TY - GEN
T1 - Simulation Optimization and Stochastic Gradients
T2 - 2025 Winter Simulation Conference, WSC 2025
AU - Fu, Michael C.
AU - Hu, Jiaqiao
AU - Ryzhov, Ilya O.
AU - Zhou, Enlu
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This tutorial addresses the use of stochastic gradients in simulation optimization, including methodology and algorithms, theoretical convergence analysis, and applications. Specific topics include stochastic gradient estimation techniques - both direct unbiased and indirect finite-difference-based; stochastic approximation algorithms and their convergence rates; stochastic gradient descent (SGD) algorithms with momentum and reusing past samples via importance sampling; and a real-world application in geographical partitioning.
AB - This tutorial addresses the use of stochastic gradients in simulation optimization, including methodology and algorithms, theoretical convergence analysis, and applications. Specific topics include stochastic gradient estimation techniques - both direct unbiased and indirect finite-difference-based; stochastic approximation algorithms and their convergence rates; stochastic gradient descent (SGD) algorithms with momentum and reusing past samples via importance sampling; and a real-world application in geographical partitioning.
UR - https://www.scopus.com/pages/publications/105033153487
U2 - 10.1109/WSC68292.2025.11338889
DO - 10.1109/WSC68292.2025.11338889
M3 - Conference contribution
AN - SCOPUS:105033153487
T3 - Proceedings - Winter Simulation Conference
SP - 28
EP - 42
BT - 2025 Winter Simulation Conference, WSC 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 7 December 2025 through 10 December 2025
ER -