A choice function hyper-heuristic framework for the allocation of maintenance tasks in Danish railways

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A new signalling system in Denmark aims at ensuring fast and reliable train operations, however imposes very strict time limits on recovery plans in the event of failure. As a result, it is necessary to develop a new approach to the entire maintenance scheduling process. In the largest region of Denmark, the Jutland peninsula, there is a decentralised structure for maintenance planning, whereby the crew start their duties from their home locations rather than starting from a single depot. In this paper, we allocate a set of maintenance tasks in Jutland to a set of maintenance crew members, defining the sub-region that each crew member is responsible for. Two key considerations must be made when allocating tasks to crew members. Firstly a fair balance of workload must exist between crew members and secondly, the distance between two tasks in the same sub-region must be minimised, in order to facilitate quick response in the case of unexpected failure. We propose a perturbative selection hyper-heuristic framework to improve initial solutions by reassigning outliers, those tasks that are far away, to another crew member at each iteration, using one of five low-level heuristics. Results of two hyper-heuristics, using a number of different initial solution construction methods are presented over a set of 12 benchmark problem instances.
Original languageEnglish
JournalComputers & Operations Research
Pages (from-to)15-26
Number of pages12
Publication statusPublished - 2018

Bibliographical note

This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/)

CitationsWeb of Science® Times Cited: No match on DOI

    Research areas

  • Hyper-heuristic, Maintenance scheduling, Combinatiorial optimisation, European rail traffic management system

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