Dynamic risk management in petroleum project investment based on a variable precision rough set model

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

34 Scopus Citations
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Author(s)

  • Gang Xie
  • Wuyi Yue
  • Shouyang Wang
  • Kin Keung Lai

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)891-901
Journal / PublicationTechnological Forecasting and Social Change
Volume77
Issue number6
Publication statusPublished - Jul 2010

Abstract

In this paper, an adaptive algorithm is designed for dynamic risk management in petroleum project investment based on a variable precision rough set (VPRS) model. In risk management, at each stage of decision-making, experts are invited to identify risk indices and support the decision-maker in evaluating the risk exposure (RE) of individual projects. The VPRS model is used to mine risk rules and determine the significance of risk indices from RE decision tables. Considering that there are multiple risks involved in any petroleum project investment, we use multi-objective programming to obtain the optimal selection of projects with minimum RE, where the significance of risk indices is assigned to each of the corresponding multi-objective functions as a weight. Moreover, we develop a risk ranking model to measure the degree of risk for individual projects in a portfolio. Finally, a numerical example based on a Chinese petroleum company's investments in overseas projects is presented to illustrate the proposed approach, and then conclusions are drawn. © 2010 Elsevier Inc.

Research Area(s)

  • Dynamic risk management, Multi-objective programming, Petroleum, Variable precision rough set