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Freight Transport Demand Forecasting in Urban Logistics Planning: A Case Study of Yiwu City

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Abstract:

Freight transport demand forecasting as one of the basis in urban logistics planning, is not only an important premise of designing a variety of logistics development policies and infrastructure constructions, but also a key indicator to measure whether the logistics planning is reasonable. This paper addresses the methods of the freight transport demand forecasting in urban logistics planning based on a case study of Yiwu city. Considering the change of long-term trend emphatically, conventional trend extrapolation method, regression analysis method, elasticity coefficient method, linear exponential smoothing method and grey model are applied to predict the logistics demand of Yiwu city respectively. Then the results of five kinds of forecasting methods are analyzed to obtain the final forecasting logistics demand.

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Periodical:

Applied Mechanics and Materials (Volumes 505-506)

Pages:

915-921

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.505-506.915

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Cite this paper

Online since:

January 2014

Authors:

Shi Chao Sun, Zheng Yu Duan*, Chuan Chen

Keywords:

Freight Transport Demand Forecasting, Urban Logistics Planning, Yiwu City

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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References

[1] Zhejiang Provincial Bureau of Statistics (2010). Census (2010).

Google Scholar

[2] Gregory A. Godfrey, Warren B. Powell (2000). Adaptive estimation of daily demands with complex calendar effects for freight transportation. Transportation Research Part B, Vol. 34 (06), pp.451-469.

DOI: 10.1016/s0965-8564(99)00032-4

Google Scholar

[3] Chiou, Hua-Kai, Tzeng (2004). Grey prediction model for forecasting the planning material ofequipment spare parts in navy of Taiwan. Soft Computing with Industrial Applications—Proceedingsof the Sixth Biannual Word Automation Congress, 315-320.

Google Scholar

[4] AL-Deek, Haitham M (2000). Use of vessel freight data to forecast heavy truck movements atseaports. Transportation System Institute, Department of Civil Environment Engineering, University of CentralFlorida, Orlando, FL32816. 2450, United States.

DOI: 10.3141/1804-29

Google Scholar

[5] Garrido, Rodrig A, Mahmassani (2000). Forecasting freight transportation demand with thespace-time multinomial probit model. Transportation ResearchPart B. 34: 403-418.

DOI: 10.1016/s0191-2615(99)00032-6

Google Scholar

[6] Paulo. S. A. Freitas, Antonio J. L. Rodrigues (2006). Model combination in neural-based forecasting. European Journal of Operational Research, 173: 801-814.

DOI: 10.1016/j.ejor.2005.06.057

Google Scholar

[7] Jiang Huiyuan, Yang Daming (2006). The Forecast Methods of Volume of Water Freight for Comparison. Operations Research and Management Science. VoL. 11 (3): 74-79.

Google Scholar