Approximately Optimal Computing-Budget Allocation for subset ranking

Document Type

Conference Proceeding

Publication Date

6-29-2015

Abstract

The best design among many can be selected through their accurate performance evaluation. When such evaluation is based on discrete event simulations, the design selection is extremely time-consuming. Ordinal optimization greatly speeds up this process. Optimal Computing-Budget Allocation (OCBA) has further accelerated it. Other kinds of OCBA have been introduced for reaching different goals, for example, to select the optimal subset of designs. However, facing the issue of subset ranking, which is a generalized form from problems selecting the best design or optimal subset, all the existing ones are insufficient. This work develops a new OCBA-based approach to address this subset ranking issue. Through mathematical deduction, its theoretical foundation is laid. Our numerical simulation results reveal that it indeed outperforms all the other existing methods in terms of probability of correct subset ranking and computational efficiency.

Identifier

84938281616 (Scopus)

ISBN

[9781479969234]

Publication Title

Proceedings IEEE International Conference on Robotics and Automation

External Full Text Location

https://doi.org/10.1109/ICRA.2015.7139736

ISSN

10504729

First Page

3856

Last Page

3861

Issue

June

Volume

2015-June

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