Application of DNA Genetic Algorithm in Manufacturing System Scheduling Optimization

Shu Zhi Nie; Bang Yan Ye

doi:10.4028/www.scientific.net/AMR.323.34

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 323Application of DNA Genetic Algorithm in...

Application of DNA Genetic Algorithm in Manufacturing System Scheduling Optimization

Abstract:

In this paper, built mathematical model on Flow Shop scheduling, put forward a RNA genetic algorithm based on DNA computing to solve the Flow Shop scheduling problems. Adopt RNA four digit system encoding method based on DNA computing and RNA computing operator in genetic algorithm. It resolved the encoding scheme and convergence problem which exists in the conventional genetic algorithm. Under some constraint conditions, this genetic algorithm got simulated. Simulation results showed that this algorithm has a better optimum searching and seeking abilities, made the scheduling results comparatively reasonable and expanded the application of DNA computing.

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Periodical:

Advanced Materials Research (Volume 323)

Pages:

34-39

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.323.34

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Online since:

August 2011

Authors:

Shu Zhi Nie, Bang Yan Ye

Keywords:

DNA Computing, Flow-Shop Scheduling Introduction, Hybrid Genetic Algorithm

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References

[1] Maccarthy B. L, Liu J.Addressing the gap in scheduling research: a review of optimization and heuristic methods in production scheduling. International Journal of Production Research, 31(1) ,(1993),pp.59-79.

DOI: 10.1080/00207549308956713

Google Scholar

[2] Garretti M, Taisch M. Neural networks in production planning and control. Production Planning and Control,10, (1999),pp.324-339.

DOI: 10.1080/095372899233082

Google Scholar

[3] Ding yong-sheng. Computing intelligent—theory, technology and application(Science Press,China 2004).

Google Scholar

[4] Xuan guang-nan, Cheng run-wei. Genetic Algorithms and Engineering Design.(Science Press,China 2000).

Google Scholar

[5] Zhang lian-zhen, Xu jin. The Research of DNA Computing Model by Operating on Plasmids. ComputerEngineering and Applications, 40(4),(2004),pp.51-52.

Google Scholar

[6] Zhang hai-gang, Gu xing-sheng. Vehicle Scheduling Problem Based on DNA Evolutionary Algorithm.Journal of East China University of Science and Technology(Natural Science Edition), 32(12),(2006),pp.1463-1467.

Google Scholar

[7] Niu qun, Gu xing-sheng. Flow Shop Scheduling Problems Based on DNA Evolutionary Algorithms. Journal of Shanghai University(Natural Science Edition), 10 (B10),(2004),pp.88-92.

Google Scholar

[8] Liu min,Wu cheng. Intelligent Optimization ofthe manufacturing process scheduling algorithm and its application(National Defense Industry Press,China 2008).

Google Scholar

[9] Wang wan-liang, Wu qi-di. Intelligent production scheduling algorithm and its application(Science Press,China 2007).

Google Scholar

[10] Ding yongsheng, Shao shihuang, Ren lihong. DNA Computing and Soft Computing(Science Press,China 2002).

Google Scholar

[11] Tao ji-li. Application and research of genetic algorithms based-on DNA computing(Doctoral dissertation of Zhejiang University,China 2007).

Google Scholar

[12] Neuhauser C. and S. M. Krone. The Genealogy of Samples in Models with Selection. Genetics. 145(2),(1997),pp.519-534

DOI: 10.1093/genetics/145.2.519

Google Scholar