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A Sustainable Inventory Model with Advertisement Effort for Imperfect Quality Items under Learning in Fuzzy Monsoon Demand

Author

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  • Osama Abdulaziz Alamri

    (Department of Statistics, University of Tabuk, Tabuk 71491, Saudi Arabia)

  • Navneet Kumar Lamba

    (Department of Mathematics, Shri Lemdeo Patil Mahavidyalaya, Mandhal 441210, Maharashtra, India)

  • Mahesh Kumar Jayaswal

    (Institute of Basic Sciences, Department of Mathematics, Maharaja Surajmal Brij University, Chak-Sakeetra Kumher, Bharatpur 321201, Rajasthan, India)

  • Mandeep Mittal

    (Department of Mathematics, School of Computer Science Engeeniring and Technology, Bennett University, Greator Noida 201310, Uttar Pradesh, India)

Abstract

In this paper, we proposed a sustainable inventory model with a learning effect for imperfect quality items under different kinds of fuzzy environments like crisp, general fuzzy, cloudy fuzzy, and monsoon fuzzy. We divided the mathematical model into three parts under the learning effect according to the real-time fuzzy components (crisp, cloudy, and monsoon environments) of the demand rate of the items. We minimized the total inventory cost with respect to cycle length in each environment under the proposed assumptions. The non-linear optimization technique is applied for the algorithm and the solution method to find the decision variable. Finally, we compared the total inventory cost under different fuzzy environments and our finding is that the fuzzy monsoon environment is a more effective fuzzy environment than crisp and cloudy fuzzy environments. We have presented a numerical example for the validation of the proposed model and have shown the impact of the inventory input parameters on the cycle length and total inventory fuzzy cost. The managerial insights and future scope of this proposed study have been shown in the sensitivity analysis and conclusion. The limitations, application, future extension and scope, and social implementation have been shown in this research study.

Suggested Citation

  • Osama Abdulaziz Alamri & Navneet Kumar Lamba & Mahesh Kumar Jayaswal & Mandeep Mittal, 2024. "A Sustainable Inventory Model with Advertisement Effort for Imperfect Quality Items under Learning in Fuzzy Monsoon Demand," Mathematics, MDPI, vol. 12(15), pages 1-41, August.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:15:p:2432-:d:1450498
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    References listed on IDEAS

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    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Nita H. Shah & Milan B. Patel & Pratik H. Shah, 2022. "Inventory policies under fuzzy and cloud fuzzy environment," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 14(4), pages 356-370.
    3. Janssen, Larissa & Claus, Thorsten & Sauer, Jürgen, 2016. "Literature review of deteriorating inventory models by key topics from 2012 to 2015," International Journal of Production Economics, Elsevier, vol. 182(C), pages 86-112.
    4. Wong, Bo K. & Lai, Vincent S., 2011. "A survey of the application of fuzzy set theory in production and operations management: 1998-2009," International Journal of Production Economics, Elsevier, vol. 129(1), pages 157-168, January.
    5. Salameh, M. K. & Jaber, M. Y., 2000. "Economic production quantity model for items with imperfect quality," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 59-64, March.
    6. Klein Haneveld, Willem K. & Teunter, Ruud H., 1998. "Effects of discounting and demand rate variability on the EOQ," International Journal of Production Economics, Elsevier, vol. 54(2), pages 173-192, January.
    7. Roy, Arindam & kar, Samarjit & Maiti, Manoranjan, 2010. "A volume flexible production-policy for randomly deteriorating item with trended demand and shortages," International Journal of Production Economics, Elsevier, vol. 128(1), pages 188-199, November.
    8. Bakker, Monique & Riezebos, Jan & Teunter, Ruud H., 2012. "Review of inventory systems with deterioration since 2001," European Journal of Operational Research, Elsevier, vol. 221(2), pages 275-284.
    9. Mula, J. & Poler, R. & Garcia-Sabater, J.P. & Lario, F.C., 2006. "Models for production planning under uncertainty: A review," International Journal of Production Economics, Elsevier, vol. 103(1), pages 271-285, September.
    10. Neelanjana Rajput & Anand Chauhan & R.K. Pandey, 2022. "Optimisation of finite economic production quantity model under cloudy normalised triangular fuzzy number," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 43(1/2), pages 168-187.
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    Cited by:

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