Volume 16, Issue 3 (10-2019)                   2019, 16(3): 89-109 | Back to browse issues page

XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Najafi M, Daneshmand-Mehr M, Sadeghian R. The Impact of Forecasting Methods Combination for Reducing Bullwhip Effect in a Four-level Supply Chain under Variable Demand. Journal of Operational Research and Its Applications. 2019; 16 (3) :89-109
URL: http://jamlu.liau.ac.ir/article-1-1513-en.html
Department of Industrial Engineering, Islamic Azad University, Lahijan Branch, Lahijan, Iran
Abstract:   (1217 Views)
Bullwhip effect in a supply chain, makes inefficiencies such as excess inventory and overdue orders during the chain. These problems can be reduced by appropriate predictions. Forecasting must be done in all levels of a supply chain. This research addresses the problem of optimal combination of forecasting to reduce the bullwhip effect in a four-level supply chain when demand is variable. For this purpose, a four-level supply chain has been considered.  Moving average, exponential smoothing, linear regression and multilayer perceptron artificial neural network can be considered for predicting in each level. First, the desired supply chain is simulated for this means. The different combinations of aforementioned forecasting methods are calculated. Then a combination of forecasting methods which minimizes bullwhip effects is selected. Finally, the results are analyzed by variance analysis model. One combination has the lowest bullwhip effects. Moving average, neural networks, exponential smoothing and linear regression are determined for levels: retailer, wholesaler, manufacturer and supplier respectively. Other combinations have less utility
Full-Text [PDF 1238 kb]   (373 Downloads)    
Type of Study: Research | Subject: Special
Received: 2017/06/5 | Accepted: 2019/06/21 | Published: 2019/10/2

Add your comments about this article : Your username or Email:
CAPTCHA