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The extention rank ordering criteria weighting methods in fuzzy enviroment

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  • Ewa Roszkowska

Abstract

Weight elicitation is an important part of multi-criteria decision analysis. In real-life decisionmaking problems precise information is seldom available, and providing weights is often cognitively demanding as well as very time- and effort-consuming. The judgment of decision-makers (DMs) depends on their knowledge, skills, experience, personality, and available information. One of the weights determination approaches is ranking the criteria and converting the resulting ranking into numerical values. The best known and most widely used are rank sum, rank reciprocal and centroid weights techniques. The goal of this paper is to extend rank ordering criteria weighting methods for imprecise data, especially fuzzy data. Since human judgments, including preferences, are often vague and cannot be expressed by exact numerical values, the application of fuzzy concepts in elicitation weights is deemed relevant. The methods built on the ideas of rank order techniques take into account imprecise information about rank. The fuzzy rank sum, fuzzy rank reciprocal, and fuzzy centroid weights techniques are proposed. The weights obtained for each criterion are triangular fuzzy numbers. The proposed fuzzy rank ordering criteria weighting methods can be easily implemented into decision support systems. Numerical examples are provided to illustrate the practicality and validity of the proposed methods.

Suggested Citation

  • Ewa Roszkowska, 2020. "The extention rank ordering criteria weighting methods in fuzzy enviroment," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 30(2), pages 91-114.
  • Handle: RePEc:wut:journl:v:2:y:2020:p:91-114:id:1486
    DOI: 10.37190/ord200206
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