Variable-weight combined forecasting model with causal analysis and clustering for refined oil sales forecasting

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NETL
NSTL
Wiley

外文摘要：Forecasting refined oil sales is essential in energy supply chain management. However, accurate forecasting is limited by several factors, including multiple influences of external features, heterogeneity of different gasoline stations, and difficulty in balancing linear and nonlinear forecasting. To address these issues, we propose a novel variable-weight combined forecasting model. In the first stage, the model incorporates causal analysis and clustering methods to provide a quantitative description of multiple effects of external features and highly correlated aggregation of homogeneous data. Subsequently, based on the patterns of external feature influences learned from historical data, variable-weight combined forecasting is realized to balance linear and nonlinear forecasting dynamically. Experiments based on real sales data procured from several regions demonstrate that the proposed model outperforms other benchmark and widely used models in terms of forecasting accuracy and statistical significance. The ablation experimental results confirm the significance of causal analysis, clustering, and variable-weight combined forecasting in improving the balance between linear and nonlinear forecasting. Moreover, our results indicate that improving the quality of clustering can yield greater benefits than improving the amount of training data. Finally, we also explore whether the forecasting superiority translates into better inventory control, and our results show that the proposed optimization model can effectively balance inventory cost and service level, while also better suppress the bullwhip effect.

外文关键词：

causal analysisclusteringinventory controlrefined oil sales forecastingvariable-weight combined forecasting

作者：

Xiaofeng Xu、Wenzhi Liu、Lean Yu、Yinsheng Yu、Wanli Yi

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作者单位：

Department of Management Science and Engineering,School of Economics and Management,China University of Petroleum Huadong-Qingdao Campus,Qingdao,China

Department of Management Science and Data Science,School of Business,Sichuan University,Chengdu,China

Department of Marketing,Shandong Hi-speed Supply Chain(Jinan)Co.,Ltd.,Jinan,China

Department of Product Services,Kunlun Digital Technology Co.,Ltd.,Beijing,China

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出版年：

2024

DOI：

10.1111/deci.12648

Decision sciences: The journal for the American Institute for Decision Sciences

ISSN：0011-7315

年,卷(期)：2024.55(6)

参考文献量71