Volume 24 , Issue 3 , PP: 56-64, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Manjula G. J. 1 , N. Anitha 2 * , A. P. Pushpalatha 3 , K. Vinaya Laxmi 4 , M. Premalatha 5 , Mekala Selvaraj 6
Doi: https://doi.org/10.54216/IJNS.240305
Inventory management is characterized by a continuous struggle to lower goods levels and related costs while also providing customers with the goods they need. However, reducing costs while simultaneously striving for ideal inventory levels is difficult, notably in the current situation of high unpredictability of goods demand and lead time. Traditional inventory models are not strong enough to endure changes like goods demand and lead-time demand. As a result, it must be adjusted to achieve results. The oeuvre below presents a new kind of inventory model that deals with uncertainty in the demand for goods and lead time. In this regard, the presented work, the novel Neutrosophic Economic Order Quantity approach is a mechanism to account for the likely imprecision in the model. Specifically, the Neutrosophic set theory is integrated into the EOQ model so that it can handle variations in the demand and lead-time pattern successfully. An objective function is established for obtaining economical order quantities that include demand, lead-time, and other necessary components’ irregularities. The process variables in the model are given the final values using genetic algorithms and simulated annealing. To highlight the impact of the proposed Neutrosophic approach, it is then applied to several realistic examples. This will provide the audience a sense of how effective inventory management may be in high-uncertainty situations. The rapid evolution of organizations necessitates innovative inventory control tactics to meet growing demands
EOQ , Inventory Model , Neutrosophic model , Optimization , Python.
[1] Kar, C., Roy, T. K., & Maiti, M. (2022). EOQ model with price, marketing, service and green dependent neutrosophic demand under uncertain resource constraint: A geometric programming approach. Neutrosophic Sets and Systems, 51, 797-823.
[2] Loganayaki, S., Rajeswari, N., Kirupa, K., & Broumi, S. (2024). Optimization of triangular neutrosophic based economic order quantity model under preservation technology and power demand with shortages. Neutrosophic Sets and Systems, 65, 11-31.
[3] Mondal, B., Garai, A., Mukhopadhyay, A., & Majumder, S. K. (2021). Inventory policies for seasonal items with logistic-growth demand rate under fully permissible delay in payment: a neutrosophic optimization approach. Soft Computing, 25(5), 3725-3750.
[4] Sarkar, D., & Srivastava, P. K. (2022). A dynamic optimization approach for multi-item multi-objective fixed-place neutrosophic fuzzy inventory and green management system. Mathematics in Engineering, Science & Aerospace (MESA), 13(2).
[5] Momena, A. F., Haque, R., Rahaman, M., Salahshour, S., & Mondal, S. P. (2024). The Existence and Uniqueness Conditions for Solving Neutrosophic Differential Equations and Its Consequence on Optimal Order Quantity Strategy. Logistics, 8(1), 18.
[6] Kar, C., De, M., Maiti, M., & Das, P. (2024). Multi-objective perishable multi-item green inventory models with uncertain finite time horizons and constraints by neutrosophic optimisation approach. International Journal of Mathematics in Operational Research, 27(2), 167-198.
[7] De, S. K., Nayak, P. K., Khan, A., Bhattacharya, K., & Smarandache, F. (2020). Solution of an EPQ model for imperfect production process under game and neutrosophic fuzzy approach. Applied Soft Computing, 93, 106397.
[8] Karthick, B., & Shafiya, M. (2024). A Smart Manufacturing on Multi-echelon Sustainable Supply Chain Under Uncertain Demand. Process Integration and Optimization for Sustainability, 8(1), 143-163.
[9] Rahaman, M., Mondal, S. P., Alam, S., & Goswami, A. (2021). Synergetic study of inventory management problem in uncertain environment based on memory and learning effects. Sādhanā, 46(1), 39.
[10] Pal, S., & Chakraborty, A. (2020). Triangular neutrosophic based production reliability model of deteriorating item with ramp type demand under shortages and time discounting. Neutrosophic Sets and Systems, 35(1), 347-367.
[11] De, S. K., Roy, B., & Bhattacharya, K. (2022). Solving an EPQ model with doubt fuzzy set: a robust intelligent decision-making approach. Knowledge-Based Systems, 235, 107666.
[12] Barman, H., Roy, S. K., Sakalauskas, L., & Weber, G. W. (2023). Inventory model involving reworking of faulty products with three carbon policies under neutrosophic environment. Advanced Engineering Informatics, 57, 102081.
[13] Broumi, S., Mohanaselvi, S., Witczak, T., Talea, M., Bakali, A., & Smarandache, F. (2023). Complex fermatean neutrosophic graph and application to decision making. Decision Making: Applications in Management and Engineering, 6(1), 474-501.
[14] Broumi, S., Raut, P. K., & Behera, S. P. (2023). Solving shortest path problems using an ant colony algorithm with triangular neutrosophic arc weights. International Journal of Neutrosophic Science, 20(4), 128-28.
[15] Supakar, P., Kumar, N., Mahato, S. K., & Pal, P. (2023). Neutrosophic trade-credit EOQ model for deteriorating items considering expiration date of the items using different variants of particle swarm optimizations. International Journal of System Assurance Engineering and Management, 1-25.
[16] Mondal, B., Biswas, S., Garai, A., & Roy, T. K. (2019, March). Posynomial Geometric Programming in EOQ Model with Interval Neutrosophic Number. In International Conference on Information Technology and Applied Mathematics (pp. 434-449). Cham: Springer International Publishing.
[17] Mohanta, K., Jha, A. K., Dey, A., & Pal, A. (2023). An application of neutrosophic logic on an inventory model with two-level partial trade credit policy for time-dependent perishable products. Soft Computing, 27(8), 4795-4822.
[18] Garg, H., Rajeswari, S., Sugapriya, C., & Nagarajan, D. (2022). A model for container inventory with a trapezoidal bipolar neutrosophic number. Arabian Journal for Science and Engineering, 47(11), 15027-15047.
[19] Das, K., & Islam, S. (2024). A deterministic multi-item inventory model with quadratic demand under neutrosophic and pythagorean hesitant fuzzy programming approach. Results in Control and Optimization, 14, 100367.
[20] Kar, C., Mondal, B., & Roy, T. K. (2018). An inventory model under space constraint in neutrosophic environment: a neutrosophic geometric programming approach. Neutrosophic Sets and Systems: An International Book Series in Information Science and Engineering, 21(2018), 93-109.
