Approximation and contamination bounds for probabilistic programs

Abstract

We explore approximations of stochastic programs with probabilistic constraints by stochastic programs with suitably chosen penalty-type objectives and fixed constraints. Contamination bounds constructed for these substitute problems may be then implemented within the output analysis for the original probabilistic program.

Keywords

• Stochastic programs with probabilistic constraints
• Output analysis
• Contamination technique