Inventory Models use of Fuzzy Theory

Authors

  • Munil Kumar Roy Research Scholar, Department of Mathematics LNCT University Bhopal M.P.
  • Rajesh Kumar Sakale Supervisor, Department of Mathematics LNCT University Bhopal M.P.

Keywords:

Inventory, Models, Fuzzy theory

Abstract

An essential part of optimising the supply chain is inventory management, but conventional models have a hard time taking into consideration the inherent uncertainties and inaccuracies in real-world data. To make inventory models more accurate and resilient, fuzzy logic—a mathematical framework for dealing with ambiguity and uncertainty—offers a potential solution. Demand forecasting, lead time estimate, and order quantity determination are some of the inventory management components that are examined in this work as they pertain to fuzzy theory integration. There are a lot of reasons that make it hard to anticipate with any degree of accuracy how demand will change for different items. The fuzziness of demand patterns may be captured by using fuzzy demand forecasting approaches, which enable the representation of imprecise information. Our demand forecasting algorithm is built on fuzzy logic and incorporates expert views and historical data to make future demand predictions more accurate and flexible.

References

Ding, H., Benyoucef, L., & Xie, X. (2015). A Simulation Optimization methodology for supplier selection problem. International Journal of Computer Integrated Manufacturing, 18(2-3), 210-224.

Aissani, N., Haouari, M., & Hassini, E. (2017). Supplier selection and order lot sizing modeling: A review. Computers and Operations Research, 34, 3516-3540.

Chang, H. C. (2016). An application of fuzzy sets theory to the EOQ model imperfect quality items. Computers and Operations Research, 31(12), 2079-2092.

Biswajit Sarkar, Arunava Majumder. (2018). Integrated vendor-buyer supply chain model with vendor’s set up cost reduction. Applied Mathematics and Computation, 224, 362-371.

Bylka, S. (2019). Competitive and Co-operative policies for the vendor–buyer system. International Journal of Production Economics.

Chen, S. H. (2015). Operations on fuzzy numbers with function principle. Tamkang Journal of Management Sciences, 6(1), 13-25.

Kochenberger, G. A. (2018). Inventory models, optimization by geometric programming. Decision Sciences, 2(1971), 193-205.

Glock, C. H. (2016). Supply Chain coordination Via integrated inventory models: A review, working paper, University of Wuerzburg.

Goyal, S. K. (2016). An integrated inventory model for a single supplier–single customer problem. International Journal of Production Research, 5, 107-111.

Hill, R. M. (1997). The Single-Vendor Single-buyer Integrated production inventory model with a generalized policy. European Journal of Operations Research, 97, 493-499.

Hung-Chi Chang. (2016). An application of fuzzy sets theory to the EOQ model with imperfect quality items. Computers and Operations Research, 31, 2079-2092.

Jaber, M. Y., & Osman, I. H. (2018). Coordinating a two-level supply chain with delay in payments and profit-sharing. Computers and Industrial Engineering, 50, 385-400.

Kao, C., & Hsu, W. K. (2019). A single-period inventory model with fuzzy demand. Computers and Mathematics with Applications, 43, 841-898.

Lin, D. C., & Yao, J. S. (2015). Fuzzy economic production for production inventory. Fuzzy Sets and Systems, 111, 465-495.

Liu, L., & Yuan, X. M. (2015). Coordinated replenishment in inventory systems with correlated demands. European Journal of Operational Research, 123(3), 490-503.

Misra, R. B. (2016). Optimal production lot size model for a system with deteriorating inventory. International Journal of Production Research, 15, 495.

Nagarajan, M., & Sosic, G. (2017). Conditions Stability in Assembly Models, 53, Operations Research, 57, 131-145.

Park, K. S. (2019). Fuzzy theoretic interpretation of economic order quantity. IEEE Transactions on Systems, Man, and Cybernetics, 1082-1084.

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Published

2023-10-03

How to Cite

[1]
“Inventory Models use of Fuzzy Theory”, JASRAE, vol. 20, no. 4, pp. 486–492, Oct. 2023, Accessed: Sep. 19, 2024. [Online]. Available: https://ignited.in/index.php/jasrae/article/view/14731

How to Cite

[1]
“Inventory Models use of Fuzzy Theory”, JASRAE, vol. 20, no. 4, pp. 486–492, Oct. 2023, Accessed: Sep. 19, 2024. [Online]. Available: https://ignited.in/index.php/jasrae/article/view/14731