Change search
ReferencesLink to record
Permanent link

Direct link
Sensitivity analysis of optimization: Examining sensitivity of bottleneck optimization to input data models
University of Skövde, School of Engineering Science.
2016 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The aim of this thesis is to examine optimization sensitivity in SCORE to the accuracy of particular input data models used in a simulation model of a production line. The purpose is to evaluate if it is sufficient to model input data using sample mean and default distributions instead of fitted distributions. An existing production line has been modeled for the simulation study. SCORE is based on maximizing any key performance measure of the production line while simultaneously minimizing the number of improvements necessary to achieve maximum performance. The sensitivity to the input models should become apparent the more changes required. The experiments concluded that the optimization struggles to obtain convergence when fitted distribution models were used. Configuring the input parameters to the optimization might yield better optimization result. The final conclusion is that the optimization is sensitive to what input data models are used in the simulation model.

Place, publisher, year, edition, pages
2016. , 45 p.
Keyword [en]
simulation, optimization, input modeling, probability distribution, simulation-based constraint removal, production systems
National Category
Computer and Information Science
URN: urn:nbn:se:his:diva-12624OAI: diva2:944556
Subject / course
Automation Engineering
Available from: 2016-07-01 Created: 2016-06-29 Last updated: 2016-07-01Bibliographically approved

Open Access in DiVA

fulltext(2305 kB)13 downloads
File information
File name FULLTEXT01.pdfFile size 2305 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Ekberg, Marie
By organisation
School of Engineering Science
Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 13 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 32 hits
ReferencesLink to record
Permanent link

Direct link