Dynamic fuzzy OWA model for group multiple criteria decision making

J. R. Chang*, T. H. Ho, C. H. Cheng, An-Pin Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

Obtaining relative weights in MCDM problems is a very important issue. The Ordered Weighted Averaging (OWA) aggregation operators have been extensively adopted to assign the relative weights of numerous criteria. However, previous aggregation operators (including OWA) are independent of aggregation situations. To solve the problem, this study proposes a new aggregation model - dynamic fuzzy OWA based on situation model, which can modify the associated dynamic weight based on the aggregation situation and can work like a "magnifying lens" to enlarge the most important attribute dependent on minimal information, or can obtain equal attribute weights based on maximal information. Two examples are adopted in this paper for comparison and showing the effects under different weights.

Original languageEnglish
Pages (from-to)543-554
Number of pages12
JournalSoft Computing
Volume10
Issue number7
DOIs
StatePublished - 1 May 2006

Keywords

  • Dynamic fuzzy OWA model
  • Fuzzy multiple criteria decision making (FMCDM)
  • Linguistic variable
  • Ordered weighted averaging (OWA)

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