SUPPLY CHAIN MODELLING AND CONTROL UNDER PROPORTIONAL INVENTORY-REPLENISHMENT POLICIES

Abstract A novel state-space model of a multi-node supply chain is presented, controlled via local proportional inventory-replenishment policies. The model is driven by a stochastic sequence representing customer demand. The model is analyzed under stationarity conditions and a simple recursive scheme is developed for updating the covariance matrix. This allows us to characterize the “bullwhip effect” (demand amplification) in the chain and to solve an optimization problem for a three-node model involving the minimization of inventory subject to a probabilistic constraint on downstream demand. Finally issues related to estimation schemes based on local historical data are discussed.