Investigating the effect of demand aggregation on the performance of an (R, Q) inventory control policy

Abstract

This paper investigates the effect of demand aggregation on the performance measures of an inventory system controlled by a (r, Q) policy. Demand usage data is available at different time scales, i.e., daily, weekly, monthly etc., and forecasting is based on these time scales. Using forecasts, appropriate lead time demand models are constructed and used in optimization procedures. The question being investigated is what effect the forecasting time bucket has on whether or not the inventory control model meets planned performance. A simulation model is used to compare performance under different demand aggregation levels. The simulation model of the optimized (r, Q) inventory system is run for the planning horizon and the supply chain operational performance measures like ready rate, expected back order etc., are collected. Subsequently, the effect of aggregating the demand and planning accordingly is analyzed based on the simulated supply chain's operational performance.

Pricing Policy in an Inventory Model with Green Level Dependent Demand for a Deteriorating Item

“…In their suggested paradigm for decaying goods, Hsieh and Dye [28] presented the notion of preservation technology. For degrading objects under preservation technology, Rossetti et al [29] investigated the impact of the demand of (r, q) inventory model. Tayal et al [30] presented the ideal strategy of a two-echelon inventory model.…”