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Genetic algorithm based on conflict detecting for solving departure time domains of passenger trains

Genetic algorithm based on conflict detecting for solving departure time domains of passenger trains AbstractIn passenger train operations, it is imperative that timetables are well planned to achieve the highest levels of efficiency and safety. The departure time domain of passenger trains serves as the framework and core component of the train timetable, determining a rough plan for passenger trains, which eventually impacts the overall performance of the train operations. The goal of the departure time domain of passenger trains is to satisfy the passenger's expected arrival/departure times. This paper developed a departure time domain for passenger trains under the constrained receiving and dispatching capacities of arrival–departure tracks in a railway station. A genetic algorithm was proposed based on strategies of conflict detecting in order to calculate an optimal arrival and departure time domain for the trains. The proposed model and algorithm were implemented in an experimental network at Chengdu Station in China with 52 pairs of trains; the results showed that all trains met the expectations of the passengers with the capacities of the arrival–departure tracks. The model and algorithm developed in this paper could also serve to resolve the problem of departure time domain of passenger trains in an entire railway network. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Transportation Letters (The International Journal of Transportation Research) Taylor & Francis

Genetic algorithm based on conflict detecting for solving departure time domains of passenger trains

Genetic algorithm based on conflict detecting for solving departure time domains of passenger trains


Abstract

AbstractIn passenger train operations, it is imperative that timetables are well planned to achieve the highest levels of efficiency and safety. The departure time domain of passenger trains serves as the framework and core component of the train timetable, determining a rough plan for passenger trains, which eventually impacts the overall performance of the train operations. The goal of the departure time domain of passenger trains is to satisfy the passenger's expected arrival/departure times. This paper developed a departure time domain for passenger trains under the constrained receiving and dispatching capacities of arrival–departure tracks in a railway station. A genetic algorithm was proposed based on strategies of conflict detecting in order to calculate an optimal arrival and departure time domain for the trains. The proposed model and algorithm were implemented in an experimental network at Chengdu Station in China with 52 pairs of trains; the results showed that all trains met the expectations of the passengers with the capacities of the arrival–departure tracks. The model and algorithm developed in this paper could also serve to resolve the problem of departure time domain of passenger trains in an entire railway network.

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References (41)

Publisher
Taylor & Francis
Copyright
© 2015 W. S. Maney & Son Ltd
ISSN
1942-7875
eISSN
1942-7867
DOI
10.1179/1942787515Y.0000000009
Publisher site
See Article on Publisher Site

Abstract

AbstractIn passenger train operations, it is imperative that timetables are well planned to achieve the highest levels of efficiency and safety. The departure time domain of passenger trains serves as the framework and core component of the train timetable, determining a rough plan for passenger trains, which eventually impacts the overall performance of the train operations. The goal of the departure time domain of passenger trains is to satisfy the passenger's expected arrival/departure times. This paper developed a departure time domain for passenger trains under the constrained receiving and dispatching capacities of arrival–departure tracks in a railway station. A genetic algorithm was proposed based on strategies of conflict detecting in order to calculate an optimal arrival and departure time domain for the trains. The proposed model and algorithm were implemented in an experimental network at Chengdu Station in China with 52 pairs of trains; the results showed that all trains met the expectations of the passengers with the capacities of the arrival–departure tracks. The model and algorithm developed in this paper could also serve to resolve the problem of departure time domain of passenger trains in an entire railway network.

Journal

Transportation Letters (The International Journal of Transportation Research)Taylor & Francis

Published: Sep 1, 2015

Keywords: Departure time domain; Genetic algorithm; Arrival and departure track; Conflicts detecting

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