Title :
Optimizing the performance of genetic algorithms for finding the optimal value of a given function
Author :
Huang, Yiadong ; Chan, Shu-Park
Author_Institution :
Circuits & Syst. Res. Lab., Santa Clara Univ., CA, USA
Abstract :
An approach for optimizing the performance of genetic algorithms (GAs) which is derived from the exhaustive examinations of some parameters of GAs is provided. The problems of finding the optimal values of some numerical functions are used as examples to illustrate the performance of GAs. GAs are shown to be effective for solving these problems. In addition, various parameters of the optimization algorithm are critically selected for efficiency. Experimental results suggest that while it is possible to optimize GA control parameters, excellent performances can be obtained with an appropriately selected range of GA control parameter settings, based mainly on the experience of the users
Keywords :
genetic algorithms; iterative methods; control parameter settings; efficiency; genetic algorithms; numerical functions; optimal value; optimization; Circuits and systems; Genetic algorithms; Genetic engineering; Genetic mutations; Iterative algorithms; Laboratories; Optimal control; Testing;
Conference_Titel :
Circuits and Systems, 1991., Proceedings of the 34th Midwest Symposium on
Conference_Location :
Monterey, CA
Print_ISBN :
0-7803-0620-1
DOI :
10.1109/MWSCAS.1991.252087