Chaotic Genetic Algorithm for Mixed Integer Programming Problem

Ya Ming Wang; Z. Zhang; Jun Bao Zheng; L.L. Tong

doi:10.4028/www.scientific.net/AMM.651-653.2273

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 651-653Chaotic Genetic Algorithm for Mixed Integer...

Chaotic Genetic Algorithm for Mixed Integer Programming Problem

Abstract:

This paper proposed a chaotic genetic algorithm (CGA) to solve the mixed integer programming problem (MIPP). The basic idea of this algorithm is to overcome the deficiency of genetic algorithm (GA) by introducing chaotic disturbances into the genetic search process. Two typical MIPP problems are used to evaluate the performances of the proposed CGA. Experimental results show that performances of the algorithm have been improved by the chaotic disturbances, such as, search ability, precision, stability and convergence speed or calculation efficiency. The proposed CGA algorithm is suitable for solving complicated practical MIPP problem.

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Periodical:

Applied Mechanics and Materials (Volumes 651-653)

Pages:

2273-2277

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.651-653.2273

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Online since:

September 2014

Authors:

Ya Ming Wang*, Z. Zhang, Jun Bao Zheng, L.L. Tong

Keywords:

Chaotic, Chaotic Genetic Algorithm, Mixed Integer Programming Problem

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* - Corresponding Author

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