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Simulation selection problems: overview of an economic analysis

Published: 03 December 2006 Publication History

Abstract

This paper summarizes a new approach that we recently proposed for ranking and selection problems, one that maximizes the expected NPV of decisions made when using stochastic or discrete-event simulation. The expected NPV models not only the economic benefit from implementing a selected system, but also the marginal costs of simulation runs and discounting due to simulation analysis time. Our formulation assumes that facilities exist to simulate a fixed number of alternative systems, and we pose the problem as a "stoppable" Bayesian bandit problem. Under relatively general conditions, a Gittins index can be used to indicate which system to simulate or implement. We give an asymptotic approximation for the index that is appropriate when simulation outputs are normally distributed with known but potentially different variances for the different systems.

References

[1]
Branke, J., S. E. Chick, and C. Schmidt. 2005. New developments in ranking and selection, with an empirical comparison of the three main approaches. In Proceedings of the 2005 Winter Simulation Conference, ed. M. Kuhl, N. Steiger, F. Armstrong, and J. Joines, 708--717.
[2]
Breakwell, J., and H. Chernoff. 1964. Sequential tests for the mean of a normal distribution II (large t). Annals of Mathematical Statistics 35:162--163.
[3]
Brezzi, M., and T. L. Lai. 2002. Optimal learning and experimenation in bandit problems. Journal of Economic Dynamics & Control 27:87--108.
[4]
Chang, F., and T. L. Lai. 1987. Optimal stopping and dynamic allocation. Advances in Applied Probability 19:829--853.
[5]
Chen, C.-H., J. Lin, E. Yücesan, and S. E. Chick. 2000. Simulation budget allocation for further enhancing the efficiency of ordinal optimization. Discrete Event Dynamic Systems: Theory and Applications 10 (3): 251--270.
[6]
Chernoff, H. 1961. Sequential tests for the mean of a normal distribution. In Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, Volume 1, 79--91. University of California Press.
[7]
Chernoff, H., and A. J. Petkau. 1986. Numerical solutions for Bayes sequential decision problems. SIAM Journal on Scientific and Statistical Computing 7 (1): 46--59.
[8]
Chick, S. E. 2005. Subjective probability and Bayesian methodology. In Handbook in Operations Research and Management Science: Simulation, ed. S. Henderson and B. Nelson. Elsevier.
[9]
Chick, S. E. and N. Gans. 2005. An economic analysis of simulation selection problems. INSEAD/Wharton Alliance Working Paper, Fontainebleau, France.
[10]
Chick, S. E., and K. Inoue. 2001. New two-stage and sequential procedures for selecting the best simulated system. Operations Research 49 (5): 732--743.
[11]
Gittins, J. C. 1979. Bandit problems and dynamic allocation indices. Journal of the Royal Statistical Society, Series B 41:148--177.
[12]
Gittins, J. C. 1989. Multi-armed bandit allocation indices. New York: Wiley.
[13]
Gittins, J. C., and K. D. Glazebrook. 1977. On Bayesian models in stochastic scheduling. Journal of Applied Probability 14:556--565.
[14]
Gittins, J. C., and D. M. Jones. 1974. A dynamic allocation index for the sequential design of experiments. In Progress in Statistics, ed. J. Gani, K. Sarkadi, and J. Vincze. North-Holland.
[15]
Glazebrook, K. D. 1979. Stoppable families of alternative bandit processes. Journal of Applied Probability 16:843--854.
[16]
Kim, S.-H., and B. L. Nelson. 2001. A fully sequential procedure for indifference-zone selection in simulation. ACM Transactions on Modeling and Computer Simulation 11:251--273.
[17]
Kim, S.-H., and B. L. Nelson. 2005. Selecting the best system. In Handbook in Operations Research and Management Science: Simulation, ed. S. Henderson and B. Nelson. Elsevier.

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  • (2008)Update on economic approach to simulation selection problemsProceedings of the 40th Conference on Winter Simulation10.5555/1516744.1516807(297-304)Online publication date: 7-Dec-2008
  1. Simulation selection problems: overview of an economic analysis

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    cover image ACM Conferences
    WSC '06: Proceedings of the 38th conference on Winter simulation
    December 2006
    2429 pages
    ISBN:1424405017

    Sponsors

    • IIE: Institute of Industrial Engineers
    • ASA: American Statistical Association
    • IEICE ESS: Institute of Electronics, Information and Communication Engineers, Engineering Sciences Society
    • IEEE-CS\DATC: The IEEE Computer Society
    • SIGSIM: ACM Special Interest Group on Simulation and Modeling
    • NIST: National Institute of Standards and Technology
    • (SCS): The Society for Modeling and Simulation International
    • INFORMS-CS: Institute for Operations Research and the Management Sciences-College on Simulation

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    Winter Simulation Conference

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    Published: 03 December 2006

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    • IIE
    • ASA
    • IEICE ESS
    • IEEE-CS\DATC
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    • NIST
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    • INFORMS-CS
    WSC06: Winter Simulation Conference 2006
    December 3 - 6, 2006
    California, Monterey

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    WSC '06 Paper Acceptance Rate 177 of 252 submissions, 70%;
    Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

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    • (2008)Update on economic approach to simulation selection problemsProceedings of the 40th Conference on Winter Simulation10.5555/1516744.1516807(297-304)Online publication date: 7-Dec-2008

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