Rapid screening algorithms for stochastically constrained problems

A simulation optimization framework containing three fundamental stages (feasibility check, screening, and selection) is proposed for solving the zero-one optimization via simulation problem in the presence of a single stochastic constraint. We present three rapid screening algorithms that combine these three stages in different manners, such that various sampling mechanisms are applied, therefore yielding different statistical guarantees. An empirical evaluation for the efficiency comparison between the proposed algorithms and other existing works is provided.