Stochastic Optimization by Simulation: Numerical Experiments with M/M/1 Queue in Steady-State

Abstract

This paper gives numerical illustrations of the behavior of stochastic approximation combined with different derivative estimation techniques, to optimize a steady-state system. It is a companion paper to L'Ecuyer and Glynn (1993), which gives convergence proofs for most of the variants experimented here. The numerical experiments are made with a simple M/ M/1 queue, which while simple, serves to illustrate the basic convergence properties and possible pitfalls of the various techniques. Discrete-event systems, Stochastic approximation, Gradient estimation, Optimization, Steady- state.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1993
Accession Number
ADA271143

Entities

People

  • Nataly Giroux
  • Peter W. Glynn
  • Pierre L'ecuyer

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Computers
  • Convergence
  • Engineering
  • Estimators
  • Industrial Engineering
  • Mathematical Programming
  • Military Research
  • Operations Research
  • Optimization
  • Sequences
  • Simulations
  • Standards
  • Statistics
  • Steady State
  • Symbols

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Operations Research