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A convergent and efficient decomposition method for the traffic assignment problem

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Listed:
  • David Di Lorenzo
  • Alessandro Galligari
  • Marco Sciandrone

Abstract

In this work we consider the network equilibrium problem formulated as convex minimization problem whose variables are the path flows. In order to take into account the difficulties related to the large dimension of real network problems we adopt a decomposition-based approach suitably combined with a column generation strategy. We present an inexact block-coordinate descent method and we prove the global convergence of the algorithm. The results of computational experiments performed on medium-large dimensional problems show that the proposed algorithm is at least competitive with state of the art algorithms. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • David Di Lorenzo & Alessandro Galligari & Marco Sciandrone, 2015. "A convergent and efficient decomposition method for the traffic assignment problem," Computational Optimization and Applications, Springer, vol. 60(1), pages 151-170, January.
    • Handle: RePEc:spr:coopap:v:60:y:2015:i:1:p:151-170
    DOI: 10.1007/s10589-014-9668-6
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    References listed on IDEAS

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    1. Bar-Gera, Hillel & Hellman, Fredrik & Patriksson, Michael, 2013. "Computational precision of traffic equilibria sensitivities in automatic network design and road pricing," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 485-500.
    2. Fukushima, Masao, 1984. "A modified Frank-Wolfe algorithm for solving the traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 18(2), pages 169-177, April.
    3. Nie, Yu (Marco), 2010. "A class of bush-based algorithms for the traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 73-89, January.
    4. C. J. Lin & S. Lucidi & L. Palagi & A. Risi & M. Sciandrone, 2009. "Decomposition Algorithm Model for Singly Linearly-Constrained Problems Subject to Lower and Upper Bounds," Journal of Optimization Theory and Applications, Springer, vol. 141(1), pages 107-126, April.
    5. Hillel Bar-Gera, 2002. "Origin-Based Algorithm for the Traffic Assignment Problem," Transportation Science, INFORMS, vol. 36(4), pages 398-417, November.
    6. Larry J. LeBlanc & Richard V. Helgason & David E. Boyce, 1985. "Improved Efficiency of the Frank-Wolfe Algorithm for Convex Network Programs," Transportation Science, INFORMS, vol. 19(4), pages 445-462, November.
    7. Maria Mitradjieva & Per Olov Lindberg, 2013. "The Stiff Is Moving---Conjugate Direction Frank-Wolfe Methods with Applications to Traffic Assignment ," Transportation Science, INFORMS, vol. 47(2), pages 280-293, May.
    8. Torbjörn Larsson & Michael Patriksson, 1992. "Simplicial Decomposition with Disaggregated Representation for the Traffic Assignment Problem," Transportation Science, INFORMS, vol. 26(1), pages 4-17, February.
    9. Bar-Gera, Hillel, 2010. "Traffic assignment by paired alternative segments," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1022-1046, September.
    10. Dial, Robert B., 2006. "A path-based user-equilibrium traffic assignment algorithm that obviates path storage and enumeration," Transportation Research Part B: Methodological, Elsevier, vol. 40(10), pages 917-936, December.
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    Cited by:

    1. Leonardo Galli & Alessandro Galligari & Marco Sciandrone, 2020. "A unified convergence framework for nonmonotone inexact decomposition methods," Computational Optimization and Applications, Springer, vol. 75(1), pages 113-144, January.

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