Solution of real-world train timetabling problems

Caprara, Alberto; Fischetti, Matteo; Guida, Pier Luigi; Monaci, Michele; Sacco, Giuseppe; Toth, Paolo

doi:10.1109/hicss.2001.926325

Cited by 24 publications

(12 citation statements)

References 7 publications

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“…Since then, numerous researchers have been working on problems ranging from sports timetabling [35], railway timetabling [14], [25] and educational timetabling [2], [3], [6], [15], [17], [30].…”

Section: Introductionmentioning

confidence: 99%

A Tabu Search Hyper-heuristic Approach to the Examination Timetabling Problem at the MARA University of Technology

Kendall

Hussin

2005

Practice and Theory of Automated Timetabling V

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Abstract. In this paper we introduce an examination timetabling problem from the MARA University of Technology (UiTM). UiTM is the largest university in Malaysia. It has 13 branch campuses and offers 144 programmes, delivered by 18 faculties. This dataset differs from the others reported in the literature due to weekend constraints that have to be observed. We present their examination timetabling problem with respect to its size, complexity and constraints. We analyse their real-world data, and produce solutions utilising a tabu-search-based hyper-heuristic. Since this is a new dataset, and no solutions have been published in the literature, we can only compare our results with an existing manual solution. We find that our solution is at least 80% better with respect to proximity cost. We also compare our approach against a benchmark dataset and show that our method is able to produce good quality results.

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Section: Introductionmentioning

confidence: 99%

A Tabu Search Hyper-heuristic Approach to the Examination Timetabling Problem at the MARA University of Technology

Kendall

Hussin

2005

Practice and Theory of Automated Timetabling V

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“…In the second research branch, the timetabling problem is planned for a 24 hour period, without considering cycles. 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.…”

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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“…Mainly in the field of Operations Research and Artificial Intelligence many interesting proposals have been presented, to solve timetabling problems in sports (Easton et al 2004;Trick 2001), transportations (bus, railways, planes) (Isaai and Singh 2001;Caprara et al 2001;Kendall and Mohd Hussin 2003;Qi et al 2004), schools (Abramson et al 1999;Colorni et al 1998;Ribeiro Filho and Lorena 2001;Hansen and Vidal 1995;Schaerf 1999) and universities (Awad and Chinneck 1998;Burke et al 2006;Burke and Newall 2003;Caramia et al 2001;Casey and Thompson 2003;Carter et al 1994;Corr et al 2006;Desroches et al 1978;Dowsland and Thompson 2005;Erben 2001;Di Gaspero 2000;Di Gaspero and Schaerf 2001;Kendall and Mohd Hussin 2003;Merlot et al 2003;Paquete and Fonseca 2001;Petrovic and Bykov 2003;Qu et al 2006;Schimmelpfeng and Helber 2007;Thompson and Dowsland 1996; Thompson and Dowsland 1998;White and Xie 2001;Yang and Petrovic 2005).…”

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confidence: 98%

Managing the tabu list length using a fuzzy inference system: an application to examination timetabling

Pais

Amaral

2011

Ann Oper Res

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In this paper, we present an application of Tabu Search (TS) to the examination timetabling problem. One of the drawbacks of this meta-heuristic is related to the need of tuning some parameter (like tabu tenure) whose value affects the performance of the algorithm. The importance of developing an automatic procedure is clear considering that most of the users of timetabling software, like academic staff, do not have the expertise to conduct such tuning. The goal of this paper is to present a method to automatically manage the memory in the TS using a Decision Expert System. More precisely a Fuzzy Inference Rule Based System (FIRBS) is implemented to handle the tabu tenure based on two concepts, "Frequency" and "Inactivity". These concepts are related respectively with the number of times a move is introduced in the tabu list and the last time (in number of iterations) the move was attempted and prevented by the tabu status. Computational results show that the implemented FIRBS handles well the tuning of the tabu status duration improving, as well, the performance of Tabu Search.

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Solution of real-world train timetabling problems

Cited by 24 publications

References 7 publications

A Tabu Search Hyper-heuristic Approach to the Examination Timetabling Problem at the MARA University of Technology

A Tabu Search Hyper-heuristic Approach to the Examination Timetabling Problem at the MARA University of Technology

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

Managing the tabu list length using a fuzzy inference system: an application to examination timetabling

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