Two new approaches for assessing the weights of fuzzy opinions in group decision analysis

  • Authors:

  • Ying-Ming Wang;Celik Parkan

  • Affiliations:

  • School of Public Administration, Fuzhou University, Fuzhou 350002, PR China and Center for Accounting Studies of Xiamen University, Xiamen, Fujian 361005, PR China;Department of Management, C.W. Post Campus, Long Island University, 720 Northern Blvd., Brookville, NY 11548, USA

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2006

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Abstract

The aggregation of fuzzy opinions is an important component of group decision analysis with fuzzy information. This paper proposes two new approaches for the assessment of the weights to be associated with fuzzy opinions. These approaches involve, respectively, the minimization of the sum of squared distances from one weighted fuzzy opinion to another, which is called the least squares distance method (LSDM), and the minimization of the sum of squared differences between the defuzzified values of any two weighted fuzzy opinions, which is called the defuzzification-based least squares method (DLSM). The two approaches are developed and numerical examples are presented to illustrate their simplicity and effectiveness in aggregating fuzzy opinions.