Peak Period Inventory Planning for Apparel Industry

Abstract

The purpose of this study is the development of a mathematical/computer model for inventory planning for items with very sharp peaks in demand. The demand at peak periods for these items constitutes the most of the annual demand. The correct amount of inventory must be built before the peak due to maximum order quantity lead-time and maximum inventory level constraints. This target inventory is dependent on inventory carrying charges stockout costs and sales revenues. We suggest an alternative way of determining the shortage cost. The problem is modeled as a dynamic programming problem utilizing the value iteration method of Howard. We assume that the seasonality and the expected demands are known. The proposed model can be used to find the optimal ordering amounts to maximize the expected profit from the season depending on the number of weeks left until the end of season and the initial inventory on-hand. Multiple regression models are developed to predict the season performance based upon critical input factors. Results show that lead-time is the most important factor in determining the season performance. Also some characteristics of optimal ordering patterns are presented. © 2024 Elsevier B.V. All rights reserved.