A Stochastic User Equilibrium (SUE) algorithm based on Ant Colony Optimisation (ACO)

In this paper we propose a Stochastic User Equilibrium (SUE) algorithm that can be adopted as a simulation model when cost functions depend on the number of vehicles using network elements. 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 compared with traditional MSA algorithms.