Genetic Algorithm Approach to Aircraft Gate Reassignment Problem

Gu, Yu; Chung, Christopher A.

doi:10.1061/(asce)0733-947x(1999)125:5(384)

Cited by 60 publications

(24 citation statements)

References 7 publications

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“…Pan and Wey [5] proposed an efficient gate reassignment algorithm GRASS for inverter minimization in post technology mapping. Gu and Chung [6] proposed a genetic algorithm approach to solving the gate reassignment problem in order to efficiently find minimum extra delayed time solutions. Wong et al [7] identified the causes, as well as the practical measurement of aircraft flight delays.…”

Section: Related Workmentioning

confidence: 99%

Study on an Airport Gate Reassignment Method and Its Application

Zhao

2017

Symmetry

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Bad weather, mechanical failures, air control, and crew members of the discomfort health are very likely to cause flight delays. If these events occur, decision-makers of airport operation must rediscover the flight schedules through reassigning gates to these flights, delaying flights, and canceling flights. Therefore, it is important to study the recovery strategy with the feasibility and the least cost for delayed flights and to improve the airport operation efficiency. In this paper, a mathematical model of gate reassignment based on the objectives of the loss of passengers, airport operating, and airlines, and the most important index of disturbance value of the gate reassignment for delayed flights is constructed. Then, the genetic algorithm (GA) and ant colony optimization (ACO) algorithm are combined in order to propose a two-stage hybrid(GAOTWSH) algorithm, which is used to solve the constructed mathematical model of gate reassignment for delayed flights. The test data from the operations of the one airport is used to simulate and demonstrate the performance of the constructed mathematical model of gate reassignment for irregular flights. The results show that the proposed GAOTWSH algorithm has better optimization performance and the constructed gate reassignment model is feasible and effective. The study provides a new idea and method for irregular flights.

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Section: Related Workmentioning

confidence: 99%

Study on an Airport Gate Reassignment Method and Its Application

Zhao

2017

Symmetry

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“…Two papers describe approaches for solving the gate reassignment problem. In [29] a genetic algorithm is proposed which efficiently calculates minimum extra delayed time schedules that are at least as effective as solutions generated by experienced gate managers. In [3] an integral minimum cost network flow model is introduced.…”

Section: State-of-the-art Algorithmmentioning

confidence: 99%

Flight gate scheduling: State-of-the-art and recent developments

Dorndorf

Drexl

Nikulin

et al. 2007

Omega

128

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This work has been supported by the German Science Foundation (DFG) through the grant "Planung der Bodenabfertigung an Flughäfen" (Dr 170/9-1, 9-2 and Pe 514/10-2). Terms of use: Documents in2 Corresponding author Abstract This paper surveys a large variety of mathematical models and up-to-date Solution techniques developed for solving a general flight gate scheduling problem that deals with assigning difFerent aircraft activities (arrival, departure and intermediate parking) to distinct aircraft stands or gates. The aim of the work is both to present various models and Solution techniques which are available in nowadays literature and to give a general idea about new open problems that arise in practise. We restrict the scope of the paper to flight gate Management without touching scheduling of ground handling Operations.Keywords: flight gate scheduling, assignment of aircraft activities to terminals, survey of models and algorithms.

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“…For example, the chromosome [2,3, 1, 3,2, 1] means that machine 1 has jobs 3 and 6, machine 2 has jobs 1 and 5, and machine 3 has jobs 2 and 4. This kind of structure is used by Gu and Chung (1999) for assigning gates to flights in airports. In their application, gates can be repeated but the ordering of flights is not part of the problem, since the flight schedule, even if changing due to delay, is an input and not an output.…”

Section: Genetic Algorithmsmentioning

confidence: 99%

“…At this time, we will use just the machine information in the gene (following Gu and Chung 1999) and then solve the TSP using the Doubling…”

Section: Genetic Algorithm (Ga)mentioning

confidence: 99%

Scheduling flexible flow lines with sequence-dependent setup times

Kurz

Askin

2004

European Journal of Operational Research

212

102

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This manuscript has t)een reproduced from the microfilm master UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be fipom any type of computer printer.The quality of this reproduction is dependent upon the quaiity of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print t)leedthrough, substandard margins, and improper alignment can adversely affect reproduction.In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion.Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand comer and continuing from left to right in equal sectnns with small overiaps.Photographs included in the original manuscript have been reproduced xerographically in this copy. Higher quality 6' x 9" black and white photographic prints are available for any photographs or illustrations appearing in this copy for an additional charge. Contact UMI directly to order. 3 STATEMENT BY AUTHORThis dissertation has been submitted in partial fulfillment of requirements for an advanced degree at The University of Arizona and is deposited in the University Library to be made available to borrowers under rules of the Library.Brief quotations from this dissertation are allowable without special permission, provided that accurate acknowledgment of source is made. Requests for permission for extended quotation from or reproduction of this manuscript in whole or in part may be granted by the copyright holder.

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Genetic Algorithm Approach to Aircraft Gate Reassignment Problem

Cited by 60 publications

References 7 publications

Study on an Airport Gate Reassignment Method and Its Application

Study on an Airport Gate Reassignment Method and Its Application

Flight gate scheduling: State-of-the-art and recent developments

Scheduling flexible flow lines with sequence-dependent setup times

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