Information transformation in a supply chain: a simulation study
Computers and Operations Research
Automatica (Journal of IFAC)
The governing dynamics of supply chains: The impact of altruistic behaviour
Automatica (Journal of IFAC)
Organization and problem ontology for supply chain information support system
Data & Knowledge Engineering
Approximate Solutions of a Dynamic Forecast-Inventory Model
Manufacturing & Service Operations Management
Comments on "Information Distortion in a Supply Chain: The Bullwhip Effect"
Management Science
Is there a benefit to sharing market sales information? Linking theory and practice
Computers and Industrial Engineering
A Fuzzy agent-based model for reduction of bullwhip effect in supply chain systems
Expert Systems with Applications: An International Journal
Computers and Operations Research
Forecast facilitated lot-for-lot ordering in the presence of autocorrelated demand
Computers and Industrial Engineering
The effects of fuzzy forecasting models on supply chain performance
FS'08 Proceedings of the 9th WSEAS International Conference on Fuzzy Systems
On the link between inventory and responsiveness in multi-product supply chains
International Journal of Systems Science - Production Coordination and Inventory Policies
Fuzzy forecasting applications on supply chains
WSEAS TRANSACTIONS on SYSTEMS
Situation reactive approach to Vendor Managed Inventory problem
Expert Systems with Applications: An International Journal
An adaptive inventory control for a supply chain
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Multi-agent based distributed inventory control model
Expert Systems with Applications: An International Journal
Robust Approximation to Multiperiod Inventory Management
Operations Research
Improving Supply Chain Performance: Real-Time Demand Information and Flexible Deliveries
Manufacturing & Service Operations Management
Demand Forecasting Behavior: System Neglect and Change Detection
Management Science
Information Transmission and the Bullwhip Effect: An Empirical Investigation
Management Science
A belief-rule-based inventory control method under nonstationary and uncertain demand
Expert Systems with Applications: An International Journal
Delayed demand information and dampened bullwhip effect
Operations Research Letters
Bullwhip effect measure in a seasonal supply chain
Journal of Intelligent Manufacturing
Hi-index | 0.01 |
In this paper, we consider an adaptive base-stock policy for a single-item inventory system, where the demand process is nonstationary. In particular, the demand process is an integrated moving average process of order (0, 1, 1), for which an exponential-weighted moving average provides the optimal forecast. For the assumed control policy we characterize the inventory random variable and use this to find the safety stock requirements for the system. From this characterization, we see that the required inventory, both in absolute terms and as it depends on the replenishment lead-time, behaves much differently for this case of nonstationary demand compared with stationary demand. We then show how the single-item model extends to a multi-stage, or supply-chain context; in particular we see that the demand process for the upstream stage is not only nonstationary but also more variable than that for the downstream stage. We also show that for this model there is no value from letting the upstream stages see the exogenous demand. The paper concludes with some observations about the practical implications of this work.