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System optimal routing of traffic flows with user constraints using linear programming

Author

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  • Angelelli, E.
  • Morandi, V.
  • Savelsbergh, M.
  • Speranza, M.G.

Abstract

For static traffic assignment problems, it is well known that (1) for some users the experienced travel time in a system optimum assignment can be substantially higher than the experienced travel time in a user equilibrium assignment, and (2) the total travel time in user equilibrium can be substantially higher than the total travel time in system optimum. By seeking system optimal traffic flows subject to user constraints, a compromise assignment can be obtained that balances system and user objectives. To this aim, a linear model and an efficient heuristic algorithm are proposed in this paper. A computational study shows that the proposed model, along with the heuristic algorithm, is able to provide fair solutions with near-optimal total travel time within very short computational time.

Suggested Citation

  • Angelelli, E. & Morandi, V. & Savelsbergh, M. & Speranza, M.G., 2021. "System optimal routing of traffic flows with user constraints using linear programming," European Journal of Operational Research, Elsevier, vol. 293(3), pages 863-879.
    • Handle: RePEc:eee:ejores:v:293:y:2021:i:3:p:863-879
    DOI: 10.1016/j.ejor.2020.12.043
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    References listed on IDEAS

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    Cited by:

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    2. Joanna Szkutnik-Rogoż & Jarosław Ziółkowski & Jerzy Małachowski & Mateusz Oszczypała, 2021. "Mathematical Programming and Solution Approaches for Transportation Optimisation in Supply Network," Energies, MDPI, vol. 14(21), pages 1-32, October.
    3. Fei Han & Jian Wang & Lingli Huang & Yan Li & Liu He, 2023. "Modeling Impacts of Implementation Policies of Tradable Credit Schemes on Traffic Congestion in the Context of Traveler’s Cognitive Illusion," Sustainability, MDPI, vol. 15(15), pages 1-18, July.
    4. Jarosław Ziółkowski & Aleksandra Lęgas & Elżbieta Szymczyk & Jerzy Małachowski & Mateusz Oszczypała & Joanna Szkutnik-Rogoż, 2022. "Optimization of the Delivery Time within the Distribution Network, Taking into Account Fuel Consumption and the Level of Carbon Dioxide Emissions into the Atmosphere," Energies, MDPI, vol. 15(14), pages 1-22, July.

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