Scheduling Train Crews: A Case Study for the Dutch Railways

Freling, Richard; Lentink, Ramon; Odijk, Michiel A.

doi:10.1007/978-3-642-56423-9_9

Cited by 27 publications

(17 citation statements)

References 8 publications

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“…Examples of similar strategies can be found in Barnhart et al (1995) and Freling et al (2001). Moreover, we reduce the search state space of the SPPRC algorithm by considering only a limited number of labels with minimal reduced cost in the sets L v .…”

Section: Solving the Gcsp Pricing Problemmentioning

confidence: 97%

A note on extending the generic crew scheduling model of Beasley and Cao by deadheads and layovers

Derigs

Schäfer

2014

Journal of the Operational Research Society

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Crew scheduling is a highly complex combinatorial problem that has substantial and consequential economic importance in practice. Although the core structure of the problem is the same in many different areas like urban transportation, airlines etc, the specific problem instances show significant differences with respect to constraints stemming from different legal, industry-wide and firm-specific regulations. Beasley and Cao (1996) have introduced a generic crew scheduling problem (GCSP) and a basic mathematical program. In this paper, we extend this work by introducing two types of GCSPs that represent important additional features arising in real-world settings: the possibility of deadheading and the partitioning into duties with long (overnight) breaks in between. We present appropriate models, outline the design of a common branch and price and cut-solution approach and report computational experience. The aim of this study is to analyse the additional complexity that occurs by introducing these concepts, as well as the reduction in operational cost that can be obtained.

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Section: Solving the Gcsp Pricing Problemmentioning

confidence: 97%

A note on extending the generic crew scheduling model of Beasley and Cao by deadheads and layovers

Derigs

Schäfer

2014

Journal of the Operational Research Society

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“…The size and complexity of crew scheduling and rostering problems for large railway companies calls for the application of sophisticated optimization algorithms. Some examples include Abbink et al [2005], Caprara et al [1998] and Freling et al [2001]. Caprara et al [1998] propose an integer programming formulation of the crew rostering problem and describe a heuristic algorithm, which utilizes a Lagrangian lower bound, as a possible solution method.…”

Section: Robustness In Crew Planningmentioning

confidence: 99%

A survey on robustness in railway planning

Lusby

Larsen

Bull³

2018

European Journal of Operational Research

106

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“…reoptimization). We have not used pre-processor or post-optimizer strategies, except for some network reduction techniques (see Freling et al (2001)). Here, we provide a list of the strategies that we have implemented and tested.…”

Section: Exact Strategies For Computer Time Reductionmentioning

confidence: 99%

“…In Freling et al (2001), the authors consider a case study for the Dutch Railways in detail. We use a heuristic branch-and-price algorithm to solve CSP's with at most 1114 tasks.…”

Section: Example Applicationsmentioning

confidence: 99%

A Decision Support System for Crew Planning in Passenger Transportation Using a Flexible Branch-and-Price Algorithm

Freling

Lentink

Wagelmans

2004

Annals of Operations Research

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This paper discusses a decision support system for airline and railway crew planning. The system is a state-of-the-art branch-and-price solver that is used for crew scheduling and crew rostering. We briefly discuss the mathematical background of the solver, of which most part is covered in the Operations Research literature. Crew scheduling is crew planning for one or a few days that results in crew duties or pairings, and crew rostering is crew planning for at least one week for individual crew members. Technical issues about the system and its implementation are covered in more detail, as well as several applications. In particular, we focus on a specific aircrew rostering application. The computational results contain an interesting comparison of results obtained with, on one hand, the approach in which crew scheduling is carried out before crew rostering, and, on the other hand, an approach in which these two planning problems are solved in an integrated manner.

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Scheduling Train Crews: A Case Study for the Dutch Railways

Cited by 27 publications

References 8 publications

A note on extending the generic crew scheduling model of Beasley and Cao by deadheads and layovers

A note on extending the generic crew scheduling model of Beasley and Cao by deadheads and layovers

A survey on robustness in railway planning

A Decision Support System for Crew Planning in Passenger Transportation Using a Flexible Branch-and-Price Algorithm

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