An Improved Estimation of Distribution Algorithms Based on the Minimal Free Energy

Fa Hong Yu; Mei Jia Chen; Wei Zhi Liao

doi:10.4028/www.scientific.net/AMM.373-375.1093

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 373-375An Improved Estimation of Distribution Algorithms...

An Improved Estimation of Distribution Algorithms Based on the Minimal Free Energy

Abstract:

To systematically harmonize the conflict between selective pressure and population diversity in estimation of distribution algorithms, an improved estimation of distribution algorithms based on the minimal free energy (IEDA) is proposed in this paper. IEDA conforms to the principle of minimal free energy in simulating the competitive mechanism between energy and entropy in annealing process, in which population diversity is measured by similarity entropy and the minimum free energy is simulated with an efficient and effective competition by free energy component. Through solving some typical numerical optimization problems, satisfactory results were achieved, which showed that IEDA was a preferable algorithm to avoid the premature convergence effectively and reduce the cost in search to some extent.

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Periodical:

Applied Mechanics and Materials (Volumes 373-375)

Pages:

1093-1097

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.373-375.1093

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Online since:

August 2013

Authors:

Fa Hong Yu, Mei Jia Chen, Wei Zhi Liao

Keywords:

Estimation of Distribution Algorithms, Minimum Free Energy, Similarity Entropy

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References

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