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Multi-objective optimization of crude oil-supply portfolio based on interval prediction data

  • S.I. : Data-Driven OR in Transportation and Logistics
  • Published:
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Abstract

The optimization of crude oil-supply portfolio is a hot research issue in energy security, which is closely related to the implementation of national strategy and development of economy. Forecasting the demand of crude oil is the basis for portfolio optimization. Therefore, this paper innovatively introduces the decomposition hybrid interval prediction method and proposes a multi-objective programming model in order to provide decision-making support for the formulation of crude oil-supply portfolio scheme. Under the constraints of volume, price and risk, the minimum cost and risk of importing crude oil are achieved. Furthermore, by introducing optimization parameters and risk preference factors, and setting different scenarios for numerical simulation, the results show that (1) decomposition hybrid prediction methods perform better than single prediction methods. (2) As the optimization parameter increases, costs and risks are significantly decreased. Decision-makers can set large parameters to achieve significant optimization of the objective function. (3) The total cost of imported crude oil fluctuates sharply, while the total risk decreases with the increase of risk preference factors under the different scenarios. (4) The fluctuation of price and risk adjustment factors will cause the change of oil-supply portfolio optimization scheme.

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Acknowledgements

We gratefully acknowledge the financial support from National Natural Science Foundation of China (Nos. 71771206, 71425002) and President’s Youth Foundation of the Institutes of Science and Development, CAS (No. Y7X111Q01). We wish to express our sincere gratitude to the anonymous referees for their constructive comments on and review of the earlier draft of our paper according to which we have improved the content.

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Authors and Affiliations

  1. Institutes of Science and Development, Chinese Academy of Sciences, No.15, Zhongguancun Beiyitiao Haidian District, Beijing, 100190, China

    Xiaolei Sun, Jun Hao & Jianping Li

  2. School of Public Policy and Management, University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China

    Xiaolei Sun & Jun Hao

  3. School of Economics and Management, University of Chinese Academy of Sciences, N0.80, Zhongguancun East Road Haidian District, Beijing, 100190, China

    Jianping Li

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  1. Xiaolei Sun
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Sun, X., Hao, J. & Li, J. Multi-objective optimization of crude oil-supply portfolio based on interval prediction data. Ann Oper Res 309, 611–639 (2022). https://doi.org/10.1007/s10479-020-03701-w

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