Parameter selection for "pcma " using surrogate-Assisted blackbox optimization and microscopic traffic simulation

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

1 Citation (Scopus)

Abstract

Routing algorithms have become significantly more sophisticated in recent years as increasingly more data on road networks, vehicles and drivers becomes available. The correct parametrization of such algorithms is a difficult task since the underlying traffic model needs to reflect the complexity of the algorithm and should resemble reality closely. A major drawback of such models is that evaluating a certain parameter setting may become computationally expensive, preventing the use of conventional optimization algorithms. In this work a combination of surrogate assisted black box optimization and microscopic traffic simulation is used to optimize the parameters of a recently published routing algorithm.

Original languageEnglish
Title of host publication29th European Modeling and Simulation Symposium, EMSS 2017, Held at the International Multidisciplinary Modeling and Simulation Multiconference, I3M 2017
EditorsFrancesco Longo, Michael Affenzeller, Miquel Angel Piera, Agostino G. Bruzzone, Emilio Jimenez
PublisherCAL-TEK S.r.l.
Pages117-124
Number of pages8
ISBN (Electronic)9781510847651
Publication statusPublished - 2017
Event29th European Modeling and Simulation Symposium, EMSS 2017 - Barcelona, Spain
Duration: 18 Sept 201720 Sept 2017

Publication series

Name29th European Modeling and Simulation Symposium, EMSS 2017, Held at the International Multidisciplinary Modeling and Simulation Multiconference, I3M 2017

Conference

Conference29th European Modeling and Simulation Symposium, EMSS 2017
Country/TerritorySpain
CityBarcelona
Period18.09.201720.09.2017

Keywords

  • Evolutionary algorithms
  • Noisy optimization
  • Surrogate assisted optimization
  • Traffic simulation

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