Title :
Optimizing discrete event systems with the simultaneous perturbation stochastic approximation algorithm
Author :
Hill, Stacy D. ; Fu, Michael C.
Author_Institution :
Appl. Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA
Abstract :
Stochastic approximation is one method that has been applied to the optimization of discrete-event systems requiring simulation. We investigate the use of simultaneous perturbation stochastic approximation (SPSA). This technique requires only two simulations per gradient estimate, regardless of the number of parameters of interest. We apply the technique to an open queueing network optimization problem
Keywords :
approximation theory; discrete event systems; optimisation; perturbation techniques; queueing theory; stochastic processes; discrete event systems; gradient estimate; optimization; queueing network; simultaneous perturbation stochastic approximation; Approximation algorithms; Artificial intelligence; Constraint optimization; Discrete event simulation; Discrete event systems; Educational institutions; Finite difference methods; Stability; Stochastic processes; Stochastic systems;
Conference_Titel :
Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
Conference_Location :
Lake Buena Vista, FL
Print_ISBN :
0-7803-1968-0
DOI :
10.1109/CDC.1994.411543
