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The mathematics of continuous-variable simulation optimization

Authors:

Shane G. HendersonAuthors Info & Claims

WSC '08: Proceedings of the 40th Conference on Winter Simulation

Pages 122 - 132

Published: 07 December 2008 Publication History

Abstract

Continuous-variable simulation optimization problems are those optimization problems where the objective function is computed through stochastic simulation and the decision variables are continuous. We discuss verifiable conditions under which the objective function is continuous or differ-entiable, and outline some key properties of two classes of methods for solving such problems, namely sample-average approximation and stochastic approximation.

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Cited By

Pasupathy RKim S(2011)The stochastic root-finding problemACM Transactions on Modeling and Computer Simulation10.1145/1921598.192160321:3(1-23)Online publication date: 4-Feb-2011
https://dl.acm.org/doi/10.1145/1921598.1921603
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
Staum JDunkin AIngalls R(2009)Better simulation metamodelingWinter Simulation Conference10.5555/1995456.1995478(119-133)Online publication date: 13-Dec-2009
https://dl.acm.org/doi/10.5555/1995456.1995478

The mathematics of continuous-variable 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 '08: Proceedings of the 40th Conference on Winter Simulation

December 2008

3189 pages

ISBN:9781424427086

Editors:
Scott Mason
University of Arkansas
,
Ray Hill
Air Force Institute of Technology
,
Lars Mönch
University of Hagen
,
Oliver Rose
University of Dresden
,
General Chair:
Thomas Jefferson
Intel Corporation
,
Program Chairs:
John W. Fowler
Arizona State University
,
Ricki G. Ingalls
Oklahoma State University

Sponsors

IIE: Institute of Industrial Engineers
INFORMS-SIM: Institute for Operations Research and the Management Sciences: Simulation Society
ASA: American Statistical Association
IEEE/SMC: Institute of Electrical and Electronics Engineers: Systems, Man, and Cybernetics 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

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Winter Simulation Conference

Publication History

Published: 07 December 2008

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WSC08

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IIE
INFORMS-SIM
ASA
IEEE/SMC
SIGSIM
NIST
(SCS)

WSC08: Winter Simulation Conference

December 7 - 10, 2008

Florida, Miami

Acceptance Rates

WSC '08 Paper Acceptance Rate 249 of 304 submissions, 82%;

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

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Cited By

Pasupathy RKim S(2011)The stochastic root-finding problemACM Transactions on Modeling and Computer Simulation10.1145/1921598.192160321:3(1-23)Online publication date: 4-Feb-2011
https://dl.acm.org/doi/10.1145/1921598.1921603
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
Staum JDunkin AIngalls R(2009)Better simulation metamodelingWinter Simulation Conference10.5555/1995456.1995478(119-133)Online publication date: 13-Dec-2009
https://dl.acm.org/doi/10.5555/1995456.1995478

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