Skip to main content

Ordinal optimization of DEDS


In this paper we argue thatordinal rather thancardinal optimization, i.e., concentrating on finding good, better, or best designs rather than on estimating accurately the performance value of these designs, offers a new, efficient, and complementary approach to the performance optimization of systems. Some experimental and analytical evidence is offered to substantiate this claim. The main purpose of the paper is to call attention to a novel and promising approach to system optimization.

This is a preview of subscription content, access via your institution.


  • Bertsekas, D.P. and Tsitsiklis, J.N. 1989.Parallel and Distributed Computation: Numerical Methods. Englewood Cliffs, NJ: Prentice Hall.

    Google Scholar 

  • David, H.A. 1982.Order Statistics, 2nd Ed. New York: Wiley.

    Google Scholar 

  • DeHaan, L. 1981. Estimation of the minimum of function using order statistics.JASA, 76: 467–469.

    Google Scholar 

  • Feller, W. 1968.An Introduction to Probability Theory and Its Applications, 3rd Ed. New York: Wiley.

    Google Scholar 

  • Fujimoto, R.M. 1990. Parallel discrete event simulation.Comm. ACM, 33: 31–53.

    Google Scholar 

  • Glasserman, P. and Yao, D.D. 1989. Monotonicity in generalized semi-Markov processes. submitted.

  • Glynn, P.W. 1986. Optimization of stochastic systems. Proc. 1986 Winter Simulation Conf. 356–365.

  • Goldberg, D.E. 1989.Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Ho, Y.C. and Cao, Xiren. 1991.Perturbation Analysis of Discrete Event Dynamic Systems. Kluwer.

  • Ho, Y.C., Cassandras, C., and Makhlouf, M. 1991. Parallel simulation of real time systems via the standard clock approach. Submitted.

  • Ho, Y.C., Deng, M., and Hu, J.Q. 1992. Correlated estimation noise in discrete event simulation and ordinal optimization. Manuscript in preparation.

  • Jacobsen, S.H. and Schruben, L.W. 1989 Techniques for simulation response optimization.Oper. Res. Lett. 8:

  • Kumar, V. and Gupta, A. 1991. Analyzing scalability of parallel algorithms and architectures.Proc. 1991 Int. Conf. on Supercomputing, Cologne, Germany.

  • Kung, H.T. 1976. The complexity of obtaining starting points for solving operator equations by Newton's method.Analytic Computational Complexity, J. F. Traub (ed)., Academic Press.

  • Law, A.M. and Kelton, W.D. 1990.Simulation Modeling and Analysis. New York: McGraw-Hill.

    Google Scholar 

  • Lirov, Y., Melamed, B. 1990. Expert design systems for telecommunications. To appear.

  • Reiser, M. and Lavenberg, S.S. 1980. Mean value analysis of closed multichain queueing networks.J.A.C.M., 27: 313–322.

    Google Scholar 

  • Righter, R. and Walrand, J.C. 1989. Distributed simulation of discrete event systems.Proc. IEEE, 77: 99–113.

    Google Scholar 

  • Rosenbaum, P.R. 1991 Confident search. Unpublished Manuscript, Department of Statistics, University of Pennsylvania, Philadelphia, PA.

    Google Scholar 

  • Rubinstein, R. 1986.Monte Carlo Optimization, Simulation and Sensitivity of Queueing Networks. New York: Wiley.

    Google Scholar 

  • Rubinstein, R. and Weissman, I. 1977. The Monte Carlo method for global optimization.Cah. Cen Etud. Rech. Oper. 21: 143–149.

    Google Scholar 

  • Traub, J.F. 1976. The introduction toAnalytic Computational Complexity. J.F. Traub (ed.), Academic Press.

  • Vakili, P. 1991. Massively parallel and distributed simulation of a class of discrete event system: a different perspective. Submitted.

  • Vakili, P. 1992. A standard clock technique for efficient simulation. To appear.

Download references

Author information

Authors and Affiliations


Additional information

This work is supported by NSF grants CDR-88-03012, DDM-89-14277, ONR contracts N00014-90-J-1093, N00014-89-J-1023, and army contracts DAAL-03-83-K-0171, DAAL-91-G-0194.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Ho, Y.C., Sreenivas, R.S. & Vakili, P. Ordinal optimization of DEDS. Discrete Event Dyn Syst 2, 61–88 (1992).

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI:

Key Words

  • optimization
  • parallel computation
  • queueing theory