Masters Theses
Date of Award
8-2021
Degree Type
Thesis
Degree Name
Master of Science
Major
Industrial Engineering
Major Professor
Mingzhou Jin
Committee Members
Mingzhou Jin, Ron D. Ford, Zhongshun Shi
Abstract
Inventory record inaccuracy (IRI) often arises in retail environments due to unaccounted stock loss. Theft, misplacement, spoilage, and transaction errors will reduce the true inventory values without changing the inventory record. As previous inventory replenishment policies assume perfect record accuracy, increasing IRI can cause unexpected stockout events, mistimed reorders and replenishment freezes. Solutions to rectifying IRI vary from the use of improved tracking technologies to prevent it initially occurring at all to recounting programs which estimate true inventory value. Unfortunately, in retail environments, high‑tracking technology is unsuitable and continuous counting programs are too costly. To address the limitations of current solutions, we offer a Periodic Replenish and Recount Policy (PRRP) which accounts for stochastic stock loss and minimizes total costs including recounting. The theoretical foundation of PRRP allows for the discovery of both an optimal order quantity as well as optimal count frequency for a given inventory system. We find that in instances of stochastic stock loss, PRRP balances the trade-offs between shortage, surplus and counting costs.
Recommended Citation
Ku, Colton K., "Periodic Replenish and Recount Policy to Address Record Inaccuracy from Stock Loss. " Master's Thesis, University of Tennessee, 2021.
https://trace.tennessee.edu/utk_gradthes/6153