DocumentCode
424287
Title
An improved genetic algorithm for nonlinear programming problems with inequality constraints
Author
Qian, Wei-Yi ; Wang, Ying ; Chen, De-gang
Author_Institution
Dept. of Math., Bohai Univ., Jinzhou, China
Volume
2
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
904
Abstract
An improved genetic algorithm is proposed for nonlinear programming problems with inequality constraints. In this algorithm, mutation operator is given by mimicking the physics of electromagnetism, and fitness function is given by evaluation function and objective function. To evaluate the efficiency of the algorithm, the algorithm is applied to two test problems, and our results are compared with other methods.
Keywords
electromagnetism; genetic algorithms; nonlinear programming; electromagnetism; evaluation function; genetic algorithm; inequality constraints; mutation operator; nonlinear programming problem; objective function; Chemistry; Constraint optimization; Electromagnetic forces; Genetic algorithms; Genetic mutations; Mathematical programming; Mathematics; Optimization methods; Physics; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1382314
Filename
1382314
Link To Document