doi: 10.4304/jsw.9.2.389-397
Improved Real Coded Genetic Algorithm and Its Simulation
- College of Mechanical Engineering, University of Shanghai for Science and Technology, 200093, Shanghai
Abstract
Aiming at improving search efficiencylimitations of canonical real coded genetic algorithm, thispaper improves three aspects for the canonical real codedgenetic algorithm, that are initial population generating,overall process of algorithm and the mutation operator,then puts forward an improved real coded genetic algorithm.This improved algorithm combines the series operation andparallel operation of the three basic operators (selection,crossover and mutation), presents new methods of uniformgenerating initial population and progressive variation, theformer contributes to generating good initial population, thelatter processes more active mutation operation on the basicof controlling the average fitness in a certain range, whichcan obtain advantage individual and reduce evolution time.Using typical standard test functions for two algorithms’simulation research, the simulation results show that, theproposed real coded genetic algorithm is superior to thecanonical real coded genetic algorithm on the aspects ofsearch speed and search accuracy, improving searchefficiency of canonical real coded genetic algorithm greatly.
Keywords
- real coded genetic algorithm
- improve
- s
How to Cite
Jianmin Zhu, Donger Zhou, Fucai Li, and Tingting Fu, "Improved Real Coded Genetic Algorithm and Its Simulation," Journal of Software, vol. 9, no. 2, pp. 389-397, 2014. https://doi.org/ 10.4304/jsw.9.2.389-397
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).