 A Rough Programming Model Based on the Greatest Compatible Classes and Synthesis EffectFachao Li, Chenxia Jin, Ying Jing, Marzena Wilamowska‐Korsak and Zhuming Bi Systems Research and Behavioral Science, 2013, vol. 30, issue 3, 229-243 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. Date: 2013 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:srbeha:v:30:y:2013:i:3:p:229-243 Ordering information: This journal article can be ordered from Access Statistics for this article More articles in Systems Research and Behavioral Science from Wiley Blackwell |
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