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Article Dans Une Revue Expert Systems with Applications Année : 2023

A robust ant colony metaheuristic for urban freight transport scheduling using passenger rail network

Résumé

This paper considers a promising alternative for freight transport using urban passenger rail networks. It addresses a freight rail transport scheduling problem (FRTSP), which is one of the key operational issues to integrate freight into passenger transport in urban areas. In this paper, we develop a robust ant colony optimization (ACO) metaheuristic to tackle large-size instances. Taguchi method is used to set control parameters to make the algorithm robust. Computational results clearly highlight the proposed ACO algorithm’s capability of yielding near-optimal solutions in short computation times, even in large-size instances. They also show that the proposed algorithm dominates classic ACO variants, even when the parameters of these variants are also set using Taguchi method.
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Dates et versions

hal-04056732 , version 1 (03-04-2023)

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Walid Behiri, Sana Belmokhtar-Berraf, Chengbin Chu. A robust ant colony metaheuristic for urban freight transport scheduling using passenger rail network. Expert Systems with Applications, 2023, 213, pp.118906. ⟨10.1016/j.eswa.2022.118906⟩. ⟨hal-04056732⟩
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