Ranking and Selection for Steady-State Simulation: Procedures and Perspectives

Published Online:https://doi.org/10.1287/ijoc.14.1.2.7710

References

  • Bechhofer R. E., Santner T.J., Goldsman D.Design and Analysis of Experiments for Statistical Selection, Screening and Multiple Comparisons (1995) (John Wiley, New York) Google Scholar
  • Chien C., Goldsman D., Melamed B. Large-sample results for batch means. Management Science (1997) 43:1288–1295LinkGoogle Scholar
  • Damerdji H. Strong consistency of the variance estimator in steady-state simulation output analysis. Mathematics of Operations Research (1994) 19:494–512LinkGoogle Scholar
  • Damerdji H. Mean-square consistency of the variance estimator in steady-state simulation output analysis. Operations Research (1995) >43:282–291LinkGoogle Scholar
  • Damerdji H., Goldsman D. Consistency of several variants of the standardized time series area variance estimator. Naval Research Logistics (1995) 42:1161–1176CrossrefGoogle Scholar
  • Damerdji H., Nakayama M. K., Charnes J. M., Morrice D. J., Brunner D. T., Swain J. J. Two-stage procedures for multiple comparisons with a control in steady-state simulations. Proceedings of the 1996 Winter Simulation Conference (1996) (Institute of Electrical and Electronics Engineers, Piscataway, NJ) 372–375CrossrefGoogle Scholar
  • Damerdji H., Nakayama M. K. Two-stage multiple-comparison procedures for steady-state simulations. ACM TOMACS (1999) 9:1–30CrossrefGoogle Scholar
  • Dudewicz E. J., Zaino N. A. Allowance for correlation in setting simulation run-length via ranking-and-selection procedures. TIMS Studies in the Management Sciences (1977) 7:51–61Google Scholar
  • Fishman G. S., Yarberry L. S. An implementation of the batch means method. INFORMS Journals on Computing (1997) 9:296–310LinkGoogle Scholar
  • Glynn P. W., Whitt W. Estimating the asymptotic variance with batch means. Operations Research Letters (1991) 10:431–435CrossrefGoogle Scholar
  • Goldsman D., Roberts S., Banks J., Schmeiser B. Ranking and selection in simulation. Proceedings of the 1983 Winter Simulation Conference (1983) (Institute of Electrical and Electronics Engineers, Piscataway, NJ) 387–393Google Scholar
  • Goldsman D., Gantz D., Blais G., Solomon S. Ranking and selection procedures using standardized time series. Proceedings of the 1985 Winter Simulation Conference (1985) (Institute of Electrical and Electronics Engineers, Piscataway, NJ) 120–124CrossrefGoogle Scholar
  • Goldsman D., Kim S.-H., Marshall W. S., Nelson B. L., Joines J., Barton R. R., Fishwick P., Kang K. Ranking and selection for steady-state simulation. Proceedings of the 2000 Winter Simulation Conference (2000) (Institute of Electrical and Electronics Engineers, Piscataway, NJ) 544–553CrossrefGoogle Scholar
  • Goldsman D., Marshall W. S., Farrington P. A., Nembhard H. B., Sturrock D. T., Evans G. W. Selection procedures with standardized time series variance estimators. Proceedings of the 1999 Winter Simulation Conference (1999) (Institute of Electrical and Electronics Engineers, Piscataway, NJ) 382–388CrossrefGoogle Scholar
  • Goldsman D., Meketon M. S., Schruben L. W. Properties of standardized time series weighted area variance estimators. Management Science (1990) 36:602–612LinkGoogle Scholar
  • Goldsman D., Nelson B. L., Banks J. Comparing systems via simulation. Handbook of Simulation (1998) (John Wiley, New York) . Chapter 8CrossrefGoogle Scholar
  • Iglehart D. L. Simulating stable stochastic systems, VII: selecting the best system. TIMS Studies in the Management Sciences (1977) 7:37–49Google Scholar
  • Kim S.-H., Nelson B. L. A fully sequential procedure for indifference-zone selection in simulation. ACM TOMACS (2001a) . in pressCrossrefGoogle Scholar
  • Kim S.-H., Nelson B. L. On the asymptotic validity of fully sequential selection procedures for steady-state simulation. (2001b) . Working Paper, Department of Industrial Engineering & Management Sciences, Northwestern University, Evanston, ILGoogle Scholar
  • Law A. M., Kelton W. D.Simulation Modeling & Analysis (2000) 3rd edition(McGraw-Hill, New York) Google Scholar
  • Meketon M. S., Schmeiser B., Sheppard S., Pooch U., Pedgen D. Overlapping batch means: Something for nothing? Proceedings of the 1984 Winter Simulation Conference (1984) (Institute of Electrical and Electronics Engineers, Piscataway, NJ) 227–230Google Scholar
  • Nakayama M. K., Alexopoulos C., Kang K., Lilegdon W. R., Goldsman D. Selecting the best system in steady-state simulations using batch means. Proceedings of the 1995 Winter Simulation Conference (1995) (Institute of Electrical and Electronics Engineers, Piscataway, NJ) 362–366CrossrefGoogle Scholar
  • Nakayama M. K. Multiple-comparison procedure for steady-state simulations. Annals of Statistics (1997) 25:2433–2450CrossrefGoogle Scholar
  • Rinott Y. On two-stage selection procedures and related probability-inequalities. Comm. Stat.-Thy. and Meth. (1978) A7:799–811CrossrefGoogle Scholar
  • Schmeiser B. W., Song W. T., MacNair E. A., Musselman K. J., Heidelberger P. Inverse-transformation algorithms for some common stochastic processes. Proceedings of the 1989 Winter Simulation Conference (1989) (Institute of Electrical and Electronics Engineers, Piscataway, NJ) 490–496CrossrefGoogle Scholar
  • Schruben L. W. Confidence interval estimation using standardized time series. Operations Research (1983) 31:1090–1108LinkGoogle Scholar
  • Song W. T., Schmeiser B. W. Optimal mean-squared-error batch sizes. Management Science (1995) 41:110–123LinkGoogle Scholar
  • Steiger N. M., Wilson J. R. An improved batch means procedure for simulation output analysis. INFORMS Journal on Computing (2001) . in pressLinkGoogle Scholar
  • Sullivan D. W., Wilson J. R. Restricted subset selection procedures for simulation. Operations Research (1989) 37:52–71LinkGoogle Scholar
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