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Author Shengjing Mu ♦ Hongye Su ♦ Weijie Mao ♦ Zhenyi Chen ♦ Jian Chu
Sponsorship IEEE Control Syst. Soc
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2002
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Other branches of engineering
Subject Keyword Genetic algorithms ♦ Constraint optimization ♦ Genetic mutations ♦ Process control ♦ Nonlinear distortion ♦ Stochastic processes
Abstract A genetic algorithm to handle the constrained optimization problem without penalty function term is proposed. The infeasibility degree of a solution (IFD) is defined as the sum of the square value of all the constraints violation to identify the constraints violation of the solutions quantitative. At the end of general GAs operation, an infeasibility degree selection of the current population is designed by checking whether the IFD of a solution is less than or equal to a threshold or not to decide the candidate solution is accepted or rejected. The initial results of solving two typical constrained optimization problems show the promising performance of the proposed method.
Description Author affiliation: Inst. of Adv. Process Control, Zhejiang Univ., Hangzhou, China (Shengjing Mu; Hongye Su; Weijie Mao; Zhenyi Chen; Jian Chu)
ISBN 0780375165
ISSN 01912216
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2002-12-10
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 158.58 kB
Page Count 2
Starting Page 739
Ending Page 740


Source: IEEE Xplore Digital Library