ABSTRACT:
Inventory control management remains a cornerstone of operational efficiency in modern supply chain systems. This study explores the Economic Order Quantity (EOQ) model, a foundational inventory control technique, by comparing its application under two distinct demand scenarios: constant and variable demand rates. This research highlights how demand variability influences optimal order quantities, total inventory costs, and decision-making processes through a detailed theoretical framework, mathematical analysis, and practical implications. From recent literature in operations research and supply chain management, the article provides insights into the adaptability of the EOQ model across diverse demand conditions, offering a comprehensive guide for practitioners and researchers alike.
Cite this article:
Sharma (2025). A Comparative Analysis of Inventory Models: Evaluating the Economic Order Quantity (EOQ) Model with Constant Demand versus Variable Demand Rates. Journal of Ravishankar University (Part-B: Science), 38(1), pp. 61-66. DOI:DOI: https://doi.org/10.52228/JRUB.2025-38-1-4
References
1. Chopra, S., & Meindl, P. (2016). Supply chain management: Strategy, planning,
and operation. Pearson.
2. Choi, T. M. (2014). Handbook of EOQ inventory problems: Stochastic and deterministic models.
Springer.
3. Giri, B. C., & Sharma, S. (2014). An EOQ model
with deteriorating items and time-varying demand. International Journal of Production Economics, 150, 132-138.
4. Glock, C. H., Grosse, E. H., & Ries, J. M. (2019).
Inventory management in supply chains: A review. European Journal of Operational Research, 279(3), 723-738.
5. Harris, F. W. (1913). How many parts to make at once. Factory, The Magazine of Management, 10(2),
135-136.
6. Heizer, J., Render, B., & Munson, C. (2017). Operations management: Sustainability and
supply chain management. Pearson.
7. Lau, H. S., & Lau, A. H. L. (2003). Effects of
inventory policies on supply chain performance. International Journal of Production Research, 41(8), 1785-1802.
8. Sana, S. S. (2011). An EOQ model with time-varying
demand and partial backlogging. European
Journal of Industrial Engineering, 5(4), 453-468.
9. Sarkar, B., Mandal, B., & Sarkar, S. (2015).
Quality improvement and backorder cost in an imperfect production process. International Journal of Production
Research, 53(6), 1798-1816. https://doi.org/10.1080/00207543.2014.958643
10. Silver, E. A., Pyke, D. F., & Peterson, R. (1998).
Inventory management and production
planning and scheduling. Wiley.
11. Taleizadeh, A. A., Noori-Daryan, M., &
Cárdenas-Barrón, L. E. (2017). Joint optimization of price, replenishment
frequency, and quality in a supply chain. International
Journal of Production Economics, 183, 246-258. https://doi.org/10.1016/j.ijpe.2016.10.008
12. Chopra, S. (2018). The evolution of inventory models
in supply chain management. Journal of
Business Logistics, 39(2), 89-102. https://doi.org/10.1111/jbl.12185
13. Goyal, S. K., & Giri, B. C. (2001). Recent trends
in modeling of deteriorating inventory. European
Journal of Operational Research, 134(1), 1-16. https://doi.org/10.1016/S0377-2217(00)00248-4
14. Teng, J. T., & Chang, C. T. (2005). Economic
production quantity models for deteriorating items with price- and
stock-dependent demand. Computers &
Operations Research, 32(2), 297-308. https://doi.org/10.1016/j.cor.2003.07.005
15.
Wee, H.
M., & Wang, W. T. (2013). Supply chain coordination for short-life-cycle
products with ramp-type demand. International
Journal of Production Economics, 141(1), 138-146. https://doi.org/10.1016/j.ijpe.2012.07.016