Multiattribute decision making is an important part of the decision process for both individual and group problems. We incorporate the fuzzy set theory and the basic nature of subjectivity due to ambiguity to achieve a flexible decision approach suitable for uncertain and fuzzy environments. Let us consider the analytic hierarchy process (AHP) in which the labels are structured as fuzzy numbers...

Axiomatic Foundations for Nonadditive Multiattribute Portfolio Utility Functions

Interval-valued hesitant fuzzy sets (IVHFS), as a kind of decision information presenting tool which is more complicated and scientific elastic, have an important practical value in multiattribute decision-making. There little research on the uncertainty IVHFS. The existing measure cannot distinguish different IVHFS some contexts. In my opinion, for IVHFS, there should exist two types uncertain...

Decision support based upon risk analysis into comparison of the electricity generation from different renewable energy technologies can provide information about their effects on the environment and society. The aim of this paper is to develop the assessment framework regarding risks to health and environment, and the society’s benefits of the electric power plant generation from different ren...

The aim of this paper is to develop a linear programming technique for multidimensional analysis of preferences in multiattribute group decision making under fuzzy environments. Fuzziness is inherent in decision data and group decision making processes, and linguistic variables are well suited to assessing an alternative on qualitative attributes using fuzzy ratings. A crisp decision matrix can...

Based on the additive multi-attribute value model for multiple attribute decision making (MADM) problems, this paper investigates how the set of attribute weights (or weight-set thereafter) is determined according to preference orders of alternatives given by decision makers. The weight-set is a bounded convex polyhedron and can be written as a convex combination of the extreme points. We give ...