Gu, H & Lam, HC 2019, 'A Genetic Algorithm Approach for Scheduling Trains Maintenance Under Uncertainty', International Conference on Computer Science, Applied Mathematics and Applications, Springer, Cham, Hanoi, Vietnam, pp. 106-118.View/Download from: Publisher's site
Gu, H, Joyce, M, Lam, HC, Woods, M & Zinder, Y 2019, 'A Genetic Algorithm for Assigning Train Arrival Dates at a Maintenance Centre', IFAC-PapersOnLine, IFAC Conference on Manufacturing Modelling, Management and Control, IFAC Secretariat, Berlin, Germany, pp. 957-962.View/Download from: Publisher's site
The paper is concerned with planning heavy maintenance of train-sets at a maintenance centre. The heavy maintenance process is complex and, for each train-set, the actual duration of maintenance is uncertain at the time of planning. The allocation of the dates when train-sets should arrive at the maintenance centre is crucial phase of the planning procedure. The objective function is a weighted sum of two components, the expected total penalty for not meeting the required number of train-sets in active service and the total cost for the deviation (earliness and tardiness) from the desired dates of arrival. A genetic algorithm is presented for the considered problem and its effectiveness is demonstrated by the computational experiments that used real-world data provided by a big maintenance centre.