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We provide an overview of two select topics in Monte Carlo simulationbased methods for stochastic optimization: problems with stochastic constraints and variance reduction techniques. While Monte Carlo simulation-based methods have been successfully used for stochastic optimization problems with deterministic constraints, there is a growing body of work on its use for problems with stochastic constraints. The presence of stochastic constraints brings new challenges in ensuring and testingdoi:10.1007/978-1-4939-1384-8_9 fatcat:4exjfdng65b7pdywahf7wqu5zm