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Information Technology Journal

Year: 2013 | Volume: 12 | Issue: 23 | Page No.: 7616-7620
DOI: 10.3923/itj.2013.7616.7620
Test-sheet Composition Using Cellular Genetic Algorithm with an Improved Evolutionary Rule
Ankun Huang, Dongmei Li and Kuan Lu

Abstract: For an intelligent test-sheet composition system, compared with the traditional test-sheet composition using genetic algorithm, cellular genetic algorithm can significantly improve the convergence velocity and further improve the convergence in the process. However, in the process of mutating, both the diversity index of cellular population and the possibility of escaping from local-best will be decreased. Therefore, this study proposes a cellular genetic algorithm with an improved evolutionary rule applied in the process of test-sheet composition. Experimental results show that the convergence velocity is improved and the speed of decreasing diversity index of cellular population is delayed.

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How to cite this article
Ankun Huang, Dongmei Li and Kuan Lu, 2013. Test-sheet Composition Using Cellular Genetic Algorithm with an Improved Evolutionary Rule. Information Technology Journal, 12: 7616-7620.

Keywords: Test-sheet composition, multi-objective strategy, cellular genetic algorithm and evolution rule

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