetic algorithms, simulation results verify the superiority and validity of the proposed hybrid algorithm.
KW - Augmented Lagrangian function
KW - Augmented Lagrangian multiplier method
KW - Fish swarm algorithm
KW - Stochastic convergence
UR - http://www.scopus.com/inward/record.url?scp=84908363455&partnerID=8YFLogxK
M3 - 文章
AN - SCOPUS:84908363455
SN - 0367-6234
VL - 46
SP - 55
EP - 60
JO - Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology
JF - Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology
IS - 9
ER -