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The Equivalence between Ordinal Optimization in Deterministic Complex Problems and in Stochastic Simulation Problems

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Abstract

In the last decade ordinal optimization (OO) has been successfully applied in many stochastic simulation-based optimization problems (SP) and deterministic complex problems (DCP). Although the application of OO in the SP has been justified theoretically, the application in the DCP lacks similar analysis. In this paper, we show the equivalence between OO in the DCP and in the SP, which justifies the application of OO in the DCP.

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Authors and Affiliations

  1. Division of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA

    Yu-Chi Ho

  2. Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University, Beijing, 100084, People’s Republic of China

    Yu-Chi Ho, Qing-Shan Jia & Qian-Chuan Zhao

Authors
  1. Yu-Chi Ho
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  2. Qing-Shan Jia
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  3. Qian-Chuan Zhao
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Corresponding author

Correspondence to Qing-Shan Jia.

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Acknowledgment of Financial Support

This work was supported by ARO contract DAAD19-01-1-0610, AFOSR contract F49620-01-1-0288, NSF grant ECS-0323685, NSFC Grant No.60274011 and the NCET (No.NCET-04-0094) program of China.

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Ho, YC., Jia, QS. & Zhao, QC. The Equivalence between Ordinal Optimization in Deterministic Complex Problems and in Stochastic Simulation Problems. Discrete Event Dyn Syst 16, 405–411 (2006). https://doi.org/10.1007/s10626-006-9329-8

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  • DOI: https://doi.org/10.1007/s10626-006-9329-8

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