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On the Effectiveness of Common Random Numbers

Author

Listed:
  • R. D. Wright

    (National Defense University)

  • T. E. Ramsay, Jr.

    (Georgia Institute of Technology)

Abstract

The common random number (CRN) simulation technique is a variance reduction method in which policy alternatives are tested against the same random input streams. The CRN literature suggests that positively correlated input streams will generate positively correlated policy responses and, therefore, that the variance of CRN estimators of response differences will be smaller than the variance of independent sample estimators. This paper reports simulation experiments with a typical inventory model for which the CRN technique induces negative correlation and thus augments variance. The experiments also show that CRN designs which assign separate random streams to each stochastic input and hold all streams common across policy tests usually, but not necessarily, yield maximum variance reduction.

Suggested Citation

  • R. D. Wright & T. E. Ramsay, Jr., 1979. "On the Effectiveness of Common Random Numbers," Management Science, INFORMS, vol. 25(7), pages 649-656, July.
    • Handle: RePEc:inm:ormnsc:v:25:y:1979:i:7:p:649-656
    DOI: 10.1287/mnsc.25.7.649
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    Citations

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    Cited by:

    1. Dag Kolsrud, 2008. "Stochastic Ceteris Paribus Simulations," Computational Economics, Springer;Society for Computational Economics, vol. 31(1), pages 21-43, February.
    2. Gal, S. & Rubinstein, R.Y. & Ziv, A., 1984. "On the optimality and efficiency of common random numbers," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 26(6), pages 502-512.
    3. Potter, Andrew & Yang, Biao & Lalwani, Chandra, 2007. "A simulation study of despatch bay performance in the steel processing industry," European Journal of Operational Research, Elsevier, vol. 179(2), pages 567-578, June.
    4. Joshi, Shirish & Tew, Jeffrey D., 1995. "Validation and statistical analysis procedures under the common random number correlation-induction strategy for multipopulation simulation experiments," European Journal of Operational Research, Elsevier, vol. 85(1), pages 205-220, August.
    5. Safizadeh, M. Hossein, 2002. "Minimizing the bias and variance of the gradient estimate in RSM simulation studies," European Journal of Operational Research, Elsevier, vol. 136(1), pages 121-135, January.

    More about this item

    Keywords

    simulation; random numbers;

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