Disruption Management for an Airline — Rescheduling of Aircraft

Løve, Michael; Sørensen, Kim Riis; Larsen, Jesper; Clausen, Jens

doi:10.1007/3-540-46004-7_31

Cited by 24 publications

(26 citation statements)

References 8 publications

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“…The DAR solver developed in the Descartes project is based on an extension of the local search heuristic presented by Løve et al [28]. A heuristic approach were chosen due to the time requirements.…”

Section: The Dar Model and Solution Approachmentioning

confidence: 99%

“…The initial testing surprisingly showed that the SALS heuristics were superior to the ILS heuristic. A more in-depth description of the model developed and the results of the initial testing can be found in Løve et al [28].…”

Section: The Dar Model and Solution Approachmentioning

confidence: 99%

“…In [28] Løve et al present a heuristic for the aircraft recovery problem based on local search. The schedule is represented by the lines of work for each available aircraft.…”

Section: Aircraft Recoverymentioning

confidence: 99%

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Airline disruption management—Perspectives, experiences and outlook

Kohl¹,

Larsen

et al. 2007

Journal of Air Transport Management

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212

130

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Over the past decade, airlines have become more concerned with developing an optimal flight schedule, with very little slack left to accommodate for any form of variation from the optimal solution. During operation the planned schedules often have to be revised due to disruptions caused by for example severe weather, technical problems and crew sickness. Thus, the field of Airline Disruption Management has emerged within the past few years. The increased focus on cutting cost at the major airlines has intensified the interest in the development of new and cost efficient methods to handle airline disruptions.The purpose of this paper is twofold. In the first part it offers an introduction to airline disruption management, provides the readers with a description of the planning processes and delivers a detailed overview of the numerous aspects of airline disruption management. In the second part we report on experiences from a large research and development project on airline disruption management. Within the project the first prototype of a multiple resource decision support system at the operations control center in a major airline, has been implemented.

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Section: The Dar Model and Solution Approachmentioning

confidence: 99%

Section: The Dar Model and Solution Approachmentioning

confidence: 99%

See 1 more Smart Citation

Airline disruption management—Perspectives, experiences and outlook

Kohl¹,

Larsen

et al. 2007

Journal of Air Transport Management

Self Cite

212

130

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“…The Dedicated Aircraft Recovery module of the DESCARTES project is based on the methods described in the project. A summary of the findings can be found in [26].…”

Section: Aircraft Recoverymentioning

confidence: 99%

Disruption management in the airline industry—Concepts, models and methods

Clausen

Larsen

et al. 2010

Computers & Operations Research

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268

118

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The airline industry is notably one of the success stories with respect to the use of optimization based methods and tools in planning. Both in planning of the assignment of available aircraft to flights and in crew scheduling, these methods play a major role.Plans are usually made several months prior to the actual day of operation. As a consequence, changes often occur in the period from the construction of the plan to the day of operation. Optimization tools play an important role also in handling these changes.However, at the day of operation, no planning tool have been able to cope with the complexity of the re-planning given that the time span for proposing a solution is only a few minutes. Numerous suggestions for such subsystems have been put forward, but today no general tool is able to handle aircraft, crew, and passenger concurrently in a single system. Currently, there is a gap between the reality faced in operations control and the decision support offered by the commercial it-systems targeting the recovery process. Though substantial achievements have been made with respect to solution methods, and hardware has become much more powerful, even the most advanced prototype systems for integrated recovery have severe limitations.The current review accounts for the majority of subsystems mentioned in the literature in terms of the sub-problem addressed and the method used in each particular contribution. For each proposed system, also the computational experiments supporting the practical usability of the system is reported.

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“…Their complexity varies according to the number of constraints addressed. Typical scheduling problems in the airport domain are: aircraft scheduling (Bian, Burke, Jain & Kendall, 2005;El Moudani & Mora-Camino, 2000;Gurtner, Bongiorno, Ducci & Miccichè, 2016;Yan & Chen, 2008), ground crew scheduling (Clausen, 2011), disruption management (Pereira, Fadigas, Senna & Moret, 2011) (Løve, Sørensen, Larsen & Clausen, 2002), aircraft landing sequence scheduling (García Ansola, García Higuera, Pastor & Otamendi, 2011;Tavakkoli-Moghaddam, Yaghoubi-Panah & Radmehr, 2012) or personnel training scheduling (Brucker, Qu & Burke, 2011). Particularly in the domain of personnel scheduling, the most popular type of scheduling problem is the aircraft crew scheduling, while the problem of ground crew has mainly been neglected.…”

Section: Introductionmentioning

confidence: 99%