In this paper, we propose an ACO-based algorithm to imitate the behaviour of public transport users. In particular, we show that the proposed algorithm allows transit systems to be simulated in less time but with the same accuracy compared with traditional assignment algorithms. Moreover, we state the equivalence in terms of hyperpath choice behaviour between artificial ants (simulated with the proposed algorithm) and transit users (simulated with traditional assignment algorithms). Finally, we apply the proposed algorithm on a real-scale network highlighting performances of the ACO approach.

An Ant Colony Optimisation algorithm for simulating hyper-path choices on real-scale networks

D'ACIERNO, LUCA;MONTELLA, BRUNO
2010

Abstract

In this paper, we propose an ACO-based algorithm to imitate the behaviour of public transport users. In particular, we show that the proposed algorithm allows transit systems to be simulated in less time but with the same accuracy compared with traditional assignment algorithms. Moreover, we state the equivalence in terms of hyperpath choice behaviour between artificial ants (simulated with the proposed algorithm) and transit users (simulated with traditional assignment algorithms). Finally, we apply the proposed algorithm on a real-scale network highlighting performances of the ACO approach.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11588/369462
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