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a cross-entropy based multiagent approach for multiclass activity chain modeling and simulation


  • Tai-Yu Ma

    () (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

  • Jean-Patrick Lebacque

    () (IFSTTAR/GRETTIA - Génie des Réseaux de Transport Terrestres et Informatique Avancée - IFSTTAR - Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux - UPEC UP12 - Université Paris-Est Créteil Val-de-Marne - Paris 12)


This paper attempts to model complex destination-chain, departure time and route choices based on activity plan implementation and proposes an arc-based cross entropy method for solving approximately the dynamic user equilibrium in multiagent-based multiclass network context. A multiagent-based dynamic activity chain model is developed, combining travelers' day-to-day learning process in the presence of both traffic flow and activity supply dynamics. The learning process towards user equilibrium in multiagent systems is based on the framework of Bellman's principle of optimality, and iteratively solved by the cross entropy method. A numerical example is implemented to illustrate the performance of the proposed method on a multiclass queuing network.

Suggested Citation

  • Tai-Yu Ma & Jean-Patrick Lebacque, 2011. "a cross-entropy based multiagent approach for multiclass activity chain modeling and simulation," Working Papers halshs-00310903, HAL.
  • Handle: RePEc:hal:wpaper:halshs-00310903
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    dynamic traffic assignment; cross entropy method; activity chain; multiagent; Bellman equation;

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