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dc.contributor.authorRos Oton, Xavier
dc.contributor.authorMontero Mercadé, Lídia
dc.contributor.authorBarceló Bugeda, Jaime
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.date.accessioned2018-01-22T20:44:33Z
dc.date.available2018-01-22T20:44:33Z
dc.date.issued2017
dc.identifier.citationRos, X., Lídia Montero, Barcelo, J. Notes on using simulation-optimization techniques in traffic simulation. A: EURO Working Group on Transportation. Meeting. "20th EURO Working Group on Transportation Meeting, EWGT 2017, 4-6 September 2017, Budapest, Hungary". Budapest: Elsevier, 2017, p. 881-888.
dc.identifier.urihttp://hdl.handle.net/2117/113081
dc.description© <year>. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.description.abstractMathematical and simulation models of systems lay at the core of many decision support systems, and their role becomes more critical when the system is more complex. The decision process usually involves optimizing some utility function that evaluates the performance indicators measuring the impacts of the decisions. The complexity of the system directly increases the difficulty when the associated function to be optimized is a non-analytical, non-differentiable, non-linear function that can only be evaluated by simulation. Simulation-optimization techniques are especially suited to these cases, and its use is becoming increasingly used with traffic models, which represent an archetypal case of complex, dynamic systems that exhibit highly stochastic characteristics. In this approach, simulation is used to evaluate the objective function, and it is combined with a non-differentiable optimization technique for solving the associated optimization problem. Of these techniques, one of the most commonly used is Stochastic Perturbation Stochastic Approximation (SPSA). This paper analyses, discusses and presents the computational results from applying this technique in the calibration of traffic simulation models. This study uses variants of the SPSA by replacing the usual gradient approach with a combination of projected gradient and trust region methods. A special approach has also been analyzed for parameter calibration cases in which each variable has a different magnitude.
dc.format.extent8 p.
dc.language.isoeng
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Simulació
dc.subject.otherSimulation-optimization
dc.subject.otherTraffic Simulation
dc.subject.otherCalibration of Simulation Models
dc.subject.otherSimultaneous Perturbation Stochastic Approximation
dc.titleNotes on using simulation-optimization techniques in traffic simulation
dc.typeConference report
dc.contributor.groupUniversitat Politècnica de Catalunya. MPI - Modelització i Processament de la Informació
dc.identifier.doi10.1016/j.trpro.2017.12.098
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::49 Calculus of variations and optimal control; optimization
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S235214651730995X
dc.rights.accessOpen Access
drac.iddocument21186170
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/PE2016-2020/TRA2016-76914-C3-1-P
upcommons.citation.authorRos, X., Lídia Montero, Barcelo, J.
upcommons.citation.contributorEURO Working Group on Transportation. Meeting
upcommons.citation.pubplaceBudapest
upcommons.citation.publishedtrue
upcommons.citation.publicationName20th EURO Working Group on Transportation Meeting, EWGT 2017, 4-6 September 2017, Budapest, Hungary
upcommons.citation.startingPage881
upcommons.citation.endingPage888


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