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Convexity of chance constraints with independent random variables

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Abstract

We investigate the convexity of chance constraints with independent random variables. It will be shown, how concavity properties of the mapping related to the decision vector have to be combined with a suitable property of decrease for the marginal densities in order to arrive at convexity of the feasible set for large enough probability levels. It turns out that the required decrease can be verified for most prominent density functions. The results are applied then, to derive convexity of linear chance constraints with normally distributed stochastic coefficients when assuming independence of the rows of the coefficient matrix.

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Authors and Affiliations

  1. Weierstrass Institute Berlin, Mohrenstr. 39, Berlin, 10117, Germany

    René Henrion

  2. EDF R&D, 1 avenue du Général de Gaulle, 92141, Clamart, France

    Cyrille Strugarek

Authors
  1. René Henrion
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  2. Cyrille Strugarek
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Correspondence to René Henrion.

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Henrion, R., Strugarek, C. Convexity of chance constraints with independent random variables. Comput Optim Appl 41, 263–276 (2008). https://doi.org/10.1007/s10589-007-9105-1

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  • DOI: https://doi.org/10.1007/s10589-007-9105-1

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