a cross-entropy based multiagent approach for multiclass activity chain modeling and simulation
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.
|Date of creation:||11 May 2011|
|Date of revision:|
|Note:||View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00310903v3|
|Contact details of provider:|| Web page: https://hal.archives-ouvertes.fr/|
When requesting a correction, please mention this item's handle: RePEc:hal:wpaper:halshs-00310903. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (CCSD)
If references are entirely missing, you can add them using this form.