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On a class of minimax stochastic programs

Alexander Shapiro (ashapiro***at***isye.gatech.edu)
Shabbir Ahmed (sahmed***at***isye.gatech.edu)

Abstract: For a particular class of minimax stochastic programming models, we show that the problem can be equivalently reformulated into a standard stochastic programming problem. This permits the direct use of standard decomposition and sampling methods developed for stochastic programming. We also show that this class of minimax stochastic programs subsumes a large family of mean-risk stochastic programs where risk is measured in terms of deviations from a quantile.

Keywords: worst case distribution, problem of moments, Lagrangian duality, mean risk stochastic programs, deviation from a quantile

Category 1: Stochastic Programming

Category 2: Robust Optimization

Category 3: Convex and Nonsmooth Optimization

Citation: Technical report, School of Industrial & Systems Engineering, Georgia Institute of Technology

Download: [PDF]

Entry Submitted: 08/12/2003
Entry Accepted: 08/20/2003
Entry Last Modified: 08/12/2003

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