Author
Listed:
- Chandra K. Jaggi
(Department of Operational Research, Faculty of Mathematical Sciences, University of Delhi, Delhi, India)
- Aditi Khanna
(Department of Operational Research, Faculty of Mathematical Sciences, University of Delhi, Delhi, India)
- Sarla Pareek
(Department of Operational Research, Centre for Mathematical Sciences, Banasthali University, Banasthali, Rajasthan, India)
- Ritu Sharma
(Department of Operational Research, Centre for Mathematical Sciences, Banasthali University, Banasthali, Rajasthan, India)
Abstract
In this paper, the two-warehouse inventory problem is considered for deteriorating items with constant demand rate and shortages under inflationary conditions. In today’s unstable global economy, the effects of inflation and time value of money cannot be ignored; as it increases the cost of goods. To safeguard from the rising prices, during the inflation regime, the organization prefers to keep a higher inventory, thereby increasing the aggregate demand. This additional inventory needs additional storage space that is facilitated by a rented warehouse. Further ahead, in the real business world, to retain the freshness of the commodity, most of the organizations adopt the first-in-first-out (FIFO) dispatching policy. FIFO policy yields fresh and good conditioned stock thereby resulting in customer satisfaction, especially when items are deteriorating in nature. However, the two warehousing systems usually assume that the holding cost of items is more in RW than the OW due to modern preserving techniques. Therefore, to reduce the inventory costs, it is economical to consume the goods of RW at the earliest. This approach is termed as Last-In-First-Out (LIFO) approach. The objective of the present research is to develop a two warehouse inventory model with FIFO and LIFO dispatching policies under inflationary conditions. Further, comparison between FIFO and LIFO policies has been exhibited with the help of a numerical example. Sensitivity analysis has also been performed to study the impact of various parameters on the optimal solution.
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