In the simulation optimization setting, an approach that exploits the property that it is easier to select the correct order among noisy measurements than to obtain precise estimates, i.e., ordering converges faster (exponentially) than estimation.
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References
Ho, Y. C., Sreenevas, R., & Vakili, P. (1992). Ordinal optimization of DEDS. Discrete-Event Dynamic Systems: Theory and Applications, 2, 61–88.
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(2013). Ordinal Optimization. In: Gass, S.I., Fu, M.C. (eds) Encyclopedia of Operations Research and Management Science. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1153-7_200559
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DOI: https://doi.org/10.1007/978-1-4419-1153-7_200559
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