Integrating the simplified interpolation into the genetic algorithm for constrained optimization problems

Authors:
Hong Li;Yong-Chang Jiao;Yuping Wang
Affiliations:
National Laboratory of Antennas and Microwave Technology, Xidian University, Xi’an, Shaanxi, China;National Laboratory of Antennas and Microwave Technology, Xidian University, Xi’an, Shaanxi, China;School of Computer Science and Engineering, Xidian University, Xi’an, Shaanxi, China
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Year:
2005

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Abstract

In this paper, a hybrid genetic algorithm for solving constrained optimization problems is addressed. First, a real-coded genetic algorithm is presented. The simplified quadratic interpolation method is then integrated into the genetic algorithm to improve its local search ability and the accuracy of the minimum function value. Simulation results on 13 benchmark problems show that the proposed hybrid algorithm is able to avoid the premature convergence and find much better solutions with high speed compared to other existing algorithms.