Proceedings of the Korean Operations and Management Science Society Conference (한국경영과학회:학술대회논문집)
- 2005.05a
- /
- Pages.658-663
- /
- 2005
An Empirical Study on Supply Chain Demand Forecasting Using Adaptive Exponential Smoothing
적응적 지수평활법을 이용한 공급망 수요예측의 실증분석
- Kim, Jeong-Il ;
- Cha, Gyeong-Cheon (Forbizone Inc.) ;
- Jeon, Deok-Bin ;
-
Park, Dae-Geun
;
- Park, Seong-Ho ;
- Park, Myeong-Hwan
- 김정일 (한국과학기술원 테크노경영대학원) ;
- 차경천 ;
- 전덕빈 (한국과학기술원 테크노경영대학원) ;
-
박대근
(한국과학기술원 테크노경영대학원)
;
- 박성호 (한국과학기술원 테크노경영대학원) ;
- 박명환 (한성대학교 산업공학과)
- Published : 2005.05.13
Abstract
This study presents the empirical results of comparing several demand forecasting methods for Supply Chain Management(SCM). Adaptive exponential smoothing using change detection statistics (Jun) is compared with Trigg and Leach's adaptive methods and SAS time series forecasting systems using weekly SCM demand data. The results show that Jun's method is superior to others in terms of one-step-ahead forecast error and eight-step-ahead forecast error. Based on the results, we conclude that the forecasting performance of SCM solution can be improved by the proposed adaptive forecasting method.
Keywords