Constrained Optimization Solution Based on an Improved Genetic Algorithm

Chun Yan Li; Guang Hui Zeng

doi:10.4028/www.scientific.net/AMM.190-191.334

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 190-191Constrained Optimization Solution Based on an...

Constrained Optimization Solution Based on an Improved Genetic Algorithm

Abstract:

A hybrid adaptive genetic algorithm is proposed for solving constrained optimization problems. The algorithm combines adaptive penalty method and smoothing technique in order to get no parameter tuning and easily escaping from the local optimal solutions. Meanwhile, local line search technique is introduced and a new crossover operator is designed for getting much faster convergence. The performance of the algorithm is tested on thirteen benchmark functions and the results indicate that the proposed algorithm is robust and effective.

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Periodical:

Applied Mechanics and Materials (Volumes 190-191)

Pages:

334-337

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.190-191.334

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Online since:

July 2012

Authors:

Chun Yan Li, Guang Hui Zeng

Keywords:

Constrained Optimization, Genetic Algorithm (GA), Local Line Search, Penalty Function

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References

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