The Equivalence between Ordinal Optimization in Deterministic Complex Problems and in Stochastic Simulation Problems |
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| Authors: | Yu-Chi Ho Qing-Shan Jia Qian-Chuan Zhao |
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| Affiliation: | (1) Division of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA;(2) Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University, Beijing, 100084, People’s Republic of China |
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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. 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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| Keywords: | Ordinal optimization Equivalence Deterministic complex problems Stochastic simulation problems |
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