Population Fitness Probability for Effectively Terminating Evolution Operations of a Genetic Algorithm

Heng-Chou CHEN
Oscal T.-C. CHEN

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E89-D    No.12    pp.3012-3014
Publication Date: 2006/12/01
Online ISSN: 1745-1361
DOI: 10.1093/ietisy/e89-d.12.3012
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Biocybernetics, Neurocomputing
Keyword: 
genetic algorithm,  termination strategy,  population fitness,  Euclidean distance,  

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Summary: 
The probability associated with population fitness in a Genetic Algorithm (GA) is studied using the concept of average Euclidean distance. Based on the probability derived from population fitness, the GA can effectively terminate its evolution operations to mitigate the total computational load. Simulation results verify the feasibility of the derived probability used for the GA's termination strategy.

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