A fuzzy-stochastic OWA model for robust multi-criteria decision making

  • Authors:

  • Mahdi Zarghami;Ferenc Szidarovszky;Reza Ardakanian

  • Affiliations:

  • Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran 51664 and Systems and Industrial Engineering Department, University of Arizona, Tucson, USA 85721-0020;Systems and Industrial Engineering Department, University of Arizona, Tucson, USA 85721-0020;Civil Engineering Department, Sharif University of Technology, Tehran, Iran 11365-9313

  • Venue:
  • Fuzzy Optimization and Decision Making
  • Year:
  • 2008

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Abstract

All realistic Multi-Criteria Decision Making (MCDM) problems face various kinds of uncertainty. Since the evaluations of alternatives with respect to the criteria are uncertain they will be assumed to have stochastic nature. To obtain the uncertain optimism degree of the decision maker fuzzy linguistic quantifiers will be used. Then a new approach for fuzzy-stochastic modeling of MCDM problems will be introduced by merging the stochastic and fuzzy approaches into the OWA operator. The results of the new approach, entitled FSOWA, give the expected value and the variance of the combined goodness measure for each alternative. Robust decision depends on the combined goodness measures of alternatives and also on the variations of these measures under uncertainty. In order to combine these two characteristics a composite goodness measure will be defined. The theoretical results will be illustrated in a watershed management problem. By using this measure will give more sensitive decisions to the stakeholders whose optimism degrees are different than that of the decision maker. FSOWA can be used for robust decision making on the competitive alternatives under uncertainty.