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

Linda Pei, Barry L. Nelson, Susan Hunter

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations


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 languageEnglish (US)
Title of host publicationWSC 2018 - 2018 Winter Simulation Conference
Subtitle of host publicationSimulation for a Noble Cause
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages12
ISBN (Electronic)9781538665725
StatePublished - Jan 31 2019
Event2018 Winter Simulation Conference, WSC 2018 - Gothenburg, Sweden
Duration: Dec 9 2018Dec 12 2018

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736


Conference2018 Winter Simulation Conference, WSC 2018

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications


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