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A web-based simulation optimization system for industrial scheduling

Authors:

Marcus Andersson,

Henrik Grimm,

Anna Persson,

Amos NgAuthors Info & Claims

WSC '07: Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come

Pages 1844 - 1852

Published: 09 December 2007 Publication History

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WSC '07: Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come

A web-based simulation optimization system for industrial scheduling

Pages 1844 - 1852

Abstract
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Abstract

Many real-world production systems are complex in nature and it is a real challenge to find an efficient scheduling method that satisfies the production requirements as well as utilizes the resources efficiently. Tools like discrete event simulation (DES) are very useful for modeling these systems and can be used to test and compare different schedules before dispatching the best schedules to the targeted systems. DES alone, however, cannot be used to find the "optimal" schedule. Simulation-based optimization (SO) can be used to search for optimal schedules efficiently without too much user intervention. Observing that long computing time may prohibit the interest in using SO for industrial scheduling, various techniques to speed up the SO process have to be explored. This paper presents a case study that shows the use of a Web-based parallel and distributed SO platform to support the operations scheduling of a machining line in an automotive factory.

References

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Cited By

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Hunter SApplegate EArora VChong BCooper KRincón-Guevara OVivas-Valencia C(2019)An Introduction to Multiobjective Simulation OptimizationACM Transactions on Modeling and Computer Simulation10.1145/329987229:1(1-36)Online publication date: 24-Jan-2019
https://dl.acm.org/doi/10.1145/3299872
(2017)A novel Iterative Optimization-based Simulation (IOS) frameworkComputers and Industrial Engineering10.1016/j.cie.2017.06.037111:C(1-17)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1016/j.cie.2017.06.037
Syberfeldt AKarlsson INg ASvantesson JAlmgren T(2013)A web-based platform for the simulation-optimization of industrial problemsComputers and Industrial Engineering10.1016/j.cie.2013.01.00864:4(987-998)Online publication date: 1-Apr-2013
https://dl.acm.org/doi/10.1016/j.cie.2013.01.008
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Published In

WSC '07: Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come

December 2007

2659 pages

ISBN:1424413060

General Chair:
Jeff Tew

Publisher

IEEE Press

Publication History

Published: 09 December 2007

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WSC07

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

WSC07: Winter Simulation Conference

December 9 - 12, 2007

Washington D.C.

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WSC '07 Paper Acceptance Rate 152 of 244 submissions, 62%;

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

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Hunter SApplegate EArora VChong BCooper KRincón-Guevara OVivas-Valencia C(2019)An Introduction to Multiobjective Simulation OptimizationACM Transactions on Modeling and Computer Simulation10.1145/329987229:1(1-36)Online publication date: 24-Jan-2019
https://dl.acm.org/doi/10.1145/3299872
(2017)A novel Iterative Optimization-based Simulation (IOS) frameworkComputers and Industrial Engineering10.1016/j.cie.2017.06.037111:C(1-17)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1016/j.cie.2017.06.037
Syberfeldt AKarlsson INg ASvantesson JAlmgren T(2013)A web-based platform for the simulation-optimization of industrial problemsComputers and Industrial Engineering10.1016/j.cie.2013.01.00864:4(987-998)Online publication date: 1-Apr-2013
https://dl.acm.org/doi/10.1016/j.cie.2013.01.008
Andersson MNg AGrimm HJefferson TFowler JIngalls R(2008)Simulation optimization for industrial scheduling using hybrid genetic representationProceedings of the 40th Conference on Winter Simulation10.5555/1516744.1517094(2004-2011)Online publication date: 7-Dec-2008
https://dl.acm.org/doi/10.5555/1516744.1517094

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Simulation Based Job Scheduling Optimization for Batch Workloads

Pareto and scalar bicriterion optimization in scheduling deteriorating jobs

Data mining based job dispatching using hybrid simulation-optimization approach for shop scheduling problem

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