A disjunctive graph model and framework for constructing new train schedules

Burdett, Robert L.; Kozan, Erhan

doi:10.1016/j.ejor.2008.12.005

Cited by 60 publications

(27 citation statements)

References 32 publications

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“…They used the disjunctive graph to represent the problem and used LS and SA to obtain good correction. Burdett and Kozan [19] considered the timetabling problem as a jobshop problem and addressed a customized disjunctive graph to construct the timetable. In addition, they proposed some CA to create feasible solutions.…”

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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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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“…Liu and Kozan [18] present a feasibility satisfaction procedure algorithm to solve the train scheduling problem which regarded as a blocking parallel-machine job shop scheduling problem. Burdett and Kozan [19] proposed a novel hybrid job shop approach to create new train schedules.…”

Section: Introductionmentioning

confidence: 99%

“…Liu and Kozan [15] presented a feasibility satisfaction procedure algorithm to solve the train scheduling problem which is regarded as a blocking parallel-machine job shop scheduling problem. Burdett and Kozan [19] proposed a novel hybrid job shop approach to create new train schedules. Based on the TAS method proposed by Dorfman and Medanic [16], Li et al [4] proposed an algorithm based on the global information of the train to obtain an effective travel advance strategy of the train.…”

Section: Introductionmentioning

confidence: 99%

“…Şahin [17], Higgins et al [14], and Liu and Kozan [18] extended some priority rules to backtracking search, look-ahead search, and metaheuristic algorithms for train scheduling, respectively. Burdett and Kozan [19] divided the scheduling process into two levels: global scheduling to establish an initial train diagram without considering conflicts and local scheduling to repair conflicts. Dorfman and Medanic [16] developed a local feedback based travel advance strategy (TAS) by using a discrete event model of the train advance along the lines of railway.…”

Section: Introductionmentioning

confidence: 99%

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Coordination Optimization of the First and Last Trains' Departure Time on Urban Rail Transit Network

Zhou

Deng

Xie

et al. 2013

Advances in Mechanical Engineering

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Coordinating the departure times of different line directions' of first and the last trains contributes to passengers' transferring. In this paper, a coordination optimization model (i.e., M1) referring to the first train's departure time is constructed firstly to minimize passengers' total originating waiting time and transfer waiting time for the first trains. Meanwhile, the other coordination optimization model (i.e., M2) of the last trains' departure time is built to reduce passengers' transfer waiting time for the last trains and inaccessible passenger volume of all origin-destination (OD) and improve passengers' accessible reliability for the last trains. Secondly, two genetic algorithms, in which a fixed-length binary-encoding string is designed according to the time interval between the first train departure time and the earliest service time of each line direction or between the last train departure time and the latest service time of each line direction, are designed to solve M1 and M2, respectively. Finally, the validity and rationality of M1, M2, and their solving genetic algorithms are verified with numerical analysis, in which the effects of the parameters in M1 and M2 on coordination optimization result are analyzed.

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“…They claimed that it was an efficient technique with respect to the time needed to travel criteria. Burdett and Kozan (2010) made a relationship between flexible job-shop (with parallel machines) and train scheduling. They used a disjunctive graph to model the train scheduling problem.…”

Section: Introductionmentioning

confidence: 99%

Scheduling algorithm with controllable train speeds and departure times to decrease the total train tardiness

Gholami¹,

Sotskov²

2014

10.5267/j.ijiec

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The problem of generating a train schedule for a single-track railway system is addressed in this paper. A three stage scheduling is proposed to reduce the total train tardiness. We derived an appropriate job-shop scheduling algorithm called DR-algorithm. In the first stage, by determining appropriate weights of the dispatching rules, a pre-schedule is constructed. In the second stage, on the basis of the pre-schedule, the departure times of the trains are modified to reduce the number of conflicts in using railway sections by different trains. In the third stage, a train speed control helps the scheduler to change the trains' speeds in order to reduce the train tardiness and to reach other objectives. The factual train schedule is based on the modified train speeds and on the modified departure times of the trains. The experimental running of the DR-algorithm on the benchmark instances showed this algorithm can solve train scheduling problems in a close to optimal way. In particular, the total train tardiness was reduced about 20% due to controlling train speeds and the departure times of the trains.

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A disjunctive graph model and framework for constructing new train schedules

Cited by 60 publications

References 32 publications

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

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

Coordination Optimization of the First and Last Trains' Departure Time on Urban Rail Transit Network

Scheduling algorithm with controllable train speeds and departure times to decrease the total train tardiness

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