Stochastic semidefinite programming: a new paradigm for stochastic optimization

摘要

Semidefinite programs are a class of optimization problems that have been studied extensively during the past 15 years. Semidefinite programs are naturally related to linear programs, and both are defined using deterministic data. Stochastic programs were introduced in the 1950s as a paradigm for dealing with uncertainty in data defining linear programs. In this paper, we introduce stochastic Semidefinite programs as a paradigm for dealing with uncertainty in data defining Semidefinite programs.