SavedAdd your journal

Journals / An International Journal of Optimization and Control: Theories & Applications (IJOCTA) / 2013 / Cilt: 3 - Sayı: 1

An algorithm for solution of an interval valued EOQ model

Susovan CHAKRABORTTYA
Madhumangalr PAL
Prasun Kumar NAYAKC
Pages
55–64
Publication Date
2022-10-11
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Finally a sensitive analysis of the optimalsolution with respect to the parameters of the model is examined.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper deals with the problem of determining the economic order quantity (EOQ)in the interval sense.
📊
Key Findings & Data:A purchasing inventory model with shortages and lead time, whose carryingcost, shortage cost, setup cost, demand quantity and lead time are considered as interval numbers,instead of real numbers.
💡
Conclusion & Impact:Finally a sensitive analysis of the optimalsolution with respect to the parameters of the model is examined.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

This paper deals with the problem of determining the economic order quantity (EOQ)in the interval sense. A purchasing inventory model with shortages and lead time, whose carryingcost, shortage cost, setup cost, demand quantity and lead time are considered as interval numbers,instead of real numbers. First, a brief survey of the existing works on comparing and ranking anytwo interval numbers on the real line is presented. A common algorithm for the optimum productionquantity (Economic lot-size) per cycle of a single product (so as to minimize the total average cost) isdeveloped which works well on interval number optimization under consideration. A numerical exampleis presented for better understanding the solution procedure. Finally a sensitive analysis of the optimalsolution with respect to the parameters of the model is examined.

🔖

Cite This Article

CHAKRABORTTYA, S., PAL, M., NAYAKC, P. K. (2022). An algorithm for solution of an interval valued EOQ model. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), Cilt: 3 - Sayı: 1, 55–64. https://ajindex.com/articles/440735

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (1)

  1. 1] Sengupta, A., Pal, T. K., On comparing interval numbers. European Journal of Operational Research, 127(1), 28-43 (2000). [2] Lin, D.C., Yao, J. S., Fuzzy economic production for production inventory. Fuzzy Sets and Systems, 111, 465-495 (2000). [3] Haris, F.W., How many parts to make at once. Factory, The Magazine of Management, 10(2), 135-152 (1913). [4] Mahata, G.C., Goswami, A., Fuzzy EOQ models for deteriorating items with stock dependent demand and non-linear holding costs. International Journal of Applied Mathematics and Computer Sciences, 5(2), 94-98 (2009). [5] Mahata, G.C., Goswami, A., An EOQ Model with Fuzzy Lead Time, Fuzzy Demand and Fuzzy Cost coefficients. International Journal of Mathematical, Physical and Engineering Sciences 3:1 (2009). [6] Ishibuchi, H., Tanaka, H., Multiobjective programming in optimization of the interval objective function. European Journal of Operational Research, 48, 219-225 (1990). [7] Zimmermann, H.J., Fuzzy Set Theory and its Application. Kluwer Academic Publishers, Boston, (1991). [8] Kacprzyk, J., Staniewski, P., Long term inventory policy making through fuzzy decision making models. Fuzzy Sets and Systems, 8, 117-132 (1982). [9] Park, K.S., Fuzzy set theoretic interpretation of economic order quantity. IEEE Transactions on Systems, Man and Cybernetics, SMC, 17, 1082-1084 (1987). [10] Gen, M., Tsujimura, Y., Zheng, D., An application of fuzzy set theory to inventory contol models. Computers and Industrial Engineering, 33, 553-556 (1997). [11] Grzegorzewski, P., Nearest interval approximation of a fuzzy number. Fuzzy Sets and Systems, 130, 321-330 (2002). [12] Moore, R.E., Method and Application of Interval Analysis. SIAM, Philadelphia, (1979). [13] Chanas, S., Kuchta, D., Multiobjective programming in optimization of interval objective functions,A generalized approach. European Journal of Operational Research, 94(3), 594-598 (1996). [14] Mahato, S.K., Bhunia, A.K., Intervalarithmetic-oriented interval computing technique for global optimization. Applied Mathematics Research express, 2006, 1-19 (2006). [15] Wang, X., Tang, W., Zhao, R., Fuzzy Economic Order Quantity Inventory Model Without Backordering. Tsinghua science and technology, 12(1), 91-96 (2007). [16] Muhammad, A., Omar, A., Economic Order Quantity for Items with Two Types of Imperfect Quality. An International Journal of Optimization and Control: Theories & Applications, 2(1), 73-82 (2012). [17] Mohammed, F.U., Kazushi, S., Coordination and Optimiz