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Path Flow Estimator in an Entropy Model Using a Nonlinear L-Shaped Algorithm

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Listed:
  • Maryam Abareshi

    (Semnan University)

  • Mehdi Zaferanieh

    (Hakim Sabzevari University)

  • Bagher Keramati

    (Semnan University)

Abstract

The general problem of estimating origin-destination matrices in congested traffic networks is formulated as a mathematical program with equilibrium constraints. In this paper a path flow entropy model based on an equilibrium assignment approach is presented. It is assumed the flows on links are disaggregated due to some external reasons. Using the L-shaped algorithm the problem is transformed into a problem with less constraints. Then applying the lagrangian dual function the original problem is reduced to a nonlinear convex problem with only one linear constraint.

Suggested Citation

  • Maryam Abareshi & Mehdi Zaferanieh & Bagher Keramati, 2017. "Path Flow Estimator in an Entropy Model Using a Nonlinear L-Shaped Algorithm," Networks and Spatial Economics, Springer, vol. 17(1), pages 293-315, March.
    • Handle: RePEc:kap:netspa:v:17:y:2017:i:1:d:10.1007_s11067-016-9327-9
    DOI: 10.1007/s11067-016-9327-9
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    References listed on IDEAS

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    Cited by:

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    3. Maryam Abareshi & Mehdi Zaferanieh & Mohammad Reza Safi, 2019. "Origin-Destination Matrix Estimation Problem in a Markov Chain Approach," Networks and Spatial Economics, Springer, vol. 19(4), pages 1069-1096, December.
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    5. Li, Tao & Wan, Yan, 2019. "Estimating the geographic distribution of originating air travel demand using a bi-level optimization model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 267-291.

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