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Stochastic dominance based comparison for system selection

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  • Batur, D.
  • Choobineh, F.

Abstract

We present two complementing selection procedures for comparing simulated systems based on the stochastic dominance relationship of a performance metric of interest. The decision maker specifies an output quantile set representing a section of the distribution of the metric, e.g., downside or upside risks or central tendencies, as the basis for comparison. The first procedure compares systems over the quantile set of interest by a first-order stochastic dominance criterion. The systems that are deemed nondominant in the first procedure could be compared by a weaker almost first-order stochastic dominance criterion in the second procedure. Numerical examples illustrate the capabilities of the proposed procedures.

Suggested Citation

  • Batur, D. & Choobineh, F., 2012. "Stochastic dominance based comparison for system selection," European Journal of Operational Research, Elsevier, vol. 220(3), pages 661-672.
    • Handle: RePEc:eee:ejores:v:220:y:2012:i:3:p:661-672
    DOI: 10.1016/j.ejor.2012.02.018
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    References listed on IDEAS

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    1. Batur, D. & Choobineh, F., 2010. "A quantile-based approach to system selection," European Journal of Operational Research, Elsevier, vol. 202(3), pages 764-772, May.
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    4. Pichitlamken, Juta & Nelson, Barry L. & Hong, L. Jeff, 2006. "A sequential procedure for neighborhood selection-of-the-best in optimization via simulation," European Journal of Operational Research, Elsevier, vol. 173(1), pages 283-298, August.
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    Cited by:

    1. Demet Batur & F. Fred Choobineh, 2021. "Selecting the Best Alternative Based on Its Quantile," INFORMS Journal on Computing, INFORMS, vol. 33(2), pages 657-671, May.
    2. Demet Batur & Lina Wang & F. Fred Choobineh, 2018. "Methods for System Selection Based on Sequential Mean–Variance Analysis," INFORMS Journal on Computing, INFORMS, vol. 30(4), pages 724-738, November.
    3. Ng, Pin & Wong, Wing-Keung & Xiao, Zhijie, 2017. "Stochastic dominance via quantile regression with applications to investigate arbitrage opportunity and market efficiency," European Journal of Operational Research, Elsevier, vol. 261(2), pages 666-678.
    4. Montes, Ignacio & Miranda, Enrique & Montes, Susana, 2014. "Decision making with imprecise probabilities and utilities by means of statistical preference and stochastic dominance," European Journal of Operational Research, Elsevier, vol. 234(1), pages 209-220.

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