Chapter 3 Passenger Railway Optimization

Caprara, Alberto; Kroon, Leo; Monaci, Michele; Peeters, M.J.P.; Toth, Paolo

doi:10.1016/s0927-0507(06)14003-7

Cited by 172 publications

(112 citation statements)

References 70 publications

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“…A related and well studied field of application is integrated vehicle and crew scheduling, for example in the airline business or in the public transport sector. Pertinent surveys are given in Klabjan (2005), Caprara, Kroon, Monaci, Peeters, and Toth (2007), and Desaulniers and Hickman (2007). However, the models and solution approaches used for solving such problems are always based on the fundamental assumption of a given timetable for the requests/tasks.…”

Section: Literature Reviewmentioning

confidence: 99%

Simultaneous Vehicle and Crew Routing and Scheduling for Partial- and Full-Load Long-Distance Road Transport

Drexl

Rieck

Sigl

et al. 2013

Bus Res

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Section: Literature Reviewmentioning

confidence: 99%

Simultaneous Vehicle and Crew Routing and Scheduling for Partial- and Full-Load Long-Distance Road Transport

Drexl

Rieck

Sigl

et al. 2013

Bus Res

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“…Given its importance, the problem has been widely studied in the literature on railway optimization; for surveys on the specific problem as well as on the use of combinatorial optimization in railway planning see, e.g., [6,7,10,14,19].…”

Section: Literature Reviewmentioning

confidence: 99%

Solving a real-world train-unit assignment problem

2010

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Abstract. We face a real-world train unit assignment problem for an operator running trains in a regional area. Given a set of timetabled train trips, each with a required number of passenger seats, and a set of train units, each with a given number of available seats, the problem calls for an assignment of the train units to trips, possibly combining more than one train unit for a given trip, that fulfills the seat requests. With respect to analogous case studies previously faced in the literature, ours is characterized by the fairly large number of distinct train unit types available (in addition to the fairly large number of trips to be covered). As a result, although there is a wide margin of improvement over the solution used by the practitioners (as our results show), even only finding a solution of the same value is challenging in practice. We present a successful approach, based on an ILP formulation in which the seat requirement constraints are stated in a ")-1(strong" fo rm, derived from the description of the convex hull of the variant of the knapsack polytope arising when the sum of the variables is restricted not to exceed two, illustrating computational results on our case study.

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“…A state-of-the-art review of literature and practice revealed a lot of research in mathematical models for macroscopic timetable optimization (ON-TIME 2013), see also the review papers by Bussieck et al (1997), Cordeau et al (1998), Caprara et al (2007), and Lusby et al (2011). These macroscopic models rely implicitly on reliable input data which may not always be available.…”

Section: Introductionmentioning

confidence: 99%

A three-level framework for performance-based railway timetabling

Goverde

Bešinović

Binder

et al. 2016

Transportation Research Part C: Emerging Technologies

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The performance of railway operations depends highly on the quality of the railway timetable. In particular for dense railway networks it can be a challenge to obtain a stable robust conflict-free and energy-efficient timetable with acceptable infrastructure occupation and short travel times. This paper presents a performance-based railway timetabling framework using an integrated approach on three levels: microscopic, macroscopic and a corridor fine-tuning level, to compute a timetable explicitly driven by the above mentioned performance indicators. A case study on the Dutch railway network illustrates the feasibility of this approach to achieve the highest timetabling design level.

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Chapter 3 Passenger Railway Optimization

Cited by 172 publications

References 70 publications

Simultaneous Vehicle and Crew Routing and Scheduling for Partial- and Full-Load Long-Distance Road Transport

Simultaneous Vehicle and Crew Routing and Scheduling for Partial- and Full-Load Long-Distance Road Transport

Solving a real-world train-unit assignment problem

A three-level framework for performance-based railway timetabling

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