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A Stochastic Traffic Assignment Algorithm Based on Ant Colony Optimisation

  • Luca D’Acierno
  • Bruno Montella
  • Fortuna De Lucia
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4150)

Abstract

In this paper we propose a Stochastic User Equilibrium (SUE) algorithm that can be adopted as a model, known as a simulation model, that imitates the behaviour of transportation systems. Indeed, analyses of real dimension networks need simulation algorithms that allow network conditions and performances to be rapidly determined. Hence, we developed an MSA (Method of Successive Averages) algorithm based on the Ant Colony Optimisation paradigm that allows transportation systems to be simulated in less time but with the same accuracy as traditional MSA algorithms. Finally, by means of Blum’s theorem, we stated theoretically the convergence of the proposed ACO-based algorithm.

Keywords

Assignment Problem Network Design Problem Assignment Algorithm Pheromone Trail Stochastic User Equilibrium 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Luca D’Acierno
    • 1
  • Bruno Montella
    • 1
  • Fortuna De Lucia
    • 1
  1. 1.Dept. of Transportation Engineering‘Federico II’ UniversityNaplesItaly

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