Sequential sampling for solving stochastic programs

Güizin Bayraksan*, David P. Morton

*Corresponding author for this work

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

2 Scopus citations

Abstract

We develop a sequential sampling procedure for solving a class of stochastic programs. A sequence of feasible solutions, with at least one optimal limit point, is given as input to our procedure. Our procedure estimates the optimality gap of a candidate solution from this sequence, and if that point estimate is sufficiently small then we stop. Otherwise, we repeat with the next candidate solution from the sequence with a larger sample size. We provide conditions under which this procedure: (i) terminates with probability one and (ii) terminates with a solution which has a small optimality gap with a prespecified probability.

Original languageEnglish (US)
Title of host publicationProceedings of the 2007 Winter Simulation Conference, WSC
Pages421-429
Number of pages9
DOIs
StatePublished - Dec 1 2007
Event2007 Winter Simulation Conference, WSC - Washington, DC, United States
Duration: Dec 9 2007Dec 12 2007

Publication series

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

Other

Other2007 Winter Simulation Conference, WSC
CountryUnited States
CityWashington, DC
Period12/9/0712/12/07

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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