Article2016

An economic order quantity model considering different holding costs for imperfect quality items subject to fuzziness and learning

Ehsan Shekarian · Ezutah Udoncy Olugu · Salwa Hanim Abdul‐Rashid · Nima Kazemi

49 citations0/0 files storedJournal of Intelligent & Fuzzy Systems

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Supply Chain and Inventory Management Optimization and Mathematical Programming Fuzzy Systems and Optimization

Abstract

This paper extends an economic order quantity (EOQ) model for items with imperfect quality based on two different holding costs and learning considerations. This is one of the few attempts aiming at combining the EOQ model, learning theory, and fuzzy technique in solving an EOQ problem. In present research, a fuzzy model is developed in which both parameters and decision variables are fuzzified and represented by triangular fuzzy numbers (TFNs). The total profit per unit time is obtained using fuzzy arithmetic operations, and then defuzzified by the graded mean integration value (GMIV) method. Using Karush-Kuhn-Tucker (KKT) conditions, the optimal lot size is obtained from the defuzzified total profit per unit time function. A numerical example for investigating the behavior of the model in a fuzzy situation is presented, and directions for future study are proposed. Besides, the results of the developed fully fuzzy model are compared with some previous ones in the literature.

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References

1965Fuzzy sets 1996Fuzzy sets 1968Introduction to Operations Research 1936Factors Affecting the Cost of Airplanes 1980Operations Research -- An Introduction 1990How Many Parts to Make at Once 2000Economic production quantity model for items with imperfect quality 1968Introduction to Operations Research

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