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Relative Similarity Programming Model for Uncertain Multiple Attribute Decision-Making Objects and Its Application

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  • Zhili Huang
  • Qinglan Chen
  • Liu Chen
  • Qinyuan Liu

Abstract

This paper is concerned with the uncertain multiattribute decision-making (UMADM) of which the attribute value is triangular fuzzy number. Firstly, the max-relative similarity degree and min-relative similarity degree of alternative decision-making objects are given based on the relative similarity degree of triangular fuzzy number, the advantage relation theories to comparative relative similarity degree of triangular fuzzy number are proposed, and some good properties, relations, and conclusions are derived. Secondly, in order to determine the attribute weight vector, a triangular fuzzy number-based decision-making object relative similarity programming model is established with the help of maximizing possibility degree algorithm rules in the cooperative game theory. Subsequently, by aggregating the comparison overall relative similarity degree values of all decision-making objects, we could pick over and sort the set of alternative objects and gather a new model algorithm for the relative similarity programming of triangular fuzzy number-based multiple attribute decision-making alternatives. Finally, an example is given to illustrate the feasibility and practicability of the model algorithm presented in this paper.

Suggested Citation

  • Zhili Huang & Qinglan Chen & Liu Chen & Qinyuan Liu, 2021. "Relative Similarity Programming Model for Uncertain Multiple Attribute Decision-Making Objects and Its Application," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-16, March.
  • Handle: RePEc:hin:jnlmpe:6618333
    DOI: 10.1155/2021/6618333
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