Random number generators: good ones are hard to find
Communications of the ACM
Journal of Optimization Theory and Applications
Random number generation and quasi-Monte Carlo methods
Random number generation and quasi-Monte Carlo methods
SIAM Journal on Control and Optimization
Stochastic approximation with two time scales
Systems & Control Letters
A one-measurement form of simultaneous perturbation stochastic approximation
Automatica (Journal of IFAC)
Optimal structured feedback policies for ABR flow control using two-timescale SPSA
IEEE/ACM Transactions on Networking (TON)
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
ACM Transactions on Modeling and Computer Simulation (TOMACS)
SPSA algorithms with measurement reuse
Proceedings of the 38th conference on Winter simulation
STEWARD: demo of spatio-textual extraction on the web aiding the retrieval of documents
dg.o '07 Proceedings of the 8th annual international conference on Digital government research: bridging disciplines & domains
Adaptive Newton-based multivariate smoothed functional algorithms for simulation optimization
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Brief paper: New algorithms of the Q-learning type
Automatica (Journal of IFAC)
A probabilistic constrained nonlinear optimization framework to optimize RED parameters
Performance Evaluation
Brief paper: An adaptive optimization scheme with satisfactory transient performance
Automatica (Journal of IFAC)
A proof of convergence of the B-RED and P-RED algorithms for random early detection
IEEE Communications Letters
An efficient and optimized bluetooth scheduling algorithm for piconets
ICDCIT'07 Proceedings of the 4th international conference on Distributed computing and internet technology
An optimal weighted-average congestion based pricing scheme for enhanced QoS
ICDCIT'07 Proceedings of the 4th international conference on Distributed computing and internet technology
Optimal multi-layered congestion based pricing schemes for enhanced QoS
Computer Networks: The International Journal of Computer and Telecommunications Networking
Stochastic optimization for adaptive labor staffing in service systems
ICSOC'11 Proceedings of the 9th international conference on Service-Oriented Computing
Actor-critic algorithms for hierarchical Markov decision processes
Automatica (Journal of IFAC)
Hi-index | 0.01 |
Simultaneous perturbation stochastic approximation (SPSA) algorithms have been found to be very effective for high-dimensional simulation optimization problems. The main idea is to estimate the gradient using simulation output performance measures at only two settings of the N-dimensional parameter vector being optimized rather than at the N + 1 or 2N settings required by the usual one-sided or symmetric difference estimates, respectively. The two settings of the parameter vector are obtained by simultaneously changing the parameter vector in each component direction using random perturbations. In this article, in order to enhance the convergence of these algorithms, we consider deterministic sequences of perturbations for two-timescale SPSA algorithms. Two constructions for the perturbation sequences are considered: complete lexicographical cycles and much shorter sequences based on normalized Hadamard matrices. Recently, one-simulation versions of SPSA have been proposed, and we also investigate these algorithms using deterministic sequences. Rigorous convergence analyses for all proposed algorithms are presented in detail. Extensive numerical experiments on a network of M/G/1 queues with feedback indicate that the deterministic sequence SPSA algorithms perform significantly better than the corresponding randomized algorithms.