Unifying Trust-region Algorithms with Adaptive Sampling for Nonconvex Simulation Optimization
Continuous simulation optimization is challenging due to its derivative-free and often nonconvex noisy setting. Trust-region methods have proven remarkable robustness for this class of problems. Each iteration of a trust-region method involves constructing a local model via interpolation or regression within a neighbor...