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A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment

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  • Peidro, David
  • Mula, Josefa
  • Jiménez, Mariano
  • del Mar Botella, Ma

Abstract

This paper models supply chain (SC) uncertainties by fuzzy sets and develops a fuzzy linear programming model for tactical supply chain planning in a multi-echelon, multi-product, multi-level, multi-period supply chain network. In this approach, the demand, process and supply uncertainties are jointly considered. The aim is to centralize multi-node decisions simultaneously to achieve the best use of the available resources along the time horizon so that customer demands are met at a minimum cost. This proposal is tested by using data from a real automobile SC. The fuzzy model provides the decision maker (DM) with alternative decision plans with different degrees of satisfaction.

Suggested Citation

  • Peidro, David & Mula, Josefa & Jiménez, Mariano & del Mar Botella, Ma, 2010. "A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment," European Journal of Operational Research, Elsevier, vol. 205(1), pages 65-80, August.
    • Handle: RePEc:eee:ejores:v:205:y:2010:i:1:p:65-80
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    1. Andrew J. Clark & Herbert Scarf, 2004. "Optimal Policies for a Multi-Echelon Inventory Problem," Management Science, INFORMS, vol. 50(12_supple), pages 1782-1790, December.
    2. Amid, A. & Ghodsypour, S.H. & O'Brien, C., 2006. "Fuzzy multiobjective linear model for supplier selection in a supply chain," International Journal of Production Economics, Elsevier, vol. 104(2), pages 394-407, December.
    3. Petrovic, Dobrila, 2001. "Simulation of supply chain behaviour and performance in an uncertain environment," International Journal of Production Economics, Elsevier, vol. 71(1-3), pages 429-438, May.
    4. V. Sridharan & William L. Berry & V. Udayabhanu, 1987. "Freezing the Master Production Schedule Under Rolling Planning Horizons," Management Science, INFORMS, vol. 33(9), pages 1137-1149, September.
    5. Liu, Shiang-Tai & Kao, Chiang, 2004. "Solving fuzzy transportation problems based on extension principle," European Journal of Operational Research, Elsevier, vol. 153(3), pages 661-674, March.
    6. Xie, Ying & Petrovic, Dobrila & Burnham, Keith, 2006. "A heuristic procedure for the two-level control of serial supply chains under fuzzy customer demand," International Journal of Production Economics, Elsevier, vol. 102(1), pages 37-50, July.
    7. Kumar, Manoj & Vrat, Prem & Shankar, Ravi, 2006. "A fuzzy programming approach for vendor selection problem in a supply chain," International Journal of Production Economics, Elsevier, vol. 101(2), pages 273-285, June.
    8. Petrovic, Dobrila & Roy, Rajat & Petrovic, Radivoj, 1999. "Supply chain modelling using fuzzy sets," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 443-453, March.
    9. Jimenez, Mariano & Arenas, Mar & Bilbao, Amelia & Rodri'guez, M. Victoria, 2007. "Linear programming with fuzzy parameters: An interactive method resolution," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1599-1609, March.
    10. de Kok, Ton & Inderfurth, Karl, 1997. "Nervousness in inventory management: Comparison of basic control rules," European Journal of Operational Research, Elsevier, vol. 103(1), pages 55-82, November.
    11. Dubois, Didier & Fargier, Helene & Fortemps, Philippe, 2003. "Fuzzy scheduling: Modelling flexible constraints vs. coping with incomplete knowledge," European Journal of Operational Research, Elsevier, vol. 147(2), pages 231-252, June.
    12. Petrovic, Dobrila & Roy, Rajat & Petrovic, Radivoj, 1998. "Modelling and simulation of a supply chain in an uncertain environment," European Journal of Operational Research, Elsevier, vol. 109(2), pages 299-309, September.
    13. Pandian M. Vasant, 2005. "Fuzzy Linear Programming For Decision Making And Planning Under Uncertainty," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 4(04), pages 647-662.
    14. Wang, Juite & Shu, Yun-Feng, 2007. "A possibilistic decision model for new product supply chain design," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1044-1061, March.
    15. Shih, Li-Hsing, 1999. "Cement transportation planning via fuzzy linear programming," International Journal of Production Economics, Elsevier, vol. 58(3), pages 277-287, January.
    16. van Donselaar, K. & van den Nieuwenhof, J. & Visschers, J., 2000. "The impact of material coordination concepts on planning stability in supply chains," International Journal of Production Economics, Elsevier, vol. 68(2), pages 169-176, November.
    17. Herrera, F. & Verdegay, J. L., 1995. "Three models of fuzzy integer linear programming," European Journal of Operational Research, Elsevier, vol. 83(3), pages 581-593, June.
    18. Sakawa, Masatoshi & Nishizaki, Ichiro & Uemura, Yoshio, 2001. "Fuzzy programming and profit and cost allocation for a production and transportation problem," European Journal of Operational Research, Elsevier, vol. 131(1), pages 1-15, May.
    19. Giannoccaro, Ilaria & Pontrandolfo, Pierpaolo & Scozzi, Barbara, 2003. "A fuzzy echelon approach for inventory management in supply chains," European Journal of Operational Research, Elsevier, vol. 149(1), pages 185-196, August.
    20. Selim, Hasan & Araz, Ceyhun & Ozkarahan, Irem, 2008. "Collaborative production-distribution planning in supply chain: A fuzzy goal programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(3), pages 396-419, May.
    21. Hau L. Lee & Corey Billington, 1993. "Material Management in Decentralized Supply Chains," Operations Research, INFORMS, vol. 41(5), pages 835-847, October.
    22. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
    23. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    24. Shotaro Minegishi & Daniel Thiel, 2000. "System dynamics modeling and simulation of a particular food supply chain," Post-Print hal-02158574, HAL.
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