Fuzzy Assessment of Multiattribute Utility Functions
This paper is concerned with deriving fuzzy multiattribute utility functions (FMUF) based on extensions of the fuzzy set theory. The general procedure of assessing the MUF is composed of three steps; (i) evaluating unidimensional (single-attribute) utility functions (UNIF), (ii) assessing the scaling constants ki, K on them and (iii) obtaining representation forms of the MUFs. The step (i) corresponds to the lowest-level system’s decomposition in which preferential and utility independence among the attributes are assumed. In the step (ii), system’s coordination is executed from the societal point of view and value trade-off experiments among the attributes are performed. The step (iii) is simply concerned with formal representation and calculation of numerical (viz. cardinal) MUFs. This method has shown to be particularly useful for manipulating noncommensurateness and conflict of the multidimensional objective systems. The main limitation of this method is to neglect multiple agent problems. The evaluation is exclusively based on individual preferences of the single decision maker. The method ultimately have some individual assert a set of preference as “socially” desirable. Collective choice or group decision problems are not taken into considerations.
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- Baer, R.M. and Osterby, O. (1969). Algorithms over partially ordered sets, BIT, 9: 97–118.Google Scholar
- Dubois, D. and Prade, H. (1980). Systems of linear fuzzy constraints.Google Scholar
- Fuzzy Sets and Systems, 3:37–48.Google Scholar
- Keeney, R.L. and Raiffa, H. (1976). Decisions with Multiple Objectives, Preferences and Value Tradeoffs. John Wiley, New York.Google Scholar
- Sakawa, M. and Seo, F. (1982). Integrated methodology for computer-aided decision analysis. in T. Robert, F. de P. Hanika and R. Tomlinson (Ed.), Progress in Cybernetics and Systems Research. 10: 333–341.Google Scholar
- Zadeh, L.A. (1965). Fuzzy sets. Information and Control, 8:338–353. Zadeh, L.A. (1971). Similarity relations and fuzzy orderings. Information Sciences, 3: 177–200.Google Scholar