Abstract
An inventory model for a single deteriorating item under fuzzy environment has been presented in this paper. Here demand rate is considered to be constant for some time period, post which the same is a linear function of time. This situation is common during the time of a new product launch in the market. As the product becomes popular, its demand increases with time although it remains constant during the initial days. Cycle time is considered to be constant in most of the models. However, practically it has been observed that it is difficult to pro-actively predict the cycle time. Because of this problem, cycle time has been considered as uncertain and has been further described as Symmetric Triangular Fuzzy number. The Signed Distance method has been used for defuzzification of the total cost function. For illustration of the process for finding the total optimal cost and the cycle time, numerical examples have been considered. The effects of changing parameter values on the optimal solution of the system have been demonstrated through Sensitivity Analysis.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bellman, R. E., & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management Science, 17(4), 141–164.
Bera, U. K., Bhunia, A. K., & Maiti, M. (2013). Optimal partial backordering two-storage inventory model for deteriorating items with variable demand. International Journal of Operational Research, 16(1), 96.
Dubois, D., & Prade, H. (1978). Operations on fuzzy numbers. International Journal of Systems Science, 9(6), 613–626.
Dutta, D., & Kumar, P. (2015). A partial backlogging inventory model for deteriorating items with time-varying demand and holding cost. International Journal of Mathematics in Operational Research, 7(3), 281.
Dutta, P., Chakraborty, D., & Roy, A. R. (2005). A single-period inventory model with fuzzy random variable demand. Mathematical and Computer Modelling, 41(8–9), 915–922.
Ghosh, S. K., & Chaudhuri, K. S. (2004). An order-level inventory model for a deteriorating item with Weibull distribution deterioration, time-quadratic demand and shortages. AMO-Advanced Modeling and Optimization, 6(1), 21–35.
He, W., Wei, H. E., & Fuyuan, X. U. (2013). Inventory model for deteriorating items with time-dependent partial backlogging rate and inventory level-dependent demand rate. Journal of Computer Applications, 33(8), 2390–2393.
Hu, J., Guo, C., Xu, R., & Ji, Y. (2010). Fuzzy economic order quantity model with imperfect quality and service level. In 2010 Chinese Control and Decision Conference [Internet]. Available from https://doi.org/10.1109/ccdc.2010.5498441
Jaggi, C. K., Pareek, S., Sharma, A., & Nidhi. (2013). Fuzzy inventory model for deteriorating items with time-varying demand and shortages. American Journal of Operational Research, 2(6), 81–92.
Kao, C., & Hsu, W. K. (2002). A single-period inventory model with fuzzy demand. Computers & Mathematics with Applications, 43(6–7), 841–848.
Lin, C., Tan, B., & Lee, W. C. (2000). An EOQ model for deteriorating items with time-varying demand and shortages. International Journal of System Science, 31(3), 391–400.
Mishra, N., Mishra, S. P., Mishra, S., Panda, J., & Misra, U. K. (2015). Inventory model of deteriorating items for linear holding cost with time dependent demand. Mathematical Journal of Interdisciplinary Sciences, 4(1), 29–36.
Pal, A. K., Bhunia, A. K., & Mukherjee, R. N. (2006). Optimal lot size model for deteriorating items with demand rate dependent on displayed stock level (DSL) and partial backordering. European Journal of Operational Research, 175(2), 977–991.
Park, K. S. (1987). Fuzzy-set theoretic interpretation of economic order quantity. IEEE Transactions on Systems, Man, and Cybernetics, 17(6), 1082–1084.
Priyan, S., & Manivannan, P. (2017). Optimal inventory modelling of supply chain system involving quality inspection errors and fuzzy effective rate. OPSEARCH, 54, 21–43.
Roy, A., & Samanta, G. P. (2009). Fuzzy continuous review inventory model without backorder for deteriorating items. Electronic Journal of Applied Statistical Analysis, 2, 58–66.
Wang, T. Y., & Chen, L. H. (2001). A production lot size inventory model for deteriorating items with time-varying demand. International Journal of Systems Science, 32(6), 745–751.
Wang, X., Tang, W., & Zhao, R. (2007). Fuzzy economic order quantity inventory models without backordering. Tsinghua Science and Technology, 12(1), 91–96.
Wu, K., & Yao, J.-S. (2003). Fuzzy inventory with backorder for fuzzy order quantity and fuzzy shortage quantity. European Journal of Operational Research, 150(20), 320–352.
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.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Shee, S., Chakrabarti, T. (2021). Fuzzy Inventory Model for Deteriorating Items in a Supply Chain System with Time Dependent Demand Rate. In: Shah, N.H., Mittal, M. (eds) Soft Computing in Inventory Management. Inventory Optimization. Springer, Singapore. https://doi.org/10.1007/978-981-16-2156-7_4
Download citation
DOI: https://doi.org/10.1007/978-981-16-2156-7_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-2155-0
Online ISBN: 978-981-16-2156-7
eBook Packages: Business and ManagementBusiness and Management (R0)