Population fitness probability for effectively terminating the evolution operations of a genetic algorithm

Author

Heng-Chou Chen ; Chen, Oscal T C

Author_Institution

Dept. of Electr. Eng., Nat. Chung Cheng Univ., Chia-Yi

fYear

2006

fDate

21-24 May 2006

Lastpage

3769

Abstract

A probability associated with the population fitness is used in a genetic algorithm (GA) to terminate the evolution. The theoretically probabilistic derivation of population fitness reveals that the probability is inversely proportional to the individual variation and directly proportional to the evolving error between the average individual and the global optimum of the objective function. Based on the probability, GA switches its operation mode between the genetic operation and the population regeneration. A modified genetic algorithm with a termination strategy is proposed to find the global optima of five objective functions and thus validate the proposed probability of population fitness

Keywords

genetic algorithms; probability; evolution operation termination; genetic algorithm; genetic operation; objective function; population fitness; population regeneration; probabilistic derivation; probability; Convergence; Genetic algorithms; Genetic mutations; Laboratories; Parameter estimation; Stability; Switches; Upper bound;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2006. ISCAS 2006. Proceedings. 2006 IEEE International Symposium on

Conference_Location

Island of Kos

Print_ISBN

0-7803-9389-9

Type

conf

DOI

10.1109/ISCAS.2006.1693447

Filename

1693447