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A Rough Programming Model Based on the Greatest Compatible Classes and Synthesis Effect

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  • Fachao Li
  • Chenxia Jin
  • Ying Jing
  • Marzena Wilamowska‐Korsak
  • Zhuming Bi

Abstract

The globalization connects different parts of the world tightly, one region can be closely interacted by another region. The globalized environment can become dynamic and turbulent, thus brings uncertainties into decision making. A critical challenge in system science is to deal with the uncertainties such as fuzziness, randomness and roughness of information. In this paper, a programming model in rough sets is presented. First, the characteristics and limitations of the existing rough programming methods are analysed systematically. Second, the necessity and feasibility of developing a new rough programming model is discussed, and the model is developed on the basis of the greatest compatible classes and synthesis effect. Finally, the effectiveness and characteristics of the newly developed model are validated through a case study. The result illustrates that the new programming model is of significance in practical applications, and it makes it possible to take decision preferences into account of the decision‐making processes effectively. Copyright © 2013 John Wiley & Sons, Ltd.

Suggested Citation

  • Fachao Li & Chenxia Jin & Ying Jing & Marzena Wilamowska‐Korsak & Zhuming Bi, 2013. "A Rough Programming Model Based on the Greatest Compatible Classes and Synthesis Effect," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 229-243, May.
  • Handle: RePEc:bla:srbeha:v:30:y:2013:i:3:p:229-243
    DOI: 10.1002/sres.2175
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    References listed on IDEAS

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    1. Arnab Chakraborty, 2012. "Recognizing Uncertainty and Linked Decisions in Public Participation: A New Framework for Collaborative Urban Planning," Systems Research and Behavioral Science, Wiley Blackwell, vol. 29(2), pages 131-148, March.
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    3. Tay, Francis E. H. & Shen, Lixiang, 2002. "Economic and financial prediction using rough sets model," European Journal of Operational Research, Elsevier, vol. 141(3), pages 641-659, September.
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    Cited by:

    1. Haiqing Yu & Shukuan Zhao & Xiaobo Xu & Yilin Wang, 2014. "An Empirical Study on the Dynamic Relationship between Higher Educational Investment and Economic Growth using VAR Model," Systems Research and Behavioral Science, Wiley Blackwell, vol. 31(3), pages 461-470, May.
    2. Li Da Xu, 2013. "Introduction: Systems Science in Industrial Sectors," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 211-213, May.

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