Journal article
A choice function hyper-heuristic framework for the allocation of maintenance tasks in Danish railways
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.
Language: | English |
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Year: | 2018 |
Pages: | 15-26 |
ISSN: | 1873765x and 03050548 |
Types: | Journal article |
DOI: | 10.1016/j.cor.2017.09.011 |
ORCIDs: | Pour, Shahrzad M. and 0000-0002-8278-2207 |
Combinatiorial optimisation European rail traffic management system Hyper-heuristic Maintenance scheduling