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A Novel MADM Approach Based on Fuzzy Cross Entropy with Interval-Valued Intuitionistic Fuzzy Sets

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  • Xin Tong
  • Liying Yu

Abstract

The paper presents a novel multiple attribute decision-making (MADM) approach for the problem with completely unknown attribute weights in the framework of interval-valued intuitionistic fuzzy sets (IVIFS). First, the fuzzy cross entropy and discrimination degree of IVIFS are defied. Subsequently, based on the discrimination degree of IVIFS, a nonlinear programming model to minimize the total deviation of discrimination degrees between alternatives and the positive ideal solution PIS as well as the negative ideal solution (NIS) is constructed to obtain the attribute weights and, then, the weighted discrimination degree. Finally, all the alternatives are ranked according to the relative closeness coefficients using the extended TOPSIS method, and the most desirable alternative is chosen. The proposed approach extends the research method of MADM based on the IVIF cross entropy. Finally, we illustrate the feasibility and validity of the proposed method by two examples.

Suggested Citation

  • Xin Tong & Liying Yu, 2015. "A Novel MADM Approach Based on Fuzzy Cross Entropy with Interval-Valued Intuitionistic Fuzzy Sets," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-9, February.
    • Handle: RePEc:hin:jnlmpe:965040
    DOI: 10.1155/2015/965040
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    Cited by:

    1. Melda Kokoç & Süleyman Ersöz, 2021. "A literature review of interval-valued intuitionistic fuzzy multi-criteria decision-making methodologies," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(4), pages 89-116.

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