Decision making under uncertainty in environmental projects using mathematical simulation modeling

Decision Making Under Uncertainty Using Mathematical Optimization: A Survey

Quantitative optimization techniques have proven to be a powerful tool in tackling complicated decision-making problems in various application domains. Scheduling workforces, pricing airline tickets, managing production systems and designing engineering projects are just a small sample of the myriad industrial applications that have benefited from optimization techniques such as linear, nonline...

Modeling Decision Making under Uncertainty and Vagueness

This paper discuss mainly issues related for modeling decision making under uncertain, vagueness, risky and imprecise information. There will be presented a description of five ordinal methods for modeling decision making under uncertainty in the context of linguistic data: Possibilistic Decisisonmaking, Revised Possibilistic Decisisonmaking, Commensurate L-Fuzzy Risk Minimization, Fuzzy relati...

Decision making under uncertainty

Decision making under uncertainty

1 Laboratory of Computational Neuroscience, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland 2 Laboratoire de Recherché en Neuroimagerie, Le Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland 3 Information Processing and Economic Decision Making, Department of Psychology, Universität Konstanz, Konstanz, Germany 4 Economic Psychology, Department of Psychology, Univers...

Decision making under uncertainty using imprecise probabilities

Various ways for decision making with imprecise probabilities—admissibility, maximal expected utility, maximality, E-admissibility, Γ-maximax, Γ-maximin, all of which are well-known from the literature—are discussed and compared. We generalize a well-known sufficient condition for existence of optimal decisions. A simple numerical example shows how these criteria can work in practice, and demon...