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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).
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Stored only when both papers are in the corpus — 17 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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