Analysis of Convergence Rate for Improved Generalized Ant Colony Optimization Algorithm

Dai Yuan Zhang; Hua Zhao

doi:10.4028/www.scientific.net/AMR.989-994.1728

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 989-994Analysis of Convergence Rate for Improved...

Analysis of Convergence Rate for Improved Generalized Ant Colony Optimization Algorithm

Abstract:

Although theoretical result of convergence for improved generalized ant colony optimization (IGACO) algorithm has been proved in recent years, the convergence speed is also an open and difficult problem. This article, based on the Markov model, tries to explore the analysis of convergence speed for IGACO algorithm. Some experiments have been studied to compare the convergence speed between ant colony optimization (ACO) algorithm and IGACO algorithm.

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Periodical:

Advanced Materials Research (Volumes 989-994)

Pages:

1728-1731

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.989-994.1728

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Online since:

July 2014

Authors:

Dai Yuan Zhang*, Hua Zhao

Keywords:

Convergence Speed, Expected Convergence Time, Markov Chain

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* - Corresponding Author

References

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