A two Timescale Stochastic Approximation Scheme for Simulation-Based Parametric Optimization

Shalabh Bhatnagar · Vivek S. Borkar

45 citations0/0 files storedProbability in the Engineering and Informational Sciences

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Simulation Techniques and Applications Markov Chains and Monte Carlo Methods Adaptive Dynamic Programming Control

Abstract

A two timescale stochastic approximation scheme which uses coupled iterations is used for simulation-based parametric optimization as an alternative to traditional “infinitesimal perturbation analysis” schemes. It avoids the aggregation of data present in many other schemes. Its convergence is analyzed, and a queueing example is presented.

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References

2016Simulation and the Monte Carlo Method 1981Simulation and the Monte Carlo Method 1992Multivariate stochastic approximation using a simultaneous perturbation gradient approximation 1978Stochastic Approximation Methods for Constrained and Unconstrained Systems 1997Stochastic approximation with two time scales 1988Perturbation Analysis Gives Strongly Consistent Sensitivity Estimates for the M/G/1 Queue 1994Stochastic Optimization by Simulation: Convergence Proofs for the GI/G/1 Queue in Steady-State 1993Optimization of Queues Using an Infinitesimal Perturbation Analysis-Based Stochastic Algorithm with General Update Times

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1999Stochastic approximation algorithms: Overview and recent trends

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