A new framework for parallel ranking & selection using an adaptive standard

Linda Pei; Barry L. Nelson; Susan Hunter

doi:10.1109/WSC.2018.8632457

A new framework for parallel ranking & selection using an adaptive standard

Linda Pei, Barry L. Nelson, Susan Hunter

Industrial Engineering and Management Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

15 Scopus citations

Abstract

When we have sufficient computational resources to treat a simulation optimization problem as a ranking & selection (R&S) problem, then it can be “solved.” R&S is exhaustive search-all feasible solutions are simulated-with meaningful statistical error control. High-performance parallel computing promises to extend the R&S limit to even larger problems, but parallelizing R&S procedures in a way that maintains statistical validity while achieving substantial speed-up is difficult. In this paper we introduce an entirely new framework for R&S called Parallel Adaptive Survivor Selection (PASS) that is specifically engineered to exploit parallel computing environments for solving simulation optimization problems with a very large number of feasible solutions.

Original language	English (US)
Title of host publication	WSC 2018 - 2018 Winter Simulation Conference
Subtitle of host publication	Simulation for a Noble Cause
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2201-2212
Number of pages	12
ISBN (Electronic)	9781538665725
DOIs	https://doi.org/10.1109/WSC.2018.8632457
State	Published - Jul 2 2018
Event	2018 Winter Simulation Conference, WSC 2018 - Gothenburg, Sweden Duration: Dec 9 2018 → Dec 12 2018

Publication series

Name	Proceedings - Winter Simulation Conference
Volume	2018-December
ISSN (Print)	0891-7736

Conference

Conference	2018 Winter Simulation Conference, WSC 2018
Country/Territory	Sweden
City	Gothenburg
Period	12/9/18 → 12/12/18

Funding

Hunter’s research was partially supported by the National Science Foundation under Grant Number CMMI-1554144. Nelson and Pei’s research was partially supported by the National Science Foundation under Grant Number CMMI-1537060. Hunter's research was partially supported by the National Science Foundation under Grant Number CMMI-1554144. Nelson and Pei's research was partially supported by the National Science Foundation under Grant Number CMMI-1537060.

ASJC Scopus subject areas

Software
Modeling and Simulation
Computer Science Applications

Access to Document

10.1109/WSC.2018.8632457

Cite this

Pei, L., Nelson, B. L., & Hunter, S. (2018). A new framework for parallel ranking & selection using an adaptive standard. In WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause (pp. 2201-2212). Article 8632457 (Proceedings - Winter Simulation Conference; Vol. 2018-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2018.8632457

@inproceedings{b9f047721863457d892a0e25dba2cc78,

title = "A new framework for parallel ranking \& selection using an adaptive standard",

abstract = "When we have sufficient computational resources to treat a simulation optimization problem as a ranking \& selection (R\&S) problem, then it can be “solved.” R\&S is exhaustive search-all feasible solutions are simulated-with meaningful statistical error control. High-performance parallel computing promises to extend the R\&S limit to even larger problems, but parallelizing R\&S procedures in a way that maintains statistical validity while achieving substantial speed-up is difficult. In this paper we introduce an entirely new framework for R\&S called Parallel Adaptive Survivor Selection (PASS) that is specifically engineered to exploit parallel computing environments for solving simulation optimization problems with a very large number of feasible solutions.",

author = "Linda Pei and Nelson, \{Barry L.\} and Susan Hunter",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE; 2018 Winter Simulation Conference, WSC 2018 ; Conference date: 09-12-2018 Through 12-12-2018",

year = "2018",

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doi = "10.1109/WSC.2018.8632457",

language = "English (US)",

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Pei, L, Nelson, BL & Hunter, S 2018, A new framework for parallel ranking & selection using an adaptive standard. in WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause., 8632457, Proceedings - Winter Simulation Conference, vol. 2018-December, Institute of Electrical and Electronics Engineers Inc., pp. 2201-2212, 2018 Winter Simulation Conference, WSC 2018, Gothenburg, Sweden, 12/9/18. https://doi.org/10.1109/WSC.2018.8632457

A new framework for parallel ranking & selection using an adaptive standard. / Pei, Linda; Nelson, Barry L.; Hunter, Susan.
WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause. Institute of Electrical and Electronics Engineers Inc., 2018. p. 2201-2212 8632457 (Proceedings - Winter Simulation Conference; Vol. 2018-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - When we have sufficient computational resources to treat a simulation optimization problem as a ranking & selection (R&S) problem, then it can be “solved.” R&S is exhaustive search-all feasible solutions are simulated-with meaningful statistical error control. High-performance parallel computing promises to extend the R&S limit to even larger problems, but parallelizing R&S procedures in a way that maintains statistical validity while achieving substantial speed-up is difficult. In this paper we introduce an entirely new framework for R&S called Parallel Adaptive Survivor Selection (PASS) that is specifically engineered to exploit parallel computing environments for solving simulation optimization problems with a very large number of feasible solutions.

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A new framework for parallel ranking & selection using an adaptive standard

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