Fuzzy compromise programming with precedence order in the criteria

  • Authors:

  • G. G. Merino;D. D. Jones;D. L. Clements;D. Miller

  • Affiliations:

  • Department of Agricultural Engineering, University of Concepcion, Chillan, Chile;Department of Biological Systems Engineering, University of Nebraska, 215 L.W. Chase Hall, East Campus, P.O. Box 830726, Lincoln, NE;Department of Biological Systems Engineering, University of Nebraska, 215 L.W. Chase Hall, East Campus, P.O. Box 830726, Lincoln, NE;Department of Biological Systems Engineering, University of Nebraska, 215 L.W. Chase Hall, East Campus, P.O. Box 830726, Lincoln, NE

  • Venue:
  • Applied Mathematics and Computation
  • Year:
  • 2003

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Abstract

This paper provides a new multi-objective decision making (MODM) method. The method was developed by extending two known approaches: "fuzzy composite programming" and "multi-attribute decision making with dominance in the attributes". The method allows the inclusion of a fuzzy representation of uncertainty relative to the information used through the decision making process. In this way the decision-maker is able to incorporate ambiguity and imprecision, which are common to most of the decision problems. The new methodology also addresses the ambiguity surrounding the relative importance of objectives. Thus, in the decision making process the decision-maker is not required to assign specific weights to the objectives to indicate their relative importance. Only a precedence order in the objectives becomes necessary to achieve a ranking in the alternatives. The MODM was applied to assess six management alternatives for the karstic aquifer management problem presented by previous authors. The design alternatives were evaluated against six objectives, which were grouped in three principal criteria: "Environmental", "Economic", and "Water Quality". The method was also evaluated in light of existing methods. It was demonstrated that, as a distance-based method, the new methodology preserves the characteristics of fuzzy composite programming but, at the same time allows the decision-maker flexibility in the assignment of relative importance between objectives.