Selecting the Optimal System Design under Covariates

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

21 Scopus Citations
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Detail(s)

Original languageEnglish
Title of host publication2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)
PublisherIEEE
Pages547-552
ISBN (electronic)9781728103556, 9781728103563
ISBN (print)9781728103570
Publication statusPublished - Aug 2019

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2019-August
ISSN (Print)2161-8070
ISSN (electronic)2161-8089

Conference

Title2019 IEEE 15th International Conference on Automation Science and Engineering (CASE 2019)
LocationUniversity of British Columbia
PlaceCanada
CityVancouver
Period22 - 26 August 2019

Abstract

In this research, we consider the ranking and selection problem in the presence of covariates. It is an important problem in personalized decision making. The performance of each design alternative depends on the values of the covariates to the simulation model for which the relationship is hard to describe analytically. Therefore the optimal design under each possible covariate value needs to be estimated by simulation. This work first introduces three measures to evaluate the selection quality over the covariate space and investigates their rate functions of convergence. By optimizing the rate functions, an asymptotically optimal budget allocation rule is developed and a corresponding selection algorithm is devised. We further show that the selection algorithm can recover the asymptotical optimal allocation in the limit. The high efficiency of the selection algorithm is illustrated via numerical testing.

Citation Format(s)

Selecting the Optimal System Design under Covariates. / Gao, Siyang; Du, Jianzhong; Chen, Chun-Hung.
2019 IEEE 15th International Conference on Automation Science and Engineering (CASE). IEEE, 2019. p. 547-552 8842957 (IEEE International Conference on Automation Science and Engineering; Vol. 2019-August).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review