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Ant colony optimisation combined with variable neighbourhood search for scheduling preventive railway maintenance activities

Abstract : Railway infrastructure maintenance is of fundamental importance in order to ensure a good service in terms of punctuality, safety and efficiently operation of trains on railway track and also for passenger comfort. Track maintenance covers a large amount of different activities such as inspections, repairs, and renewals. In this paper, we address the NP-hard problem of scheduling the preventive railway maintenance activities in order to minimise the overall cost of these activities. Given the complexity of the problem, we propose two meta-heuristics, a variable neighbourhood search (VNS), and an ant colony optimisation (ACO) based on opportunities to deal with this problem. Then, we develop a hybrid approach combining ACO with VNS. The performance of our proposed algorithms is tested by numerical experiments on a large number of randomly generated instances. Comparisons with optimal solutions are presented. The results show the effectiveness of our proposed methods.
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Submitted on : Monday, October 25, 2021 - 11:02:28 AM
Last modification on : Wednesday, November 3, 2021 - 5:22:09 AM

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Safa Khalouli, Rachid Benmansour, Said Hanafi. Ant colony optimisation combined with variable neighbourhood search for scheduling preventive railway maintenance activities. International Journal of Intelligent Engineering Informatics, Inderscience Publishers, 2018, 6 (1/2), pp.78. ⟨10.1504/IJIEI.2018.10012067⟩. ⟨hal-03400896⟩

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