2015Transportation LettersRequires access

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

D. Chen, Shaoquan Ni, Hao Lv, Miaomiao Lv, H. Li

Open publisher page 10 citations

Abstract

In 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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What this paper is about

In 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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Available abstract

In 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.

Key concepts: Train, Domain (mathematical analysis), Genetic algorithm, Computer science, Arrival time, Time domain, Plan (archaeology), Real-time computing

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