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On the scalability of meta-models in simulation-based optimization of production systems
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Simulation-Based Optimization)ORCID iD: 0000-0001-5436-2128
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Simulation-Based Optimization)ORCID iD: 0000-0003-0111-1776
2015 (English)In: Proceedings of the 2015 Winter Simulation Conference / [ed] L. Yilmaz, W. K. V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, Piscataway, NJ: IEEE Press, 2015, 3644-3655 p.Conference paper, (Refereed)
Abstract [en]

Optimization of production systems often involves numerous simulations of computationally expensive discrete-event models. When derivative-free optimization is sought, one usually resorts to evolutionary and other population-based meta-heuristics. These algorithms typically demand a large number of objective function evaluations, which in turn, drastically increases the computational cost of simulations. To counteract this, meta-models are used to replace expensive simulations with inexpensive approximations. Despite their widespread use, a thorough evaluation of meta-modeling methods has not been carried out yet to the authors' knowledge. In this paper, we analyze 10 different meta-models with respect to their accuracy and training time as a function of the number of training samples and the problem dimension. For our experiments, we choose a standard discrete-event model of an unpaced flow line with scalable number of machines and buffers. The best performing meta-model is then used with an evolutionary algorithm to perform multi-objective optimization of the production model.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Press, 2015. 3644-3655 p.
Keyword [en]
Simulation, Optimization, Production, Evolutionary
National Category
Other Mechanical Engineering
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-11917ISBN: 978-1-4673-9743-8 OAI: oai:DiVA.org:his-11917DiVA: diva2:902854
Conference
WSC '15 Winter Simulation Conference, Huntington Beach, CA, USA — December 06 - 09, 2015
Available from: 2016-02-12 Created: 2016-02-12 Last updated: 2016-03-17Bibliographically approved

Open Access in DiVA

On the scalability of meta-models in simulation-based optimization of production systems(373 kB)100 downloads
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File name FULLTEXT01.pdfFile size 373 kBChecksum SHA-512
5d70e5db01c30630ce8ce731fecd8f9d4f5eda65df1f4ca4fe9eb66512136eeb2830a5794808554f13704619d11aaacae431e320fdf0bbae4a1bedb4b638cbe2
Type fulltextMimetype application/pdf

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http://dl.acm.org/citation.cfm?id=2889108

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Bandaru, SunithNg, Amos H. C.
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CiteExportLink to record
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Citation style
  • apa
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Language
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