Exact formulations and algorithm for the train timetabling problem with dynamic demand

Barrena, Eva; Canca, David; Coelho, Leandro C.; Laporte, Gilbert

doi:10.1016/j.cor.2013.11.003

Cited by 205 publications

(96 citation statements)

References 21 publications

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“…Su et al (2013) and Li and Lo (2014) optimized the cyclic train schedule together with the driving strategy to minimize the energy consumption through the utilization of regenerative energy. Regular schedules can reduce the passenger waiting time if the passenger arrival process at stations is a uniform process or a Poisson process (Niu and Zhou, 2013;Barrena et al, 2014). However, regular schedules may result in longer passenger waiting times and travel times under time-varying passenger demands.…”

Section: Introductionmentioning

confidence: 97%

Passenger-demands-oriented train scheduling for an urban rail transit network

Wang

Tang

Ning

et al. 2015

Transportation Research Part C: Emerging Technologies

190

106

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Section: Introductionmentioning

confidence: 97%

Passenger-demands-oriented train scheduling for an urban rail transit network

Wang

Tang

Ning

et al. 2015

Transportation Research Part C: Emerging Technologies

190

106

View full text Add to dashboard Cite

“…The third formulation of the problem is based on the previous formulation of the problem except that the restrictions are on the departure time from station i and the minimal and maximal speed and waiting times. Branch and cut algorithm is used for all of the presented models [28]. In comparison to the actual cases the APWT is improved using computational experiments by 30-77 %.…”

Section: Mathematical Models For Minimizing the Pwt At The Transfer Smentioning

confidence: 99%

“…The problem of minimizing the cost of PWT at the station of the Madrid railway is presented in [28,29] and solved using …”

Section: Mathematical Models For Minimizing the Pwt At The Transfer Smentioning

confidence: 99%

Optimization Methods in Modern Transportation Systems

2018

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Abstract:One of the greatest challenges in the public transportation network is the optimization of the passengers waiting time, where it is necessary to find a compromise between the satisfaction of the passengers and the requirements of the transport companies. This paper presents a detailed review of the available literature dealing with the problem of passenger transport in order to optimize the passenger waiting time at the station and to meet the requirements of companies (maximize profits or minimize cost). After a detailed discussion, the paper clarifies the most important objectives in solving a timetabling problem: the requirements and satisfaction of passengers, passenger waiting time and capacity of vehicles. At the end, the appropriate algorithms for solving the set of optimization models are presented.

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“…Barrena et al [35] proposed a train timetabling model which deals with dynamic demand. Considering dynamic demand for di erent routes in di erent times, they proposed threebinary models and a branch and cut algorithm to minimize the total waiting of passengers in stations.…”

Section: Introductionmentioning

confidence: 99%

Train Timetabling on double track and multiple station capacity railway with useful upper and lower bounds

Jadid

Eshghi

2017

Scientia Iranica

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Abstract. Train scheduling has been one of the signi cant issues in the railway industry in recent years since it has an important role in e cacy of railway infrastructure. In this paper, the timetabling problem of a multiple-tracked railway network is discussed. More speci cally, a general model is presented here in which a set of operational and safety requirements is considered. The model handles the trains overtaking in stations and considers the stations' capacity. The objective function is to minimize the total travel time. Unfortunately, the problem is NP-hard, and real-sized problems cannot be solved in an acceptable amount of time. In order to reduce the processing time, we presented some heuristic rules, which reduce the number of binary variables. These rules are based on problem's parameters, such as travel time, dwell time, and safety time of stations, and try to remove the impracticable areas of the solution space. Furthermore, a Lagrangian Relaxation algorithm model is presented in order to nd a lower bound. Finally, comprehensive numerical experiments on the Tehran Metro case are reported. Results show the e ciency of the heuristic rules and also the Lagrangian Relaxation method in a way that the optimum values are obtained for all analyzed problems.

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Exact formulations and algorithm for the train timetabling problem with dynamic demand

Cited by 205 publications

References 21 publications

Passenger-demands-oriented train scheduling for an urban rail transit network

Passenger-demands-oriented train scheduling for an urban rail transit network

Optimization Methods in Modern Transportation Systems

Train Timetabling on double track and multiple station capacity railway with useful upper and lower bounds

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