https://scholars.lib.ntu.edu.tw/handle/123456789/425351
Title: | Optimizing rolling stock assignment and maintenance plan for passenger railway operations | Authors: | YUNG-CHENG LAI Fan, Dow Chung KWEI-LONG HUANG |
Keywords: | Decision-support model | Heuristics | Maintenance planning | Rail transportation | Rolling stock assignment planning | Issue Date: | 1-Jul-2015 | Publisher: | PERGAMON-ELSEVIER SCIENCE LTD | Journal Volume: | 85 | Start page/Pages: | 284 | Source: | Computers and Industrial Engineering | Abstract: | © 2015 Elsevier Ltd. All rights reserved. The efficient use of railway rolling stock is an important objective pursued in a railway agency or company because of intensive capital investment in rolling stock. Daily rolling stock assignment assigns appropriate equipment to cover a given set of utilization paths in the utilization schedules while considering practical requirements, such as maintenance, depot capacity, and circulation rules. Experienced railway practitioners can generally produce a feasible assignment plan; however, this manual process is time consuming, and an optimal solution is not guaranteed. This research develops an exact optimization model to improve the efficiency in rolling stock usage with consideration of all necessary regulations and practical constraints. Compared to the manual process, a hybrid heuristic process is also developed to improve solution quality and efficiency. Empirical results demonstrate that the heuristic process can successfully increase the efficiency of rolling stock use by about 5% and significantly reduce the solution time from 3 h to 11.2 s. Using this decision support tool can help railways with similar characteristics to improve the efficiency in rolling stock usage and productivity in rolling stock assignment process. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/425351 | ISSN: | 03608352 | DOI: | https://api.elsevier.com/content/abstract/scopus_id/84928493333 10.1016/j.cie.2015.03.016 |
Appears in Collections: | 工業工程學研究所 |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.