Urban Rail Timetable Optimization to Improve Operational Efficiency with Flexible Routing Plans: A Nonlinear Integer Programming Model
At present, most urban rail transit systems adopt an operation mode with a single long routing. The departure frequency is determined by the maximum section passenger flow. However, when the passenger flow varies greatly within different sections, this mode will lead to a low load factor in some sec...
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| Published in: | Sustainability Vol. 11; no. 13; p. 3701 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Basel
MDPI AG
01.07.2019
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| Subjects: | |
| ISSN: | 2071-1050, 2071-1050 |
| Online Access: | Get full text |
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| Summary: | At present, most urban rail transit systems adopt an operation mode with a single long routing. The departure frequency is determined by the maximum section passenger flow. However, when the passenger flow varies greatly within different sections, this mode will lead to a low load factor in some sections, resulting in a waste of capacity. In view of this situation, this paper develops a nonlinear integer programming model to determine an optimal timetable with a balanced scheduling mode, where the wasted capacity at a constant departure frequency can be reduced with a slight increase in passenger waiting time. Then, we simplify the original model into a single-objective integer optimization model through normalization. A genetic algorithm is designed to find the optimal solution. Finally, a numerical example is presented based on real-world passenger and operation data from Beijing Metro Line 4. The results show that the double-routing optimization model can reduce wasted capacity by 9.5%, with a 4.5% increase in passenger waiting time, which illustrates the effectiveness of this optimization model. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 2071-1050 2071-1050 |
| DOI: | 10.3390/su11133701 |