Convergence and choice of comparison schemes for discrete optimization using statistical tests

Patrick A. Kelly; Weibo Gong; Wengang Zhai

doi:10.1117/12.351174

22 June 1999 Convergence and choice of comparison schemes for discrete optimization using statistical tests

Patrick A. Kelly, Weibo Gong, Wengang Zhai

Proceedings Volume 3696, Enabling Technology for Simulation Science III; (1999) https://doi.org/10.1117/12.351174
Event: AeroSense '99, 1999, Orlando, FL, United States

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.

Citation Download Citation

Patrick A. Kelly, Weibo Gong, and Wengang Zhai "Convergence and choice of comparison schemes for discrete optimization using statistical tests", Proc. SPIE 3696, Enabling Technology for Simulation Science III, (22 June 1999); https://doi.org/10.1117/12.351174

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available