A New Multi-objective Solution Approach Using ModeFRONTIER and OpenTrack for Energy-Efficient Train Timetabling Problem
Trains move along the railway infrastructure according to specific timetables. The timetables are based on the running time calculation and they are usually calculated without considering explicitly energy consumption. Since green transportation is becoming more and more important from environmental perspectives, energy consumption minimization could be considered also in timetable calculation. In particular, the Energy-Efficient Train Timetabling Problem (EETTP) consists in the energy-efficient timetable calculation considering the trade-off between energy efficiency and running times. In this work, a solution approach to solve a multi-objective EETTP is described in which the two objectives are the minimization of both energy consumption and the total travel time. The approach finds the schedules to guarantee that the train speed profiles minimize the objectives. It is based on modeFRONTIER and OpenTrack that are integrated by using the OpenTrack Application Programming Interface in a modeFRONTIER workflow. In particular, the optimization is made by modeFRONTIER, while the calculation of the train speed profiles, energy consumption and total travel time is made by OpenTrack. The approach is used with Multi-objective Genetic Algorithm-II and the Non-dominating Sorting Genetic-II, which are two genetic algorithms available in modeFRONTIER. The solution approach is tested on a case study that represents a real situation of metro line in Turkey. For both algorithms, a Pareto Front of solution which are a good trade-off between the objectives are reported. The results show significant reduction of both energy consumption and total travel time with respect to the existing timetable.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9783030377519
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Supplemental Notes:
- © Springer Nature Switzerland AG 2020.
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Corporate Authors:
Springer Cham
Gewerbestrasse 11
Cham, Germany -
Authors:
- Longo, Giovanni
- Montrone, Teresa
- Poloni, Carlo
- Publication Date: 2020-2
Language
- English
Media Info
- Media Type: Web
- Edition: 1st Edition
- Features: References;
- Pagination: pp 103-119
- Monograph Title: Computation and Big Data for Transport: Digital Innovations in Surface and Air Transport Systems
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Serial:
- Computational Methods in Applied Sciences
- Volume: 54
- Publisher: Springer Cham
- ISSN: 1871-3033
- Serial URL: https://www.springer.com/series/6899
Subject/Index Terms
- TRT Terms: Energy consumption; Optimization; Railroad transportation; Running speed; Timetables; Travel time
- Geographic Terms: Turkey
- Subject Areas: Energy; Operations and Traffic Management; Planning and Forecasting; Railroads;
Filing Info
- Accession Number: 01892592
- Record Type: Publication
- ISBN: 9783030377519
- Files: TRIS
- Created Date: Sep 11 2023 11:39AM