A tutorial overview of optimization via discrete-event simulation

  • Michael C. Fu
Simulation And Perturbation Analysis
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 199)


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. F. Azadivar and J.J. Talavage, Optimization of stochastic simulation-models, Mathematics and Computers in Simulation 22 (1980) 231–241.CrossRefGoogle Scholar
  2. E. J. Dudewicz and S. R. Dalal, Allocation of measurements in ranking and selection with unequal variances, Sankhya B37 (1975) 28–78.Google Scholar
  3. M. C. Fu, Sample path derivatives for (s, S) inventory systems, to appear in Operations Research 42, No.2 (1994a).Google Scholar
  4. M. C. Fu, Optimization via simulation: a review, to appear in Annals of Operations Research (1994b).Google Scholar
  5. M. C. Fu and K. Healy, Simulation optimization of (s,S) inventory systems, Proceedings of the Winter Simulation Conference (1992) 506–514.Google Scholar
  6. P. Glasserman, Gradient Estimation Via Perturbation Analysis, Kluwer (1991).Google Scholar
  7. K. Healy and L. W. Schruben, Retrospective simulation response optimization, Proceedings of the 1991 Winter Simulation Conference (1991) 901–906.Google Scholar
  8. Y. C. Ho and X. R. Cao, Discrete Event Dynamic Systems and Perturbation Analysis, Kluwer Academic (1991).Google Scholar
  9. Y. C. Ho, L. Shi, L. Dai and W. B. Gong, Optimizing discrete event systems via the gradient surface method, Discrete-Event Dynamic Systems 2 (1992) 99–120.CrossRefGoogle Scholar
  10. Y. C. Ho, R. Sreenevas and P. Vakili, Ordinal optimization of DEDS, Discrete-Event Dynamic Systems: Theory and Applications 2 (1992) 61–88.CrossRefGoogle Scholar
  11. Y. Hochberg and A. C. Tamhane, Multiple Comparison Procedures, Wiley (1987).Google Scholar
  12. J. C. Hsu and B.L. Nelson, Optimization over a finite number of system designs with one-stage sampling and multiple comparisons with the best, Proceedings of the Winter Simulation Conference (1988) 451–457.Google Scholar
  13. S. H. Jacobson and L. W. Schruben, A review of techniques for simulation optimization, Operations Research Letters 8 (1989) 1–9.CrossRefGoogle Scholar
  14. H. J. Kushner and D. C. Clark, Stochastic Approximation Methods for Constrained and Unconstrained Systems, Springer-Verlag, New York (1978).Google Scholar
  15. P. L'Ecuyer, N. Giroux, N., and P. W. Glynn, Stochastic optimization by simulation: numerical experiments with a simple queue in steady-state, to appear in Management Science (1994).Google Scholar
  16. R. Y. Rubinstein, How to optimize discrete-event systems from a single sample path by the score function method, Annals of Oper. Res. 27 (1991) 175–212.CrossRefGoogle Scholar
  17. R. Y. Rubinstein and A. Shapiro, Discrete Event Systems: Sensitivity Analysis and Stochastic Optimization by the Score Function Method, Wiley (1993).Google Scholar
  18. J. C. Spall, Multivariate stochastic approximation using a simultaneous perturbation gradient approximation, IEEE Trans. on Aut. Con. 37 (1992) 332–341.CrossRefGoogle Scholar
  19. R. Suri and M. Zazanis, Perturbation analysis gives strongly consistent sensitivity estimates for the M/G/1 queue, Management Science 34 (1988) 39–64.Google Scholar
  20. P. Vakili, Using a standard clock technique for efficient simulation, Operations Research Letters (1991) 445–452.Google Scholar
  21. W.N. Yang and B.L. Nelson, Using common random numbers and control variates in multiple-comparison procedures, Operations Research, 39 (1991) 583–591.Google Scholar

Copyright information

© Springer-Verlag London Limited 1994

Authors and Affiliations

  • Michael C. Fu
    • 1
  1. 1.University of MarylandCollege ParkUSA

Personalised recommendations