An Optimization Algorithm Based on Job Shop Scheduling with Fuzzy Goals

Qing Ling Dai; Sheng Bo Zhang

doi:10.4028/www.scientific.net/AMR.912-914.1156

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 912-914An Optimization Algorithm Based on Job Shop...

An Optimization Algorithm Based on Job Shop Scheduling with Fuzzy Goals

Abstract:

The mathematical model was built up for the job shop scheduling problem at first. With following the fuzzy submit time of customer requirement an improved genetic algorithm of fuzzy objective scheduling method was put forward which took the minimum production cost as the objective function. It solved the faults of the chromosomes in genetic algorithm is difficult to accurately express the complex optimization problem solution and determined the more suitable multilayer encoding and operating mode. The simulation results show that this algorithm can be applied to fuzzy object shop scheduling optimization problem, which can ensure the machine's load balance and meet the requirements of the customer delivery date.

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Periodical:

Advanced Materials Research (Volumes 912-914)

Pages:

1156-1159

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.912-914.1156

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Online since:

April 2014

Authors:

Qing Ling Dai*, Sheng Bo Zhang

Keywords:

Fuzzy Goals, Genetic Algorithm (GA), Job Shop Scheduling, Multi-Layer Encoding

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* - Corresponding Author

References

[1] Zhang Chang-shui, Yan Ping-fan. A method to solve job-shop schedule problems by neural network[J] Automatica Sinica, 2005, 21(6)：706—712.

Google Scholar

[2] Fan Lu-qiao, Chang Hui—you, Zhu Xu-dong. Improved job-shop scheduling algorithm & its implementation[J]. Computer Integrated Manufacturing Systems, 2011, 11(5): 673—677.

Google Scholar

[3] L Wang and D Zheng. An effective hybrid optimization strategy for job—shop scheduling problems[J]. Computers & Operations Research, 2008, 28: 585—596.

DOI: 10.1016/s0305-0548(99)00137-9

Google Scholar

[4] H R Lourern_co. Local optimization and the job—shop scheduling problem[J] European Journal of Operational Research, 2012, 83：347—364.

Google Scholar

[5] Pan quan-ke, Zhu jian-ying. Study of job shop dynamic scheduling[J] Journal of Nanjing university of aeronautics and astronautics. 2010. 37(2): 262～268.

Google Scholar

[6] He li, Liu yong-xian, Xie hua-long, Liu xiao-tian. Shop scheduling and optimization based on particle swarm optimization algorithm[J]. Journal of Northeast University(Natural Science). Apr. 2012, Vol. 29. No. 4 . 124-127.

Google Scholar