Application of a Combination Forecasting Model in Logistics Parks´ Demand

Author

Qin, Chen ; Ming, Qi

Author_Institution

Sch. of Econ. & Commerce, South China Univ. of Technol., Guangzhou, China

fYear

2010

fDate

7-9 May 2010

Firstpage

2394

Lastpage

2397

Abstract

Logistics parks´ demand is an important basis of establishing the development policy of logistics industry and logistics infrastructure for planning. In order to improve the forecast accuracy of logistics parks´ demand, a combination forecasting model is proposed in this paper. Firstly, we use grey forecast model and exponential smoothing method to predict the demand respectively, then we combine the two results by using simulated annealing algorithm (SSA) to select appropriate weight. Experimental results show that the combination forecast model obtain lower total absolute error and average absolute error.

Keywords

forecasting theory; grey systems; logistics; simulated annealing; smoothing methods; combination forecasting model; exponential smoothing method; grey forecast model; logistics industry; logistics infrastructure; logistics parks demand; planning; simulated annealing algorithm; Biological system modeling; Forecasting; Logistics; Prediction algorithms; Predictive models; Simulated annealing; Smoothing methods; Logistics parks´ demand; combine; exponential smoothing method; grey forecast model; simulated annealing algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

E-Business and E-Government (ICEE), 2010 International Conference on

Conference_Location

Guangzhou

Print_ISBN

978-0-7695-3997-3

Type

conf

DOI

10.1109/ICEE.2010.605

Filename

5592670