Advertisement

A New Approach to Compute Performance Sensitivities of Stochastic Discrete Event Dynamic Systems (DEDS)

  • Hugo Lucca
Conference paper

Abstract

To analyse a complex system, e.g. flexible manufacturing systems (FMS), Hospitals, or Airports, viewed as stochastic discrete event systems (DEDS, e.g. [2],[5],[6]), as close to reality as required, there are some alternatives. For the queueing theory, which has obtained a fair amount of success, no analytical (product-form) solution is yet available, as soon as serious restrictions are involved (e.g. blocking only under given additional restrictions, see [1 ],[5]). Therefore, it is not an appropriate approach for the application to a large category of man-made systems. Thus, one may use, the natural alternative to the exact analysis of an approximated model, which is the approximated analysis of a more exact model, e.g. the Queueing Network Analyser described by Whitt [9]. Finally, experimentation (on a simulation model or the actual system) could be preferred to optimise system performance with respect to given decision parameters. Hence, simulation tools on computers are frequently used, e.g. GASP, SIMULA, or SIMAN, to perform the brute force analysis (e.g. [5], [6]).

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Balsamo, S., and De Nitto-Personé, V.: Closed Queueing Networks with Finite Capacities: Blocking Types, Product-Form Solution and Performance Indices. Performance Evaluation, vol. 12, pp. 85–102, 1991.CrossRefGoogle Scholar
  2. [2]
    Cao, X.R. and Ho, Y.C.: Sensitivity Analysis and Optimization of Throughput in a Production Line with Blocking Models. IEEE Trans. on Autom. Control, Vol. AC-32,No. 11, Nov. 1987.Google Scholar
  3. [3]
    Ho, Y.C., Cao, X. and Cassandras, C.: Infinitesimal and Finite Perturbation Analysis for Queueing Networks. Automatica, vol. 19,no. 4, pp. 439–445, 1983.CrossRefGoogle Scholar
  4. [4]
    Ho, Y.C., Eyler, M.A. and Chien, T.T.: A New Approach to Determine Parameter Sensitivities of Transfer Lines. Management Science, vol. 29,no. 6, pp. 700–714, June 1983.CrossRefGoogle Scholar
  5. [5]
    Ho, Y.C. and Cassandras, C.: A New Approach to the Analysis of Discrete Event Dynamic Systems. Automatica, vol. 19,no. 2, pp. 149–167, 1983.CrossRefGoogle Scholar
  6. [6]
    Ho, Y.C. and Cao, X.: Discrete Event Dynamic Systems: Theory and Applications. Kluwer Academic Publishers, Boston/Dordrecht/London, 1991.Google Scholar
  7. [7]
    Jiang, C.Q., Singh, M.G., and Hindi, K.S.: A New Method of Extended Perturbation Analysis Information and Decision Technologies, vol. 17, pp. 215–226, 1991.Google Scholar
  8. [8]
    Suri, R.: Perturbation Analysis: The State of the Art and Research Issues Explained via the G1/G/1 Queue. Proceedings of the IEEE, vol. 77,no. 1, pp. 114–137, 1989.CrossRefGoogle Scholar
  9. [9]
    Whitt, W.: The Queueing Network Analyzer. The Bell System Technical Journal, vol. 62,no. 9, pp. 2779–2815, November 1983.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Hugo Lucca
    • 1
  1. 1.Institut für Unternehmensforschung (OR)Hochschule St. GallenSt. GallenSwitzerland

Personalised recommendations