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Growing Science » International Journal of Industrial Engineering Computations » A new stochastic mixed integer programming to design integrated cellular manufacturing system: A supply chain framework

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International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 2 Issue 3 pp. 563-574 , 2011

A new stochastic mixed integer programming to design integrated cellular manufacturing system: A supply chain framework Pages 563-574 Right click to download the paper Download PDF

Authors: Vahid Reza Ghezavati

DOI: 10.5267/j.ijiec.2011.03.003

Keywords: Cellular manufacturing, Stochastic MIP, Supplier network, Uncertain processing time

Abstract: This research defines a new application of mathematical modeling to design a cellular manufacturing system integrated with group scheduling and layout aspects in an uncertain decision space under a supply chain characteristics. The aim is to present a mixed integer programming (MIP) which optimizes cell formation, scheduling and layout decisions, concurrently where the suppliers are required to operate exceptional products. For this purpose, the time in which parts need to be operated on machines and also products & apos; demand are uncertain and explained by set of scenarios. This model tries to optimize expected holding cost and the costs regarded to the suppliers network in a supply chain in order to outsource exceptional operations. Scheduling decisions in a cellular manufacturing framework is treated as group scheduling problem, which assumes that all parts in a part group are operated in the same cell and no inter-cellular transfer is required. An efficient hybrid method made of genetic algorithm (GA) and simulated annealing (SA) will be proposed to solve such a complex problem under an optimization rule as a sub-ordinate section. This integrative combination algorithm is compared with global solutions and also, a benchmark heuristic algorithm introduced in the literature. Finally, performance of the algorithm will be verified through some test problems.

How to cite this paper
Ghezavati, V. (2011). A new stochastic mixed integer programming to design integrated cellular manufacturing system: A supply chain framework.International Journal of Industrial Engineering Computations , 2(3), 563-574.

Refrences
Andres, C., Lozano, S., & Adenso-Diaz, B. (2007). Disassembly sequence planning in a Disassembly cell, Robotics and Computer-Integrated Manufacturing, 23(6), 690-695.

Apaioannou, G. P, & Wilson, J. M. (2008). Fuzzy extensions to integer programming of cell formation problem in machine scheduling. Annals of Operations Research, 1-19.

Badiru, A. B. (1992). Computational survey of univariate and multivariate learning curve models, IEEE Transactions on Engineering Management, 39, 176-188.

Balakrishnan, J., & Cheng C. H., (2005). Dynamic C.M. under multi-period planning horizon, Journal of Manufacturing Technology Management. 16(5), 516-530.

Balakrishnan, J., & Cheng, C.H., (2007). Multi-period planning and uncertainty issues in C.M.: a review and future directions, European Journal of Operational Research, 177(1), 281-309.

Ghosh, T., Sengupta, S., Chattopadhyay, M, & Dan, P. K. (2011). Meta-heuristics in cellular manufacturing: A state-of-the-art review, International Journal of Industrial Engineering Computations, 2, 87-122.

Ghezavati, V. R., & Saidi-Mehrabd, M. (2010). Designing integrated cellular manufacturing systems with scheduling considering stochastic processing time, The International Journal of Advanced Manufacturing Technology, 48 (5-8), 701-717.

Ghezavati, V. R., Jabal-Ameli, M. S., & Makui, A. (2009). A new heuristic method for distribution networks considering service level constraint and coverage radius, Expert Systems with Applications, 36(3), 5620-5629.

Gupta, S.M., & Kavusturucu, A. (1998). Modeling of finite buffer cellular manufacturing systems with unreliable machines. International Journal of Industrial Engineering: Theory Applications and Practice, 5(4), 265-277.

Hurley, S.F., & Whybark, C.D., (1999). Inventory and capacity trade-off in a manufacturing cell. International Journal of Production Economics Volume, 59(1), 203-212.

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

Lockwood, W. T., Mahmoodi, F., Ruben, R., Mosier, A., & Charles T. (2000). Scheduling unbalanced cellular manufacturing systems with lot splitting. International Journal of Production Research, 38(4). 951 – 965.

Mahdavi, I., Javadi, B., Fallah-Alipour, K., & Slomp, J. (2007). Designing a new mathematical model for cellular manufacturing system based on cell utilization, Applied Mathematics and Computation, 190, 662–670.

Mobasheri, F., Orren, L. H., & Sioshansi, F. P. (1989). Scenario planning at southern California Edison. INTERFACES, 19(5), 31-44.

Mulvey, J. M. (1996). Generating scenarios for the Towers Perrin investment system. INTERFACES, 26 (2), 1-15.

Shanker, R., & Vrat, P., (1998). Post design modeling for CMS with cost uncertainty, International Journal of Production Economics, 55(1), 97-109.

Shanker, R., & Vrat, P., (1999). Some design issues in C.M. using the fuzzy programming approach. International Journal of Production Research, 37(11), 2545-2563.

Snyder, L.V. (2006). Facility location under uncertainty: a review, IIE Transactions, 38, 537–554.

Solimanpur, M., Vrat. P., & Shankar, R. (2004). A heuristic to optimize makespan of cell scheduling problem. International Journal of Production Economics, 88, 231–241.

Szwarc, D., Rajamani, D., Bector, C.R, (1997). Cell formation considering fuzzy demand and machine capacity. International Journal of Advanced Manufacturing Technology, 13(2), 134-147.

Tsai, C. C., Chu, C. H., & Barta, T. (1997). Analysis and modeling of a manufacturing cell formation problem with 17. Fuzzy integer programming. IIE Transactions, 29(7), 533–547.

Tavakkoli-Moghaddam, R., Javadian, N., Javadi, B., & Safaei, N. (2007). Design of a facility layout problem in CMS with stochastic demand, Applied Mathematics and Computation, 184(2), 721-728.

Venkataramanaiah, S. (2007). Scheduling in cellular manufacturing systems: an heuristic approach. International Journal of Production Research, 1, 1-21.

Wu, X. D., Chu, C. H., Wang, Y. F., & Yan, W. L. (2006). Concurrent design of cellular manufacturing systems: A genetic algorithm approach. International Journal of Production Research, 44(6), 1217–1241.
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Journal: International Journal of Industrial Engineering Computations | Year: 2011 | Volume: 2 | Issue: 3 | Views: 2371 | Reviews: 0

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