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Deriving priority weights from intuitionistic multiplicative preference relations under group decision-making settings

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  • Zhen Zhang

    (Dalian University of Technology)

  • Chonghui Guo

    (Dalian University of Technology)

Abstract

The intuitionistic multiplicative preference relation (IMPR), which takes into account both the ratio degree to which an alternative is preferred to another and the ratio degree to which an alternative is non-preferred to another, is a useful tool for decision makers to elicit their preference information using Saaty’s 1–9 scale. In this paper, we focus on group decision making with IMPRs. First, we analyze the flaws of the consistency definition of an IMPR in previous work and then propose a new definition to overcome the flaws. On this basis, a linear programming-based algorithm is developed to check and improve the consistency of an IMPR. Second, we discuss the relationships between an IMPR and a normalized intuitionistic multiplicative weight vector and develop two approaches to group decision making based on complete and incomplete IMPRs, respectively. Based on the proposed algorithm and approaches, a general framework for group decision making with IMPRs is proposed. Finally, some numerical examples are provided to demonstrate the proposed approaches. The results show that the proposed approaches can deal with group decision-making problems with IMPRs effectively.

Suggested Citation

  • Zhen Zhang & Chonghui Guo, 2017. "Deriving priority weights from intuitionistic multiplicative preference relations under group decision-making settings," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(12), pages 1582-1599, December.
    • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:12:d:10.1057_s41274-016-0171-6
    DOI: 10.1057/s41274-016-0171-6
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    References listed on IDEAS

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    2. Xia Liu & Yejun Xu & Yao Ge & Weike Zhang & Francisco Herrera, 2019. "A Group Decision Making Approach Considering Self-Confidence Behaviors and Its Application in Environmental Pollution Emergency Management," IJERPH, MDPI, vol. 16(3), pages 1-15, January.

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