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Ranking fuzzy numbers based on ideal solution

Author

Listed:
  • Zhong-xing Wang

    (Guang Xi University)

  • Ya-ni Mo

    (Guang Xi University)

Abstract

In this paper, we consider the factor of the decision maker’s risk preference, and define the left and right deviation degree respectively. Besides, we propose a new formula of the fuzzy degree. Then we get the multiattribute matrix of fuzzy numbers. We rank fuzzy numbers with the help of an ideal solution. Some numerical examples are displayed to illustrate the validity and advantages of the proposed ranking method.

Suggested Citation

  • Zhong-xing Wang & Ya-ni Mo, 2010. "Ranking fuzzy numbers based on ideal solution," Fuzzy Information and Engineering, Springer, vol. 2(1), pages 27-36, March.
    • Handle: RePEc:spr:fuzinf:v:2:y:2010:i:1:d:10.1007_s12543-010-0035-8
    DOI: 10.1007/s12543-010-0035-8
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    Cited by:

    1. P. Phani Bushan Rao & N. Ravi Shankar, 2013. "Ranking fuzzy numbers with an area method using circumcenter of centroids," Fuzzy Information and Engineering, Springer, vol. 5(1), pages 3-18, March.
    2. Yin-Yin Huang & I-Fei Chen & Chien-Liang Chiu & Ruey-Chyn Tsaur, 2021. "Adjustable Security Proportions in the Fuzzy Portfolio Selection under Guaranteed Return Rates," Mathematics, MDPI, vol. 9(23), pages 1-18, November.

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