Ant colony optimisation combined with variable neighbourhood search for scheduling preventive railway maintenance activities
by Safa Khalouli; Rachid Benmansour; Saïd Hanafi
International Journal of Intelligent Engineering Informatics (IJIEI), Vol. 6, No. 1/2, 2018

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.

Online publication date: Fri, 06-Apr-2018

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