Rapid screening algorithms for stochastically constrained problems

Shing Chih Tsai () and Tse Yang
Additional contact information
Shing Chih Tsai: National Cheng Kung University
Tse Yang: National Cheng Kung University

Annals of Operations Research, 2017, vol. 254, issue 1, No 19, 425-447

Abstract: Abstract A simulation optimization framework containing three fundamental stages (feasibility check, screening, and selection) is proposed for solving the zero-one optimization via simulation problem in the presence of a single stochastic constraint. We present three rapid screening algorithms that combine these three stages in different manners, such that various sampling mechanisms are applied, therefore yielding different statistical guarantees. An empirical evaluation for the efficiency comparison between the proposed algorithms and other existing works is provided.

Keywords: Simulation; Output analysis; Optimization via simulation; Ranking and selection; Stochastic constraint (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s10479-017-2459-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:254:y:2017:i:1:d:10.1007_s10479-017-2459-6

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-017-2459-6

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().