Name
Title | ||
|---|---|---|
A Novel Dynamic Demand Forecasting Model for Resilient Supply Chains using Machine Learning |
Abstract | ||
|---|---|---|
Supply chain literature reveals that study of resilient supply chains and bullwhip effect (BE) have been receiving special attention during pandemic for supply chains with seasonal as well as nonseasonal demand components. The BE phenomenon has been detected in various industries and sectors, and causes multiple inefficiencies such as higher costs of producing more than needed, wastage and transpo... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/COMPSAC51774.2021.00040 | 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC) |
Keywords | DocType | ISSN |
Measurement,Costs,Supply chains,Time series analysis,Fitting,Demand forecasting,Machine learning | Conference | 0730-3157 |
ISBN | Citations | PageRank |
978-1-6654-2463-9 | 2 | 0.42 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Md. Erfanul Hoque | 1 | 2 | 2.11 |
| A. Thavaneswaran | 2 | 130 | 21.94 |
| Srimantoorao S. Appadoo | 3 | 4 | 1.51 |
| Ruppa K. Thulasiram | 4 | 652 | 57.27 |
| Behrouz Banitalebi | 5 | 8 | 2.35 |