Comparative Study of Well Known Sequencing Methodologies and Differential Evolution: A Case Study of Thailand Garment Industries

Abstract:

The objective of this research is to study the problem and efficiency improvement of the clean room garment factory. The methods of production schedule were performed by heuristic technique of well-known scheduling methodologies including Shortest Processing Time, , Earliest Due Date, First Come First Serve method and Differential Evolution Method (DE). All methods can help to reduce the costs of delay shipment and time loss in various case studies. They were applied to the production order in 2 months after flooding problems in Thailand .The demand has a lot of quantities over production capacity. The results showed that the rules of Earliest Due Date method (EDD) is a powerful methodology for increasing production efficiency and minimizing make span. Whereas, the First Come First Serve (FCFS) method is the best method for finding a minimum value of total late job. Finally, Differential Evolution Method (DE) is the best method for finding a minimize value of average tardiness job.

• Periodical: Applied Mechanics and Materials (Volumes 457-458)
• Pages: 1427-1431
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.457-458.1427
• Online since: October 2013
• Authors: Lakkana Ruekkasaem*, Isaree Srikun, Pasura Aungkulanon
• Keywords: Differential Evolution Method, Efficiency Improvement, Processing Time, Scheduling Methodologies

References

[1] B. Kenneth, Scheduling Full-Time and Part-Time Staff to Meet Cyclic Requirements, Operational Research Quarterly. 25 No. 1 (1974) 65 – 71.

DOI: 10.2307/3007776

[2] R. L. Becerra, C. A. Coello ., A Cultural Algorithm with Differential Evolution to solve constrained optimization problems, Lecture Notes in Computer Science, 3315, (2004)881-890.

DOI: 10.1007/978-3-540-30498-2_88

[3] Storn, R. and Price, K. System Design by Constraint Adaptation and Deferential Evolution Journal of Global Optimization 11 (1997)341–359.

[4] T. Kaewpaitoon and J. Teeravaraprug, Comparison of Well-known Scheduling Methodologies: A Case Study, Proceedings of the IAENG 2010 March 17 – 19 2010, Hong Kong.

[5] C. Zhang, Z. He and Y. Peng Ruan, Production Planning Optimization in F Company: A Scheduling Theory Case Study , Advanced Materials Research, 655-657, (2013) 1646-1649.

DOI: 10.4028/www.scientific.net/amr.655-657.1646

[6] G.C. Luha and C.H. Chuehb, A multi-modal immune algorithm for the job-shop scheduling problem: submitted to Information Sciences. 179 (2009) 1516–1532.

DOI: 10.1016/j.ins.2008.11.029

[7] I. L. Grigorescu and G. B., Organization of Production Processes through the Multi-Service Method by Performing some Identical Operations of the same Duration and Structure, Applied Mechanics and Materials. 371 (2013) 787-791.

DOI: 10.4028/www.scientific.net/amm.371.787

[8] B. Chiliban, M. Chiliban, M. Inţă, Advanced Product Quality Planning Reference Model in Automotive Industry, Applied Mechanics and Materials. 371, (2013) 802-806.

DOI: 10.4028/www.scientific.net/amm.371.802