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Entropy-Enhanced Genetic Algorithm with Tabu Search for Job Shop Scheduling Problems

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Abstract:

By combining Genetic algorithm with Tabu search algorithm and adjusting crossover rate and mutation rate based on information entropy, a hybrid genetic algorithm was proposed for larger-scale job shop scheduling problems, and the benchmark instances were used to verify the algorithm with simulation. Simulation results show that the proposed algorithm can solve larger-scale job shop scheduling problems, and it has obvious advantages over traditional scheduling algorithms.

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Periodical:

Advanced Materials Research (Volume 590)

Pages:

557-562

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.590.557

Citation:

Cite this paper

Online since:

November 2012

Authors:

Ying Jie Huang, Xi Fan Yao, Dong Yuan Ge, Yong Xiang Li

Keywords:

Genetic Algorithm (GA), Information Entropy, Job Shop Scheduling, Tabu Search Algorithm

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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References

[1] Jia H.Z. A modified genetic algorithm for distributed scheduling problems, Journal of Intelligent Manufacturing, Vol. 351-362(2003), p.14.

Google Scholar

[2] WU Dawei, LU Taodong, LIU Xiaobing, et al. Parallel simulated annealing algorithm for solving job-shop scheduling problem. Computer Integrated Manufacturing Systems, 2005, Vol. 103-109(2005), p.6.

Google Scholar

[3] GU Feng, CHEN Huaping, LU Bingyuan, et al. Particle swarm optimization for flexible job shop scheduling. Systems Engineering, Vol. 20-23(2005), p.23.

Google Scholar

[4] LIANG Di, XIE Liyang, SUI Tianzhong, Tao Ze. Scheduling optimization based on hybrid genetic -Tabu search algorithm for dual-resource constrained job shop. Journal of Northeastern University. Vol. 895-898(2006), p.27.

DOI: 10.1109/csqrwc.2011.6037292

Google Scholar

[5] YAN Liang, YAO Xi-fan. Applications of one improved genetic algorithm in solving the job-shop scheduling. Machine Tool & Hydraulics, Vol. 11-14(2008), p.36.

Google Scholar

[6] LIU Min, HAO Jing-hua, WU Cheng. A new genetic algorithm scheduling problems constraints and its for parallel machine with procedure. Applications Chinese Journal of Electronics, Vol. 463-465(2006), p.15.

Google Scholar

[7] YANG Bo. the application research of Tabu search algorithm in the cold chain distribution network. Shanghai: Shanghai Maritime University, (2005).

Google Scholar

[8] RAO Yun-qing, EFSTATHIOU Janet. Entropy-based measurement of manufacturing system complexity and its application in scheduling. Chinese Journal of Mechanical Engineering, Vol. 8-13(2006), p.42.

DOI: 10.3901/jme.2006.07.008

Google Scholar

[9] Piplani R, Wetjens D. Evaluation of entropy-based dispatching in flexible manufacturing system. European Journal of Operational Research, Vol. 317-331(2007), p.176.

DOI: 10.1016/j.ejor.2005.06.066

Google Scholar

[10] LIU Lin. Research on Optimization Problem of Manufacturing Process in a Discrete Manufacturing Industry. Hefei: Hefei University of Technology, (2009).

Google Scholar