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Proceedings Paper

Convergence and choice of comparison schemes for discrete optimization using statistical tests
Author(s): Patrick A. Kelly; Weibo Gong; Wengang Zhai
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Paper Abstract

Consider a discrete optimization problem where the objective function is the mean of a random variable and only samples of the random variable are available. A fundamental issue in such a problem is how to compare objective functions through the samples. Ideally, the chosen comparison scheme should lead to an algorithm whose output converges rapidly to the optimum value. In this paper we give some general conditions for convergence and then consider several algorithms having different comparison schemes.

Paper Details

Date Published: 22 June 1999
PDF: 12 pages
Proc. SPIE 3696, Enabling Technology for Simulation Science III, (22 June 1999); doi: 10.1117/12.351174
Show Author Affiliations
Patrick A. Kelly, Univ. of Massachusetts/Amherst (United States)
Weibo Gong, Univ. of Massachusetts/Amherst (United States)
Wengang Zhai, Ascend Communications, Inc. (United States)

Published in SPIE Proceedings Vol. 3696:
Enabling Technology for Simulation Science III
Alex F. Sisti, Editor(s)

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