Dynamic Intuitionistic Fuzzy Multi-Attribute Decision Making

  • Zeshui Xu
  • Xiaoqiang Cai
Chapter

Abstract

In the previous chapters, we have discussed the problems where all the intuitionstic fuzzy data are collected in the same time period or at the same stage. However, in many practical problems, such as multi-period investment decision making, medical diagnosis, personnel dynamic examination, and military system efficiency dynamic evaluation, the decision information is usually collected at different periods of time. Recently, Xu and Yager (2008) investigate aggregation techniques for dynamic intuitionistic fuzzy information, develop methods for weighting time series, and propose an approach to dynamic intuitionistic fuzzy multi-attribute decision making. They also extend the derived results to uncertain dynamic intuitionistic fuzzy environments.

This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Sadiq R, Tesfamariam S. 2007. Probability density functions based weights for ordered weighted averaging (OWA) operators: an example of water quality indices. European Journal of Operational Research, 182: 1350–1368.Google Scholar
  2. Xu Z S, Yager R R. 2008. Dynamic intuitionistic fuzzy multiple attribute decision making. International Journal of Approximate Reasoning, 48: 246–262.Google Scholar
  3. Xu Z S. 2005a. An overview of methods for determining OWA weights. International Journal of Intelligent Systems, 20: 843–865.Google Scholar
  4. Xu Z S. 2007d. Binomial distribution based approach to deriving time series weights. The IEEE International Conference on Industrial Engineering and Engineering Management, December 2–5, Singapore: 154–158.Google Scholar
  5. Xu Z S. 2008c. On multi-period multi-attribute decision making. Knowledge-Based Systems, 21: 164–171.Google Scholar
  6. Xu Z S. 2011. Approaches to multi-stage multi-attribute group decision making. International Journal of Information Technology & Decision Making, 10: 121–146.Google Scholar
  7. Yager R R. 2008. Time series smoothing and OWA aggregation. IEEE Transactions on Fuzzy Systems, 16: 994–1007.Google Scholar

Copyright information

© Science Press Beijing and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Zeshui Xu
    • 1
  • Xiaoqiang Cai
    • 2
  1. 1.Institute of SciencesPLA University of Science and TechnologyNanjing, JiangsuP.R. China
  2. 2.Department of Systems Engineering and Engineering ManagementThe Chinese University of Hong KongShatin, N.T.Hong Kong

Personalised recommendations