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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1382314
