Preferences and Decisions under Incomplete Knowledge

Nowadays, decision problems are pervaded with incomplete knowledge, i.e., imprecision and/or uncertain information, both in the problem description and in the preferential information. In this volume leading scientists in the field address various theoretical and practical aspects related to the handling of this incompleteness. The problems discussed are taken from multi-objective linear programming, rationality considerations in preference modelling, non-probabilistic utility theory, data fusion, group decision making and multicriteria decision aid. The book is oriented towards researchers, graduate and postgraduate students in decision analysis, fuzzy sets and fuzzy logic, and operations research/management science.

(P,Q,I,J) - Preference Structures.- Multi-Objective Fuzzy Linear Programming: The MOFAC Method.- An Extension of the Axioms of Utility Theory Based on Fuzzy Rationality Measures.- Hybrid Probabilistic-Possibilistic Mixtures and Utility Functions.- Additive Recursive Rules.- Maximizing the Information Obtained from Data Fusion.- Social Choice under Fuzziness: A Perspective.- Fuzzy Extension of the Rough Set Approach to Multicriteria and Multiattribute Sorting.- Behavioral Analysis of Aggregation in Multicriteria Decision Aid.- To be Symmetric or Asymmetric? A Dilemma in Decision Making.- Monotone Functions on Finite Lattices: An Ordinal Approach to Capacities, Belief and Necessity Functions.