Abstract
An attempt to attain a higher human consistency of multiobjective decision making (optimization) models is considered. Basically, as opposed to virtually all conventional approaches which, explicitly or implicitly, seek an optimal option best satisfying all the objectives, which is often counterintuitive and unrealistic, we discuss some nonconventional models in which an optimal option is sought that best satisfies, say, most (or any other linguistic quantifier as almost all, much more than a half, …) of the important objectives. Fuzzy — logic — based calculi of linguistically quantified propositions are employed. Some relations between the above new approach and the recently introduced so — called ordered weighted average (OWA) operators are discussed.
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Kacprzyk, J., Yager, R.R. (1990). Using Fuzzy Logic with Linguistic Quantifiers in Multiobjective Decision Making and Optimization: A Step Towards More Human-Consistent Models. In: Slowinski, R., Teghem, J. (eds) Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty. Theory and Decision Library, vol 6. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-2111-5_17
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DOI: https://doi.org/10.1007/978-94-009-2111-5_17
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