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Department of Mathematics, School of Basic Science and Technology, IIMT University , Meerut, Uttar Pradesh , India
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Department of Mathematics, School of basic Science and Technology, IIMT University , Meerut, Uttar Pradesh , India
School of Sciences, Indira Gandhi National Open University , Delhi , India
It presents a dynamic model of inventory management of the deteriorating items with time-sensitive demand and variable holding costs. The model is used to solve the problem in industries where demand is seasonal or because of other external conditions, like weather or market conditions. A two-tier inventory model is implemented as a way of minimizing the overall costs through holding costs, production costs, and losses of deteriorating items. Demand rate is exponential as well as linear in terms of the rate of deterioration. The model can be used to address a wide range of real-life conditions, such as shortages, irregular deterioration rates, and production constraints. Mathematical equations are given to model the inventory levels, and they are solved via differential equations. The model is used by providing numerical illustrations of how the model is applied to the optimization of inventory and the minimization of costs under different conditions. The statistical analysis and sensitivity analysis are carried out to see how various parameters, including deterioration rate, production time, and setup costs, among others, affect the overall system performance. The findings show that the deterioration rates, setup, and production time are increasing to result in increased total costs and reduced optimal levels of inventory and cycle times. Findings are useful in industries with perishable products since proper inventory management is important. It is possible to include more realistic assumptions in the model, like the presence of many products and non-linear deterioration rates. This study will add value to inventory management techniques and develop partnerships among supply chain partners in order to overcome inventory degradation and quality loss.
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