Research Articles

Qualitative phase space reconstruction analysis of supply-chain inventor time series

Chenxi Shao, Lizhong Wang, Lipeng Xiao, Jinliang Wu
South African Journal of Science | Vol 106, No 11/12 | a422 | DOI: https://doi.org/10.4102/sajs.v106i11/12.422 | © 2010 Chenxi Shao, Lizhong Wang, Lipeng Xiao, Jinliang Wu | This work is licensed under CC Attribution 4.0
Submitted: 30 August 2010 | Published: 19 November 2010

About the author(s)

Chenxi Shao, University of Science and Technology of China, China
Lizhong Wang, University of Science and Technology of China, China
Lipeng Xiao, University of Science and Technology of China, China
Jinliang Wu, University of Science and Technology of China, China

Abstract

The economy systems are usually too complex to be analysed, but some advanced methods have been developed in order to do so, such as system dynamics modelling, multi-agent modelling, complex adaptive system modelling and qualitative modelling. In this paper, we considered a supply-chain (SC) system including several kinds of products. Using historic suppliers’ demand data, we firstly applied the phase space analysis method and then used qualitative analysis to improve the complex system’s performance. Quantitative methods can forecast the quantitative SC demands, but they cannot indicate the qualitative aspects of SC, so when we apply quantitative methods to a SC system we get only numerous data of demand. By contrast, qualitative methods can show the qualitative change and trend of the SC demand. We therefore used qualitative methods to improve the quantitative forecasting results. Comparing the quantitative only method and the combined method used in this paper, we found that the combined method is far more accurate. Not only is the inventory cost lower, but the forecasting accuracy is also better.

Keywords

data mining; phase space; qualitative forecasting; quantitative forecasting; supply chain management

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