Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 164, Issue 3, Pages 748-759Publisher
ELSEVIER
DOI: 10.1016/j.ejor.2003.11.028
Keywords
multiple criteria decision making; multiobjective programming; compromise programming; fuzzy number; possibility distribution; expected interval
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Real decision problems usually consider several objectives that have parameters which are often given by the decision maker in an imprecise way. It is possible to handle these kinds of problems through multiple criteria models in terms of possibility theory. Here we propose a method for solving these kinds of models through a fuzzy compromise programming approach. To formulate a fuzzy compromise programming problem from a possibilistic multiobjective linear programming problem the fuzzy ideal solution concept is introduced. This concept is based on soft preference and indifference relationships and on canonical representation of fuzzy numbers by means of their a-cuts. The accuracy between the ideal solution and the objective values is evaluated handling the fuzzy parameters through their expected intervals and a definition of discrepancy between intervals is introduced in our analysis. (C) 2004 Elsevier B.V. All rights reserved.
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