• Journal of the Korean Society for Railway
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• v.17 no.4
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• pp.313-319
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• 2014

Additional train scheduling is often required to increase the capacity of transporting passengers or freight. In most previous studies on scheduling additional trains, operation time of the added train is designated first; and then the train operation feasibility is examined. However, it is often difficult to apply this approach to domestic trains because the density of the railroad network in Korea is high and various types of trains are in use. Moreover, for freight trains, it is even more challenging because the delay is accumulated due to lower priority whenever a freight train and a passenger train contend for a common segment of rail. In this paper, we address the additional train scheduling problem which entails finding a feasible schedule for an additional train having a fixed departure time or departure time windows. The problem is modeled as a mixed integer programming and a column generation technique is used to solve it.

• International Journal of Railway
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• v.6 no.1
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• pp.7-12
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• 2013

This paper provides an overview of Pakistan Railways scheduling and rescheduling. First of all, Pakistan Railways is introduced with its brief history and importance in this country. Assets of this network with passengers and freight using this are given. Current hope less situation is leading to privatization of this system as well as promoting short distance traveler to use road and Government efforts to retain is also presented. Train scheduling in Pakistan is being done manually, based on manual time distance graph preparation and resolution of conflicts based on manager's experience and ability. In Real-time management of this traffic Lahore head office is connected with six control stations in the Pakistan, decision for resolution of any disturbance is coordinated among them. It is recommended that computer aided tools must be developed for this system to help traffic managers and it is needed to invest on the segments to increase their speed limits which might attract passengers to use this mode of transportation with high priority.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3851-3857
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• 2014

Shippers' requests of freight trains vary with time, but generating an additional schedule of freight trains is not easy due to many considerations, such as the line capacity, operation rules, and conflicts with existing trains. On the other hand, an additional freight train schedule has been continuously requested and manually processed by domestic train operation companies using empirical method, which is time consuming. This paper proposes a model to determine the additional freight train schedule that assesses the feasibility of the added freight trains, and generates as many additional schedules as possible, while minimizing the delay of the existing schedules. The problem is presented using time-space network, modeled as multi-commodity flow problem, and solved using the column generation method. Three levels of experiment were conducted to show validity of the proposed model in the computation time.

• IE interfaces
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• v.24 no.4
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• pp.281-294
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• 2011

This paper considers the rail crane scheduling problem which is defined as determining the sequence of loading/unloading container on/from a freight train. The objective is to minimize the weighted sum of the range of order completion time and makespan. The range of order completion time implies the difference between the maximum of completion time and minimum of start time of each customer order consisting of jobs. Makespan refers to the time when all the jobs are completed. In a rail freight terminal, logistics firms as a customer wish to reduce the range of their order completion time. To develop a methodology for the crane scheduling, we formulate the problem as a mixed integer program and develop three metaheuristics, namely, genetic algorithm, simulated annealing, and tabu search. To validate the effectiveness of heuristic algorithms, computational experiments are done based on a set of real life data. Results of the experiments show that heuristic algorithms give good solutions for small-size and large-size problems in terms of solution quality and computation time.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.269-276
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• 2011

This paper considers the rail crane scheduling problem with minimizing the sum of the range of order completion time and make-span of rail crane simultaneously. The range of order completion time implies the difference between the maximum of completion time and minimum of start time. Make-span refers to the time when all the tasks are completed. At a rail terminal, logistics companies wish to concentrate on their task of loading and unloading container on/from rail freight train at a time in order to increase the efficiency of their equipment such as reach stacker. In other words, they want to reduce the range of their order completion time. As a part of efforts to meet the needs, the crane schedule is rearranged based on worker's experience. We formulate the problem as a mixed integer program. To validate the effectiveness of the model, computational experiments were conducted using a set of data randomly generated.

• Proceedings of the Safety Management and Science Conference
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• 2003.05a
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• pp.53-61
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• 2003

The process of railway traffic planning is composed of several steps such as long - term, mid - term, short - term, and real - time plan. The planning of vehicle and manpower resources is a main research topic in tactical short - term planning step Railway vehicle is usually consisted of a power car, passenger/freight cars and human resource is composed of engine driver, cabin crew, ground personnel. So far , power car was main research target in railway vehicle scheduling problem. Recently according as the light electric railway or high - speed railway is introduced, the operational planning of train set vehicles become important . In this paper , we introduce the conceptional model for trainset restoring problem and developed heuristic algorithm.