Real-Coded Genetic Algorithm for Constrained Optimization Problem

Author

Zhang, Guo-li ; Li, Geng-Yin ; Ma, Jian-Wei

Author_Institution

North China Electr. Power Univ., Baoding

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

4243

Lastpage

4247

Abstract

This paper proposes a new constraint direct disposal method (GA-CDD), which need not penalty factor, is a universal method dealing with constraint. In order to increase convergence velocity and get global optimal solution, a skill of reserving some unfeasible solution was introduced. The experiment study has shown that the method proposed in this paper is very effective, especially the optimal solution locating in the border of the feasible region

Keywords

genetic algorithms; constrained optimization problem; constraint direct disposal method; convergence velocity; real-coded genetic algorithm; Computational modeling; Constraint optimization; Cybernetics; Evolutionary computation; Genetic algorithms; Genetic mutations; Machine learning; Minimization methods; Optimization methods; Robustness; Simulated annealing; Stochastic processes; Constrained optimization problem; constraint direct disposal; genetic algorithm; real-coded; reserving unfeasible solution;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.259005

Filename

4028817

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2899780