Characterization of aggregate fuzzy membership functions using Saaty's eigenvalue approach

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18 Scopus citations


This paper describes and extends Saaty's eigenvalue approach to fuzzy membership determination. A genetic algorithm-based procedure is adopted to minimize the failure rates in fuzzy membership determination using Saaty's eigenvalue approach. The proposed method is then extended to develop an aggregate fuzzy membership function using multiple decision-maker environment. A theoretical framework for understanding the magnitude of failures with the increase in the cardinality of fuzzy sets is provided. Several researchers have shown that characterizing fuzzy memberships functions using the AHP lead to certain failures. We illustrate how a genetic algorithm-based procedure can be used to lower such failures.

Original languageEnglish (US)
Pages (from-to)199-212
Number of pages14
JournalComputers and Operations Research
Issue number2
StatePublished - Feb 2003

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research


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