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Artificial Bee Colony Constrained Optimization Algorithm With Hybrid Discrete Variables And Its Application

Zhonghua Yan ()
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Zhonghua Yan: Changde Textile Machinery Co. Ltd, Hunan, Changde, 415001, P.R.China

Acta Electronica Malaysia (AEM), 2018, vol. 2, issue 1, 18-20

Abstract: On the basis of Artificial Bee Colony Optimization Algorithm, a new algorithm by introducing constructing dynamic penalty function was presented. Based on Matlab software, the program ABCOA1.0 with hybrid discrete variables for the proposed algorithm was developed. The results show that this algorithm has no special requirements on the characteristics of optimal designing problems, which has a fairly good universal adaptability and a reliable operation of program with a strong ability of overall convergence. After optimization, the weight can be reduced, the cost can be lowered, and the product quality can be raised.

Keywords: Artificial Bee Colony Optimization Algorithm(ABCOA); Constrained optimization; hybrid discrete variable; Dynamic Penalty Function; Evolutionary Algorithm. (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:zib:zbnaem:v:2:y:2018:i:1:p:18-20

DOI: 10.26480/aem.01.2018.18.20

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