Periodic and continuous inventory models in the presence of fuzzy costs

Abstract: This paper presents two models, a periodic review model and a continuous review inventory model with fuzzy setup cost, holding cost and shortage cost. We use two methods in the name of signed distance and possibilistic mean value to defuzzify. Also we consider the lead time demand and the lead-time plus one period’s demand as random variables. To validate the models and the solution procedures we apply them to a transformer manufacturing, 'Iran transfo', company. Furthermore we design a decision support system which can be used for efficient evaluation of the proposed models in fuzzy environment.

How to cite this paper

 Sadi-Nezhad, S., Nahavandi, S & Nazemi, J. (2011). Periodic and continuous inventory models in the presence of fuzzy costs.International Journal of Industrial Engineering Computations , 2(1), 179-192.

Refrences

Cakir, O. & Canbolat, M. S. (2008). A web-based decision support system for multi-criteria inventory classification using fuzzy AHP methodology, Canada Expert Systems with Applications, 35, 1367–1378.

Chang, H-C., Yao, J-S. & Ouyang, L-Y. (2004). Fuzzy mixture inventory model with variable lead-time based on probabilistic fuzzy set and triangular fuzzy number, Mathematical and Computer Modelling, 39, 287-304.

Day, O. & Chakraborty, D. (2009). Fuzzy periodic review system with fuzzy random variable demand. European Journal of Operational Research, 198(1), 113-120.

Kao, C-K & Hsu, W-K, (2002). Lot size-reorder point inventory model with fuzzy demands, Computers & Mathematics with Applications, 43, 1291-1302.

Hadley, G., Whitin, T.M., (1963). Analysis of Inventory Systems. Prentice-Hall, New Jersey.

Handfield, R., Warsing, D. & Wu, X. (2009). (Q,r) Inventory policies in a fuzzy uncertain supply chain environment, European Journal of Operational Research, 197(2), 609-619.

Lin, Y-J. (2008). A periodic review inventory model involving fuzzy expected demand short and fuzzy backorder rate, Computers & Industrial Engineering, 54(3), Pages 666-676.

Modarres, M, Sadi-Nezhad, S & Arabi, F. (2010), Fuzzy analytical hierarchy process using preference ratio: A case study for selecting management short course in a business school, International Journal of Industrial Engineering Computations, 1(2), 173-184.

Tütüncü, G. Y., Aköz, O., Apaydın, A. & Petrovic, D. (2008). Continuous review inventory control in the presence of fuzzy costs, International Journal of Production Economics, 113(2),775-784.

Vijayan, T. & Kumaran, M. (2008). Inventory models with a mixture of backorders and lost sales under fuzzy cost, European Journal of Operational Research, 189(1), 105-119.

Wu, K. & Yao, J-S., (2003). Fuzzy inventory with backorder for fuzzy order quantity and fuzzy shortage quantity, European Journal of Operational Research, 150(2), 320-352.

Yao, J-S. & Lee, H-M. (1999). Fuzzy inventory with or without backorder for fuzzy order quantity with trapezoid fuzzy number, Fuzzy Sets and Systems, 105(3), 311-337.

Yao, J-S. & Su, J-S. (2000). Fuzzy inventory with backorder for fuzzy total demand based on interval-valued fuzzy set, European Journal of Operational Research, 124(2), 390-408.

Yao, J-S. & Chiang, J. (2003). Inventory without backorder with fuzzy total cost and fuzzy storing cost defuzzified by centroid and signed distance, European Journal of Operational Research, 148(2, 401-409.

Zadeh, L., (1965). Fuzzy sets, Information and Control, 8, 338-353.