swMATH ID: 11113
Software Authors: Bazovkin P, Mosler K
Description: Stochastic linear programming with a distortion risk constraint. Coherent distortion risk measures are applied to capture the possible violation of a restriction in linear optimization problems whose parameters are uncertain. Each risk constraint induces an uncertainty set of coefficients, which is proved to be a weighted-mean trimmed region. Thus, given a sample of the coefficients, an uncertainty set is a convex polytope that can be exactly calculated. We construct an efficient geometrical algorithm to solve stochastic linear programs that have a single distortion risk constraint. The algorithm is available as an R-package. The algorithm’s asymptotic behavior is also investigated, when the sample is i.i.d. from a general probability distribution. Finally, we present some computational experience.
Homepage: http://www.inside-r.org/packages/cran/StochaTR
Dependencies: R
Related Software: Qhull; R; modQR; ddalpha; CompPD; mrfDepth; depth; depth.plot; moQuantile; OjaNP; DepthProc; fda.usc; geometry; Octave; TukeyRegion; Rglpk; rgl; locfit; UCI-ml; robustbase
Cited in: 7 Publications

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