USING FUZZY LINEAR PROGRAMMING TO OPTIMIZE INVENTORY CONTROL POLICY IN A HYBRID MANUFACTURING/REMANUFACTURING SYSTEM
Keywords:
Hybrid manufacturing/remanufacturing system, fuzzy linear programming, fuzzy optimization, fuzzy lead time and production timeAbstract
Remanufacturing can bring used or end of life products back to like-new products. The production planning of inventory control policies in a hybrid manufacturing/ remanufacturing system with different prioritizations (manufacturing vs. remanufacturing) is investigated in this study. For this production planning problem, the imprecision of customer demand, related operating costs, number of returned used components and all lead time and production times are uncertain. This uncertainty complicates the planning of the production and inventory control. The fuzzy set theory is employed due to the presence of the imprecise information, and the Fuzzy Linear Programming (FLP) is applied to optimize the model under these uncertainties. The proposed approach maximizes the most likely value of the profit, minimizes the risk of obtaining a lower profit, and maximizes the possibility of obtaining a higher profit for each production planning policy. The results show that the Priority-To-Remanufacturing (PTR) policy shows a higher profit than the policy of Priority-To-Manufacturing (PTM) and FLP can help decision makers to be aware of the risks and effects of uncertainties in their plans. As a result, they can prepare in advance for such scenarios
References
Abbey, J.D., Meloy, M.G., Blackburn, J., and Guide, V.D.R. (2015). Consumer markets for remanufactured and refurbished products. California Management Review, 57(4):26–42.
Amid, A., Ghodsypour, S.H., and Brien, C.O. (2009). A weighted additive fuzzy multiobjective model for the supplier selection problem under price breaks in a supply Chain. Int. J. Product. Econ., 121(2):323–332.
Bellman, R.E. and Zadeh, L.A. (1970). Decision-making in a fuzzy environment. Manage. Sci., 17(4):B-141-B-164.
Buckley, J.J. (1989). Solving possibilistic linear programming problems. Fuzzy Sets Syst., 31(3):329–341.
Diaz-Madroflero, M., Mula, J., and Jiménez, M. (2015). Material requirement planning under fuzzy lead times. IFAC-PapersOnLine, 28(3):242–247.
Inderfurth, K. (2004). Optimal policies in hybrid manufacturing/remanufacturing systems with product substitution. Int. J. Product. Econ., 90(3):325–343.
Li, J., González, M., and Zhu, Y. (2009). A hybrid simulation optimization method for production planning of dedicated remanufacturing. Int. J. Product. Econ., 117(2): 286–301.
Ozgen, D. and Gulsun, B. (2014). Combining possibilistic linear programming and fuzzy AHP for solving the multi-objective capacitated multi-facility location problem. Inform. Sci., 268:185–201.
Wang, J., Zhao, J., and Wang, X. (2011). Optimum policy in hybrid manufacturing/remanufacturing system. Comp. Indust. Eng., 60(3):411–419.
Zadeh, L.A. (1977). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst., 100:9–34.
Zimmermann, H.J. (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy Sets Syst., 1(1):45–55.
