Work

Ant Colony Optimisation approaches for the transportation assignment problem

Year: 2010

Type: conference-paper

Abstract: In this paper, we propose an ACO-based algorithm that can be used to simulate mass-transit networks; this algorithm imitates the behaviour of public transport users.In particular, we show that the proposed algorithm, which is an extension of that proposed by D'Acierno et al. (A stochastic traffic assignment algorithm based on Ant Colony Optimisation, Lecture Notes in Computer Science 4150, pp.25-36, 2006), allows mass-transit systems to be simulated in less time but with the same accuracy compared with traditional assignment algorithms.Finally, we state theoretically the perfect equivalence in terms of hyperpath choice behaviour between artificial ants (simulated with the proposed algorithm) and mass-transit users (simulated with traditional assignment algorithms).

Source: WIT transactions on the built environment

DOI: 10.2495/ut100041

Authors: L. D’Acierno, M. Gallo, B. Montella

Institutions: University of Naples Federico II, University of Sannio

Language: English

Topic: Transportation Planning and Optimization

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: bronze

OpenAlex ID: W2076656846