Title :
Application of descent algorithms with Armijo stepsizes to simulation-based optimization of queueing networks
Author :
Wardi, Y. ; Lee, K.
Author_Institution :
Sch. of Electr. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
Gradient descent algorithms with Armijo stepsizes are adapted to simulation-based optimization of queuing networks. The cost function was evaluated by Monte Carlo simulation, and its gradient was estimated by infinitesimal perturbation analysis. The Armijo stepsize routine requires multiple function evaluations, which are simultaneously performed by finite perturbation analysis (FPA) in one simulation run. Two kinds of FPA estimators are considered: one is precise, but time consuming, and the other is approximate, but faster. Numerical examples show the validity of the proposed algorithm
Keywords :
Monte Carlo methods; optimisation; queueing theory; Armijo stepsizes; Monte Carlo simulation; finite perturbation analysis; gradient descent algorithms; infinitesimal perturbation analysis; queueing networks; simulation-based optimization; Analytical models; Computational modeling; Cost function; Optimization methods; Performance analysis; Performance evaluation; Queueing analysis; Steady-state; Stochastic processes; Testing;
Conference_Titel :
Decision and Control, 1991., Proceedings of the 30th IEEE Conference on
Conference_Location :
Brighton
Print_ISBN :
0-7803-0450-0
DOI :
10.1109/CDC.1991.261265
