Chance-constrained programming with fuzzy stochastic coefficients

International audienceWe consider fuzzy stochastic programming problems with a crisp objective function and linear constraints whose coefficients are fuzzy random variables, in particular of type L-R. To solve this type of problems, we formulate deterministic counterparts of chance-constrained programming with fuzzy stochastic coefficients, by combining constraints on probability of satisfying constraints, as well as their possibility and necessity. We discuss the possible indices for comparing fuzzy quantities by putting together interval orders and statistical preference. We study the convexity of the set of feasible solutions under various assumptions. We also consider the case where fuzzy intervals are viewed as consonant random intervals. The particular cases of type L-R fuzzy Gaussian and discrete random variables are detailed

An extension of stochastic dominance to fuzzy random variables

International audienceThis paper proposes a joint extension of interval comparison and random variable comparison methods to the ranking of fuzzy random variables. First, an extension of stochastic dominance to random intervals is proposed. It enables to retrieve some previous ranking methods for belief functions and for fuzzy intervals. On this basis, a direct extension of stochastic dominance to fuzzy random variables is proposed. This approach is just one among various possibilities obtained by combining fuzzy interval and random variable comparison methods