Titlebook: Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty; Roman Slowinski,Jacques Teghem Book 1990

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Multiobjective Stochastic Linear Programming with Incomplete Information: A General Methodologymany real situations, however, parameters of a stochastic nature arise and the analyst is, as a result, confronted with a stochastic multiobjective linear programming problem. Recently, some methods have been developed to deal with this kind of problems; in most of them, the decision maker is suppos

Coronary

Computation of Efficient Solutions of Stochastic Optimization Problems with Applications to Regressi (or loss) arising from the deviation between the output A(.)x of a stochastic linear system x→A(.)x and a desired stochastic target vector b(.) are minimal. Hence, one has the following stochastic linear optimization problem . where u is a convex loss function on IR., (A(.),b(.)) is a random (m,n+1

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Interactive Decision Making for Multiobjective Programming Problems with Fuzzy Parametersameters. On the basis of the .-level sets of the fuzzy numbers, the concept of .-multiobjective programming and (local) M-.-Pareto optimality is introduced. Through the interaction with the decision maker (DM), the fuzzy goals of the DM for each of the objective functions in .-multiobjective program

Ossification

A Possibilistic Approach for Multiobjective Programming Problems. Efficiency of Solutionsore particularly in Multiobjective Programming. Such methods appear without common relation as each of them arises from a particular and suitable set of hypotheses about factors such that the framework of the problem, its nature, decision-maker’s behavior, etc. In this paper we present a general for

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Multiple Objective Linear Programming Problems in the Presence of Fuzzy Coefficientslinear program. Concepts of satisfying solutions based on the bounded rationality principle are introduced, and necessary and sufficient conditions for a potential action to be a satisfying one are established. Efficient methods for singling out satisfying alternatives are also described together wi

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