An Efficient Decomposition Algorithm for Static, Stochastic, Linear and Mixed-Integer Linear Programs with Conditional-Value-at-Risk Constraints
We present an efficient decomposition algorithm for single-stage, stochastic linear programs, where conditional value at risk (CVaR) appears as a risk measure in multiple constraints. It starts with a well-known nonlinear, convex reformulation of conditional value at risk constraints, and establishes the connection to a combinatorially large polyhedral representation of the convex feasible set induced … Read more