Accelerating solving the dynamic multi-objective nework design problem using response surface methods

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Abstract

Multi objective optimization of externalities of traffic solving a network design problem in which Dynamic Traffic Management measures are used, is time consuming while heuristics are needed and solving the lower level requires solving the dynamic user equilibrium problem. Use of response surface methods in combination with evolutionary algorithms could accelerate the determination of the Pareto optimal set. Three of these methods are compared with employing the SPEA2+ evolutionary algorithm without use of these methods. The results show that the RSM methods accelerate the search considerably at the start, but tend to converge faster and therefore loose their head start.
Original languageEnglish
Title of host publicationProceedings 2nd International Conference on Models and Technologies for Intelligent Transportation Systems, June 22-24, 2011, Leuven
EditorsF. Viti, B. Immers, C. Tampere
Place of PublicationLeuven, Belgium
PublisherITS
Pages1-4
Number of pages4
Publication statusPublished - 22 Jun 2011
Event2nd International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2011 - Katholieke Universiteit Leuven, Leuven, Belgium
Duration: 22 Jun 201124 Jun 2011
Conference number: 2

Conference

Conference2nd International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2011
Abbreviated titleMT-ITS
CountryBelgium
CityLeuven
Period22/06/1124/06/11

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Evolutionary algorithms
Multiobjective optimization

Keywords

  • IR-101420
  • METIS-272941

Cite this

Wismans, L. J. J., van Berkum, E. C., & Bliemer, M. C. J. (2011). Accelerating solving the dynamic multi-objective nework design problem using response surface methods. In F. Viti, B. Immers, & C. Tampere (Eds.), Proceedings 2nd International Conference on Models and Technologies for Intelligent Transportation Systems, June 22-24, 2011, Leuven (pp. 1-4). Leuven, Belgium: ITS.
Wismans, Luc Johannes Josephus ; van Berkum, Eric C. ; Bliemer, Michiel C.J. / Accelerating solving the dynamic multi-objective nework design problem using response surface methods. Proceedings 2nd International Conference on Models and Technologies for Intelligent Transportation Systems, June 22-24, 2011, Leuven. editor / F. Viti ; B. Immers ; C. Tampere. Leuven, Belgium : ITS, 2011. pp. 1-4
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Wismans, LJJ, van Berkum, EC & Bliemer, MCJ 2011, Accelerating solving the dynamic multi-objective nework design problem using response surface methods. in F Viti, B Immers & C Tampere (eds), Proceedings 2nd International Conference on Models and Technologies for Intelligent Transportation Systems, June 22-24, 2011, Leuven. ITS, Leuven, Belgium, pp. 1-4, 2nd International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2011, Leuven, Belgium, 22/06/11.

Accelerating solving the dynamic multi-objective nework design problem using response surface methods. / Wismans, Luc Johannes Josephus; van Berkum, Eric C.; Bliemer, Michiel C.J.

Proceedings 2nd International Conference on Models and Technologies for Intelligent Transportation Systems, June 22-24, 2011, Leuven. ed. / F. Viti; B. Immers; C. Tampere. Leuven, Belgium : ITS, 2011. p. 1-4.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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N2 - Multi objective optimization of externalities of traffic solving a network design problem in which Dynamic Traffic Management measures are used, is time consuming while heuristics are needed and solving the lower level requires solving the dynamic user equilibrium problem. Use of response surface methods in combination with evolutionary algorithms could accelerate the determination of the Pareto optimal set. Three of these methods are compared with employing the SPEA2+ evolutionary algorithm without use of these methods. The results show that the RSM methods accelerate the search considerably at the start, but tend to converge faster and therefore loose their head start.

AB - Multi objective optimization of externalities of traffic solving a network design problem in which Dynamic Traffic Management measures are used, is time consuming while heuristics are needed and solving the lower level requires solving the dynamic user equilibrium problem. Use of response surface methods in combination with evolutionary algorithms could accelerate the determination of the Pareto optimal set. Three of these methods are compared with employing the SPEA2+ evolutionary algorithm without use of these methods. The results show that the RSM methods accelerate the search considerably at the start, but tend to converge faster and therefore loose their head start.

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Wismans LJJ, van Berkum EC, Bliemer MCJ. Accelerating solving the dynamic multi-objective nework design problem using response surface methods. In Viti F, Immers B, Tampere C, editors, Proceedings 2nd International Conference on Models and Technologies for Intelligent Transportation Systems, June 22-24, 2011, Leuven. Leuven, Belgium: ITS. 2011. p. 1-4