In this paper, the three Correct, MA, and EWMA Methods for series demand function model (ARiMA(1, 0, 0), ARiMA(0, 0, 1), ARiMA(1, 0, 1)) have been described, formulated, and presented to examine the influence of forecast-updating methods between order quantity and actual demand in the amplifications of bullwhip effect. By using these forecast-updating methods comparison, the optimal solution of the bullwhip effect control Policies with a time-series technique under a basic one supply chain stage perspective can be obtained. Through the comparison of the more flexible bullwhip effect control Policies, a more efficient demand function model strategy of the parameter setting, using and the integrated application method in the supply chain management procedure was decided to use. In addition, a simulated procedure and systems analysis regarding these series demand uncertainty modeling parameters will be conducted to investigate the fluctuation effects on the amplifications of bullwhip effect. The proposed method permits controlling the retailer orders' variability above the other factors in the bullwhip effect.
ASJC Scopus subject areas
- Computer Science Applications
- Artificial Intelligence