Model for operational daily airline scheduling

Teodorović, Dušan; Stojković, Goran

doi:10.1080/03081069008717431

Cited by 111 publications

(40 citation statements)

References 2 publications

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“…"Model for Operational Daily Airline Scheduling" [44] from 1990 by Teodorovic and Stojković extends the previous work described above to consider also airport curfews. Nodes in the network represent flights to be flown and are grouped in stages.…”

Section: Aircraft Recoverymentioning

confidence: 75%

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

Clausen

Larsen

et al. 2010

Computers & Operations Research

264

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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Section: Aircraft Recoverymentioning

confidence: 75%

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

Clausen

Larsen

et al. 2010

Computers & Operations Research

264

118

View full text Add to dashboard Cite

show abstract

“…The proposed model is solved exactly by a branch and bound (B&B) method. The concept is further developed in Teodorovic et al [14] where the same problem, i.e., an aircraft shortage, is considered. A lexicographic model allowing cancellations, delays and swaps is solved heuristically with an algorithm based on dynamic programming.…”

Section: Introductionmentioning

confidence: 99%

“…The problem is solved sequentially and heuristically by first making a new crew schedule after which a new aircraft schedule is created and checked for maintenance feasibility. The same lexicographic objectives as in [14] are used, although no mathematical model is presented. Still, less serious perturbations are considered but beside aircraft shortages that were considered in the earlier papers, canceled crew and changes in planned departure time are treated as well.…”

Section: Introductionmentioning

confidence: 99%

The flight perturbation problem

Andersson

Värbrand

2004

Transportation Planning and Technology

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Airlines spend considerable time, effort and financial resources on planning. It is essential to create a competitive timetable and construct a fleet and a crew schedule that utilizes these resources to the maximum. Unfortunately, it is all too common that an airline is faced with the necessity of reconstructing their schedules due to some unforeseen event, e.g., an aircraft breakdown or a crew member that is indisposed. In this paper, an application that can help airlines solve the complex problem of reconstructing aircraft schedules is presented. A mixed integer multicommodity flow model with side constraints is developed and further reformulated into a set packing model using the Dantzig-Wolfe decomposition. Cancellations, delays and aircraft swaps are used to resolve the perturbation, and the model ensures that the schedule returns to normal within a certain time. Two column generation schemes for heuristically solving the model are tested on real problem data obtained from a Swedish domestic airline. The computational tests show that the application is capable of presenting high quality solutions in a few seconds and therefore can be used as a dynamic decision support tool by the airlines.

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“…Teodorovic and Stojkovic [144] proposed a lexicographical model meant to minimize the number of cancellations first and, at the level of minimum cancellations, minimize total passenger delays. The model takes into account airport curfew times.…”

Section: Irregular Operations Controlmentioning

confidence: 99%

Optimization Applications in the Airline Industry

Yang

1998

Handbook of Combinatorial Optimization

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Model for operational daily airline scheduling

Cited by 111 publications

References 2 publications

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

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

The flight perturbation problem

Optimization Applications in the Airline Industry

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