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A search acceleration method for optimization problems with transport simulation constraints
KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
2017 (English)In: Transportation Research Part B: Methodological, ISSN 0191-2615, Vol. 98, p. 1339-1351Article in journal (Refereed) Published
Abstract [en]

This work contributes to the rapid approximation of solutions to optimization problems that are constrained by iteratively solved transport simulations. Given an objective function, a set of candidate decision variables and a black-box transport simulation that is solved by iteratively attaining a (deterministic or stochastic) equilibrium, the proposed method approximates the best decision variable out of the candidate set without having to run the transport simulation to convergence for every single candidate decision variable. This method can be inserted into a broad class of optimization algorithms or search heuristics that implement the following logic: (i) Create variations of a given, currently best decision variable, (ii) identify one out of these variations as the new currently best decision variable, and (iii) iterate steps (i) and (ii) until no further improvement can be attained. A probabilistic and an asymptotic performance bound are established and exploited in the formulation of an efficient heuristic that is tailored towards tight computational budgets. The efficiency of the method is substantiated through a comprehensive simulation study with a non-trivial road pricing problem. The method is compatible with a broad range of simulators and requires minimal parametrization.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 98, p. 1339-1351
Keywords [en]
Budget control, Computation theory, Computational efficiency, Constrained optimization, Decision making, Heuristic algorithms, Heuristic methods, Optimization, Stochastic systems, Traffic control, Transportation charges, Acceleration method, Asymptotic performance, Computational budget, Objective functions, Optimization algorithms, Optimization problems, Simulation studies, Transport simulation
National Category
Other Civil Engineering
Identifiers
URN: urn:nbn:se:kth:diva-200856DOI: 10.1016/j.trb.2016.12.009ISI: 000400037700013Scopus ID: 2-s2.0-85009861496OAI: oai:DiVA.org:kth-200856DiVA, id: diva2:1071142
Note

QC 20170203

Available from: 2017-02-03 Created: 2017-02-03 Last updated: 2017-05-23Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf