Handbook of Simulation Optimization

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Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information (2018, background): “…from the perspective of simulation optimization that are in principle available to solve (1) and (2) include response surface methods (internal) (Kleijnen, 2015), stochastic search (internal) (Andradóttir, 2015, Hu, 2015, Zabinsky, 2015) and versions of stochastic approximation (internal) where…”
Exact and Inexact Subsampled Newton Methods for Optimization (2016, background): “Combining Lemma 2.2 and Lemma 2.3, and recalling (2.3), we obtain the following linear-quadratic bound Ek[‖wk+1 − w∗‖] ≤ M 2µ̄ ‖wk − w∗‖2 + σ‖wk − w∗‖ µ̄ √ |Sk| + v µ̄ √ |Xk| .”
Distributionally Robust Optimization: A Review (2019, methodology): “This setup represents a broad range of problems in statistics, optimization, and control, such as regression and classification models [106, 163], simulation-optimization [107, 227], stochastic optimal control [31], Markov decision processes [246], and stochastic programming [45, 295].”