Optimal Production LineLayout Model Based on Integer Programming

Abstract:

To control the cost and optimize the resource utilization of enterprises, production layout problem draws recently more and more attention by industries; however, a study on this problem indicates there is a lack of research on production line design, which is a major issue in the layout problem. Traditional methodology mainly depends on the designer’s experience and calls for theory analysis and quantitative study. This paper concerns the development of a multi-stage integer programming model to describe the production line layout problem, and employs a heuristic and ant-colony algorithm to solve the problem. A practical example illustrates the effectiveness of the model.

• Periodical: Advanced Materials Research (Volumes 690-693)
• Pages: 2896-2900
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.690-693.2896
• Online since: May 2013
• Authors: Yong Zhao, Xiao Yong Pan, Chun Chuan Li, Guo Hong Yao, Jiang Wu, Xin Fu, Dong Lai, Dong Li, Quan Wei Zhang
• Keywords: Ant Colony Algorithm (ACA), Flow Line, Integer Programming, Production Layout

References

[1] S. Benjaafar, S.S. Heragu, and S.A. Irani. Next generation factory layouts: research challenges and recent progress. Interfaces, 32(6):58–76, 2002.

DOI: 10.1287/inte.32.6.58.6473

[2] G.C. Hadjinicola. Manufacturing costs in serial production systems with rework. Journal of the Operational Research Society, 61(2):342–351, 2009.

DOI: 10.1057/jors.2008.186

[3] M. Haouari and L. Hidri.On the hybrid flow shop scheduling problem. International Journal of Production Economics, 113(1):495–497, 2008.

DOI: 10.1016/j.ijpe.2007.10.007

[4] L.Hidri and M.Haouari. Bounding strategies for the hybrid flow shop scheduling problem. Applied Mathematics and Computation, 217(21):8248–8263, 2011.

DOI: 10.1016/j.amc.2011.02.108

[5] S.M. Johnson. Optimal two- and three-stage production schedules with setup times included. Naval Research Logistics Quarterly, 1(1):61–68, 1954.

DOI: 10.1002/nav.3800010110

[6] M. Kuroda and T. Tomita. Robust design of a cellular-line production system with unreliable facilities. Computers & Industrial Engineering, 48(3):537–551, 2005.

DOI: 10.1016/j.cie.2004.03.004

[7] J. Li and S.M. Meerkov. Production systems engineering. 2008.

[8] E.J. Muth. Stochastic processes and their network representations associated with a production line queuing model. European Journal of Operational Research, 15(1):63–83, 1984.

DOI: 10.1016/0377-2217(84)90049-3

[9] C.T. Papadopoulos, M.E.J. O'Kelly, M.J. Vidalis, and D. Spinellis. Analysis and design of discrete part production lines. Springer, 2009.

DOI: 10.1007/978-0-387-89494-2_2

[10] D. Quadt and H. Kuhn. A taxonomy of flexible flow line scheduling procedures. European Journal of Operational Research, 178(3):686–698, 2007.

DOI: 10.1016/j.ejor.2006.01.042

[11] H. Basali, B. Hussin, S.A. Asmai, N.K. Ibrahim, and A.S. Shibghatullah. The integration of simple Markov model in solving single line. Information Technology in Asia, 2011.

DOI: 10.1109/cita.2011.5998611

[12] I. Ribas, R. Leisten, and J.M. Framinan. Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective. Computers &Operations Research, 37(8):1439–1454, 2010.

DOI: 10.1016/j.cor.2009.11.001

[13] D. Spinellis, C. Papadopoulos, and J.M. Smith. Large production line optimization using simulated annealing. International Journal of Production Research, 38(3):509–541, 2000.

DOI: 10.1080/002075400189284

[14] D.D. Spinellis and C.T. Papadopoulos.A simulated annealing approach for buffer allocation inreliable production lines. Annals of Operations Research, 93(1):373–384, 2000.

[15] T. Urlings, R. Ruiz, and T. Stutzle. Shifting representation search for hybrid flexible flow line problems. European Journal of Operational Research, 207(2):1086–1095, 2010.

DOI: 10.1016/j.ejor.2010.05.041