Models for hesitant interval-valued fuzzy multiple attribute decision making based on the correlation coefficient with incomplete weight information

  • Authors:

  • Guiwu Wei;Xiaofei Zhao;Rui Lin;Hongjun Wang

  • Affiliations:

  • Institute of Decision Sciences, Chongqing University of Arts and Sciences, Yongchuan, China;Institute of Decision Sciences, Chongqing University of Arts and Sciences, Yongchuan, China;Institute of Decision Sciences, Chongqing University of Arts and Sciences, Yongchuan, China;Institute of Decision Sciences, Chongqing University of Arts and Sciences, Yongchuan, China

  • Venue:
  • Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
  • Year:
  • 2014

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Abstract

In this paper, we investigate the multiple attribute decision making problems with hesitant interval-valued fuzzy information, in which the information about attribute weights is incompletely known, and the attribute values take the form of hesitant interval-valued fuzzy values. We first introduce some approaches to obtaining the weight information of attributes, and then establish an optimization model based on the positive ideal point of attribute values, by which the attribute weights can be determined. For the special situations where the information about attribute weights is completely unknown, we establish another optimization model. By solving this model, we get a simple and exact formula, which can be used to determine the attribute weights. We compute the correlation coefficient between each alternative and positive ideal alternative, and then rank the alternatives by means of the correlation coefficient between each alternative and positive ideal alternative. Finally, we shall present a numerical example to show potential evaluation of emerging technology commercialization with hesitant interval-valued fuzzy information in order to illustrate the method proposed in this paper.