A Genetic Algorithm for Railway Scheduling Problems

Tormos, Pilar; Lova, Antonio; Barber, Federico; Ingolotti, L.; Abril, M.; Salido, Miguel Á.

doi:10.1007/978-3-540-78985-7_10

Cited by 48 publications

(25 citation statements)

References 13 publications

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“…As train timetabling problem is known to be NP-hard [5,7,15,33], a meta-heuristic algorithms have been applied to solve it. It has been shown that GA has high potential in finding the global optimum in a large, poorly defined search space even in the presence of difficulties such as high dimensionality, multi-modality, discontinuity, and noise [15].…”

Section: Genetic Algorithmmentioning

confidence: 99%

“…It has been shown that GA has high potential in finding the global optimum in a large, poorly defined search space even in the presence of difficulties such as high dimensionality, multi-modality, discontinuity, and noise [15]. GA has been successfully applied to combinatorial problems and is able to handle huge search spaces as those arising in scheduling problems [33]. Therefore, in this paper, GA has been used to optimize train timetable.…”

Section: Genetic Algorithmmentioning

confidence: 99%

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A simulation-based optimization approach for passenger train timetabling with periodic track maintenance and stops for praying

Bahramian

Bagheri

2015

J. Mod. Transport.

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This paper presents two optimization methods for solving the passenger train timetabling problem to minimize the total delay time in the single track railway networks. The goal of the train timetable problem is to determine departure and arrival times to or from each station in order to prevent collisions between trains and effective utilization of resources. The two proposed methods are based on integration of a simulation and an optimization method to simulate train traffic flow and generate near optimal train timetable under realistic constraints including stops for track maintenance and praying. The first proposed method integrates a cellular automata (CA) simulation model with genetic algorithm optimization method. In the second proposed approach, a CA simulation model combines with dynamically dimensioned search optimization method. The proposed models are applied to hypothetical case study to demonstrate the merit of them. The Islamic Republic of Iran Railways (IRIR) data and regulations have been used to optimize train timetable. The results show the first method is more efficient than the second method to obtain near optimal train timetabling.

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Section: Genetic Algorithmmentioning

confidence: 99%

Section: Genetic Algorithmmentioning

confidence: 99%

A simulation-based optimization approach for passenger train timetabling with periodic track maintenance and stops for praying

Bahramian

Bagheri

2015

J. Mod. Transport.

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“…In this case, the problem is typically formulated as a multicommodity flow problem Schlechte, 2007, 2008;Caprara et al, 2001Caprara et al, , 2002Caprara et al, , 2006. Further papers deal with a different but related problem, i.e., the problem of inserting additional trains in an existing timetable (Burdett and Kozan, 2009;Cacchiani et al, 2010;Flier et al, 2009;Ingolotti et al, 2004;Lova et al, 2007;Tormos et al, 2008), mostly for scheduling additional freight trains. In this case, the timetable already established for passenger trains is not modifiable, and freight train operators indicate their requests to the infrastructure manager in terms of an ideal timetable.…”

Section: Rail Transportationmentioning

confidence: 99%

Single European Sky and Single European Railway Area: A system level analysis of air and rail transportation

Pellegrini

Rodríguez

2013

Transportation Research Part A: Policy and Practice

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Air and rail transportation systems are characterized by important common features: they serve a significant share of passenger traffic in Europe; their functioning relies on the cooperation of many stakeholders operating a fixed timetable, often with competing objectives; and they have been characterized by quite a fragmented development following national borders. For these systems, the European Commission envisages a common future in terms of an increase of efficiency and elimination of national borders. In this paper, we analyze the two systems in the perspective of their common development and we underline the main existing differences linked to the management of the infrastructure. These differences concern the processes implemented for specifying and allocating capacity, both in strategic planning and in real-time intervention. Our analysis suggests that the air transportation system is moving in the direction indicated by the European Commission, as well as the rail transportation system for what concerns international train paths (typically high-speed trains). However, a substantial separation still exists between conventional rail transportation systems of different countries.

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“…In the category of meta-heuristic methods, Tormos et al [24] proposed a Genetic Algorithm (GA) for the PESP that included a guided process to build the initial population. Jamili et al [25] proposed a model to deal with train timetabling in single-rail networks based on PESP.…”

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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A Genetic Algorithm for Railway Scheduling Problems

Cited by 48 publications

References 13 publications

A simulation-based optimization approach for passenger train timetabling with periodic track maintenance and stops for praying

A simulation-based optimization approach for passenger train timetabling with periodic track maintenance and stops for praying

Single European Sky and Single European Railway Area: A system level analysis of air and rail transportation

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

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