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Risk integration and optimization of oil-importing maritime system: a multi-objective programming approach

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  • Jianping Li
  • Xiaolei Sun
  • Fei Wang
  • Dengsheng Wu

Abstract

Optimization of oil-imports portfolio has attracted considerable attention from corporate operators as well as government and its strategic planners. This paper proposes a methodology of oil-importing portfolio optimization based on the fundamental process of intelligent knowledge management (IKM). Centering on the maritime system, optimal solutions are derived for different risk scenarios. Specifically, three main steps are involved: formulating a multi-objective programming (MOP) model, integrating the composite risk exposure with domain knowledge, as well as knowledge acquisition on risk scenarios and influence of transportation risk. For illustration, optimization of the maritime structure of China’s oil imports is performed to verify the practicability of the novel methodology. Experimental results suggest that the risk-adjusted factors’ augmentation can spread the risk wider and eventually enhance risk optimization capability in the MOP model. With a given risk-adjusted factor, the influence of transportation risk on an optimal plan is simulated and analyzed. The paper uses the fundamental IKM process for transforming the data (rough knowledge) into intelligent knowledge (transformation from T1 to T2) in the empirical study on risk integration and optimization of oil-importing maritime system. It is helpful to explore hidden patterns. What’s more, results suggest that it is necessary to highlight the influence of transportation risk in order to support decision makers from different domains to obtain more reasonable optimal solutions. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Jianping Li & Xiaolei Sun & Fei Wang & Dengsheng Wu, 2015. "Risk integration and optimization of oil-importing maritime system: a multi-objective programming approach," Annals of Operations Research, Springer, vol. 234(1), pages 57-76, November.
    • Handle: RePEc:spr:annopr:v:234:y:2015:i:1:p:57-76:10.1007/s10479-014-1550-5
    DOI: 10.1007/s10479-014-1550-5
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    3. Lean Yu & Zebin Yang & Ling Tang, 2016. "Prediction-Based Multi-Objective Optimization for Oil Purchasing and Distribution with the NSGA-II Algorithm," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 423-451, March.
    4. Sun, Xiaolei & Liu, Chang & Chen, Xiuwen & Li, Jianping, 2017. "Modeling systemic risk of crude oil imports: Case of China’s global oil supply chain," Energy, Elsevier, vol. 121(C), pages 449-465.

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