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Article

Gradient-based simulation optimization

Author:

Sujin KimAuthors Info & Claims

WSC '06: Proceedings of the 38th conference on Winter simulation

Pages 159 - 167

Published: 03 December 2006 Publication History

Abstract

We present a review of methods for simulation optimization. In particular, we focus on gradient-based techniques for continuous optimization. We demonstrate the main concepts using as an example the multidimensional newsvendor problem. We also discuss mathematical techniques and results that are useful in verifying and analyzing the simulation optimization procedures.

References

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Cited By

Broadie MCicek DZeevi A(2014)Multidimensional stochastic approximationACM Transactions on Modeling and Computer Simulation10.1145/255308524:1(1-28)Online publication date: 1-Jan-2014
https://dl.acm.org/doi/10.1145/2553085
Hamm ASalfeld TWeber SHill RKuhl M(2013)Stochastic root finding for optimized certainty equivalentsProceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World10.5555/2675983.2676101(922-932)Online publication date: 8-Dec-2013
https://dl.acm.org/doi/10.5555/2675983.2676101
Qu HRyzhov IFu MHill RKuhl M(2013)Learning logistic demand curves in business-to-business pricingProceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World10.5555/2675983.2675987(29-40)Online publication date: 8-Dec-2013
https://dl.acm.org/doi/10.5555/2675983.2675987
Show More Cited By

Gradient-based simulation optimization
1. Information systems
  1. Data management systems
    1. Database administration
2. Theory of computation
  1. Design and analysis of algorithms

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Information & Contributors

Information

Published In

cover image ACM Conferences

WSC '06: Proceedings of the 38th conference on Winter simulation

December 2006

2429 pages

ISBN:1424405017

Editors:
L. Felipe Perrone
Bucknell University
,
Barry G. Lawson
University of Richmond
,
Jason Liu
Colorado School of Mines
,
Frederick P. Wieland
Sensis Corporation
,
General Chair:
David Nicol
University of Illinois, Urbana-Champaign
,
Program Chair:
Richard Fujimoto
College of Computing, Georgia Tech

Sponsors

IIE: Institute of Industrial Engineers
ASA: American Statistical Association
IEICE ESS: Institute of Electronics, Information and Communication Engineers, Engineering Sciences Society
IEEE-CS\DATC: The IEEE Computer Society
SIGSIM: ACM Special Interest Group on Simulation and Modeling
NIST: National Institute of Standards and Technology
(SCS): The Society for Modeling and Simulation International
INFORMS-CS: Institute for Operations Research and the Management Sciences-College on Simulation

Publisher

Winter Simulation Conference

Publication History

Published: 03 December 2006

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WSC06

Sponsor:

IIE
ASA
IEICE ESS
IEEE-CS\DATC
SIGSIM
NIST
(SCS)
INFORMS-CS

WSC06: Winter Simulation Conference 2006

December 3 - 6, 2006

California, Monterey

Acceptance Rates

WSC '06 Paper Acceptance Rate 177 of 252 submissions, 70%;

Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

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Citations

Cited By

Broadie MCicek DZeevi A(2014)Multidimensional stochastic approximationACM Transactions on Modeling and Computer Simulation10.1145/255308524:1(1-28)Online publication date: 1-Jan-2014
https://dl.acm.org/doi/10.1145/2553085
Hamm ASalfeld TWeber SHill RKuhl M(2013)Stochastic root finding for optimized certainty equivalentsProceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World10.5555/2675983.2676101(922-932)Online publication date: 8-Dec-2013
https://dl.acm.org/doi/10.5555/2675983.2676101
Qu HRyzhov IFu MHill RKuhl M(2013)Learning logistic demand curves in business-to-business pricingProceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World10.5555/2675983.2675987(29-40)Online publication date: 8-Dec-2013
https://dl.acm.org/doi/10.5555/2675983.2675987
Kim SZhang DYücesan E(2010)Convergence properties of direct search methods for stochastic optimizationProceedings of the Winter Simulation Conference10.5555/2433508.2433628(1003-1011)Online publication date: 5-Dec-2010
https://dl.acm.org/doi/10.5555/2433508.2433628
özdemir DYücesan EHerer YDunkin AIngalls R(2009)Sample average approximation approach to multi-location transshipment problem with capacitated productionWinter Simulation Conference10.5555/1995456.1995782(2384-2394)Online publication date: 13-Dec-2009
https://dl.acm.org/doi/10.5555/1995456.1995782
Broadie MCicek DZeevi ADunkin AIngalls R(2009)An adaptive multidimensional version of the Kiefer-Wolfowitz stochastic approximation algorithmWinter Simulation Conference10.5555/1995456.1995549(601-612)Online publication date: 13-Dec-2009
https://dl.acm.org/doi/10.5555/1995456.1995549
Horng SLin S(2009)An ordinal optimization theory-based algorithm for a class of simulation optimization problems and applicationExpert Systems with Applications: An International Journal10.5555/1512993.151312536:5(9340-9349)Online publication date: 1-Jul-2009
https://dl.acm.org/doi/10.5555/1512993.1513125
Paternina-Arboleda CMontoya-Torres JFábregas-Ariza AJefferson TFowler JIngalls R(2008)Simulation-optimization using a reinforcement learning approachProceedings of the 40th Conference on Winter Simulation10.5555/1516744.1516984(1376-1383)Online publication date: 7-Dec-2008
https://dl.acm.org/doi/10.5555/1516744.1516984
Kim SHenderson SJefferson TFowler JIngalls R(2008)The mathematics of continuous-variable simulation optimizationProceedings of the 40th Conference on Winter Simulation10.5555/1516744.1516774(122-132)Online publication date: 7-Dec-2008
https://dl.acm.org/doi/10.5555/1516744.1516774
Kabirian AOlafsson STew J(2007)Allocation of simulation runs for simulation optimizationProceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come10.5555/1351542.1351619(363-371)Online publication date: 9-Dec-2007
https://dl.acm.org/doi/10.5555/1351542.1351619

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