Overview of the Handbook.- Discrete Optimization via Simulation.- Ranking and Selection: Efficient Simulation Budget Allocation.- Response Surface Methodology.- Stochastic Gradient Estimation.- An Overview of Stochastic Approximation.- Stochastic Approximation Methods and Their Finite-time Convergence Properties.- A Guide to Sample Average Approximation.- Stochastic Constraints and Variance Reduction Techniques.- A Review of Random Search Methods.- Stochastic Adaptive Search Methods: Theory and Implementation.- Model-Based Stochastic Search Methods.- Solving Markov Decision Processes via Simulation.