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 ACObased algorithm.
A stochastic traffic assignment algorithm based on Ant Colony Optimisation / D'Acierno, Luca; Montella, Bruno; De Lucia, F.. - 4150:(2006), pp. 25-36. (Intervento presentato al convegno ANTS 2006 - Fifth International Workshop on Ant Colony Optimization and Swarm Intelligence tenutosi a Brussels, Belgium nel September 2006) [10.1007/11839088_3].
A stochastic traffic assignment algorithm based on Ant Colony Optimisation
D'ACIERNO, LUCA;MONTELLA, BRUNO;
2006
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 ACObased algorithm.File | Dimensione | Formato | |
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