Model to Reduce Airline Schedule Disturbances

Teodorović, Dušan; Stojković, Goran

doi:10.1061/(asce)0733-947x(1995)121:4(324)

Cited by 87 publications

(26 citation statements)

References 3 publications

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“…In a paper by Teodorovic and Stojkovic [41] the generation of a solution for several resources is considered. This is the first effort to consider the integration of several resources published in the literature.…”

Section: Recovery Of Multiple Resourcesmentioning

confidence: 99%

Airline disruption management—Perspectives, experiences and outlook

Kohl¹,

Larsen

et al. 2007

Journal of Air Transport Management

209

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: Recovery Of Multiple Resourcesmentioning

confidence: 99%

Airline disruption management—Perspectives, experiences and outlook

Kohl¹,

Larsen

et al. 2007

Journal of Air Transport Management

209

130

View full text Add to dashboard Cite

show abstract

“…In "Model to Reduce Airline Schedule Disturbances" [45] from 1995, Teodorovic and Stojković further extend their model to include also crew considerations. The model proposed still solves the problem individually for each aircraft type.…”

Section: Aircraft Recoverymentioning

confidence: 99%

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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“…The literature on airline schedule recovery includes Carlson [8], Lettovský [25], and Teodorović and Stojković [32]. These research efforts develop exact optimization models that reschedule flight legs and reroute aircraft by minimizing rerouting and cancellation costs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Since vehicle breakdowns have not been explicitly considered in train rescheduling [11,26], dynamic VSP [22], or dynamic VRP [16,17,21,23,31,34], most of results available are not directly applicable to our problem. Although aircraft breakdown is considered in some studies of airline operations recovery, most of the available algorithms [8,25,29,32] involve a small number of trips and aircrafts. The majority of these algorithms are computationally intensive, requiring thousands of CPU seconds to solve recovering instances involving hundreds of trips and dozens of planes.…”

Section: Literature Reviewmentioning

confidence: 99%

The vehicle rescheduling problem: Model and algorithms

Mirchandani

Borenstein

2007

Networks

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When a vehicle on a scheduled trip breaks down, one or more vehicles need to be rescheduled to serve the customers on that trip with minimum operating and delay costs. The problem of reassigning vehicles in real-time to this cut trip as well as to other scheduled trips with given starting and ending times, is referred to as the vehicle rescheduling problem (VRSP). This paper considers modeling, algorithmic, and computational aspects of the single-depot VRSP. The paper formulates a model for this problem and develops several fast algorithms to solve it, including parallel synchronous auction algorithms. The concept of the common feasible network (CFN) is introduced to find a good set of initial "prices" for speeding up the auction algorithm. Computational experiments on randomly generated problems are described. Computational results show that, for small problems, all of the developed algorithms demonstrate very good computational performances. For large problems, parallel CFN-based auction algorithms provide the optimal solution with much smaller computation times.

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Model to Reduce Airline Schedule Disturbances

Cited by 87 publications

References 3 publications

Airline disruption management—Perspectives, experiences and outlook

Airline disruption management—Perspectives, experiences and outlook

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

The vehicle rescheduling problem: Model and algorithms

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