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DDC: 510 × Subject: stochastic programming ×

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Now showing 1 - 2 of 2
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    Dynamic probabilistic constraints under continuous random distributions
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2020) González Grandón, Tatiana; Henrion, René; Pérez-Aros, Pedro
    The paper investigates analytical properties of dynamic probabilistic constraints (chance constraints). The underlying random distribution is supposed to be continuous. In the first part, a general multistage model with decision rules depending on past observations of the random process is analyzed. Basic properties like (weak sequential) (semi-) continuity of the probability function or existence of solutions are studied. It turns out that the results differ significantly according to whether decision rules are embedded into Lebesgue or Sobolev spaces. In the second part, the simplest meaningful two-stage model with decision rules from L 2 is investigated. More specific properties like Lipschitz continuity and differentiability of the probability function are considered. Explicitly verifiable conditions for these properties are provided along with explicit gradient formulae in the Gaussian case. The application of such formulae in the context of necessary optimality conditions is discussed and a concrete identification of solutions presented.
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    Structural properties of linear probabilistic constraints
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2006) Henrion, Rene
    The paper provides a structural analysis of the feasible set defined by linear probabilistic constraints. Emphasis is laid on single (individual) probabilistic constraints. A classical convexity result by Van de Panne/Popp and Kataoka is extended to a broader class of distributions and to more general functions of the decision vector. The range of probability levels for which convexity can be expected is exactly identified. Apart from convexity, also nontriviality and compactness of thefeasible set are precisely characterized at the same time. The relation between feasible sets with negative and nonnegative right-hand side is revealed. Finally, an existence result is formulated for the more difficult case of joint probabilistic constraints.