Aircraft Stand Assignment to Minimize Walking

Chen

2016

Int. J. Autom. Comput.

Abstract:This paper reviews existing approaches to the airport gate assignment problem (AGAP) and presents an optimization model for the problem considering operational safety constraints. The main objective is to minimize the dispersion of gate idle time periods (to get robust optimization) while ensuring appropriate matching between the size of each aircraft and its assigned gate type and avoiding the potential hazard caused by gate apron operational conflict. Genetic algorithm is adopted to solve the problem. An illustrative example is given to show the effectiveness and efficiency of the algorithm. The algorithm performance is further demonstrated using data of a terminal from PEK airport.

Section: Solution Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Robust assignment of airport gates with operational safety constraints

Chen

2016

Int. J. Autom. Comput.

“…Additionally, the single time slot GAP can be stated as a linear integer program [1] with the objective of minimizing the total Walking distance for arriving and departing passengers. In [36] an integer program with an extended objective function that takes into account transfer of passengers is proposed.…”

Section: Types Of Objectivesmentioning

confidence: 99%

“…Babic et al [1] use branch and bound, with some enhancements to accelerate computation, in order to determine an optimal Solution of the GAP. The objective is to reduce the number of passengers who have to walk maximum distances -at the price that more passengers have to walk the minimum distances, compared to random aircraft position assignment.…”

Section: State-of-the-art Algorithmmentioning

confidence: 99%

“…The objective is to reduce the number of passengers who have to walk maximum distances -at the price that more passengers have to walk the minimum distances, compared to random aircraft position assignment. Contrary to [1] Mangoubi and Mathaisel [36] take into account transfer passengers. Moreover, they use the LP relaxation and greedy heuristics to solve the GAP.…”

Section: State-of-the-art Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

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

Dorndorf

Drexl

Nikulin

et al. 2007

Omega

128

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.

J of Advced Transportation

Multi‐objective airport gate assignment problem in planning and operations

Kumar

Bierlaire

2013

We consider the assignment of gates to arriving and departing flights at a large hub airport. It is considered to be a highly complex problem even in planning stage when all flight arrivals and departures are assumed to be known precisely in advance. There are various considerations that are involved while assigning gates to incoming and outgoing flights (such a flight pair for the same aircraft is called a turn) at an airport. Different gates have restrictions, such as adjacency, last-in-first-out gates and towing requirements, which are known from the structure and layout of the airport. When optimizing the gate assignment costs, we consider different, and often, conflicting objectives such as maximization of gate rest time between two turns, minimization of the cost of towing an aircraft with a long layover, minimization of overall costs that includes penalization for not assigning preferred gates to certain turns, among others.One of the major contributions of this paper is to mathematically model all these features that are observed in the real-life. Further we also attempt to study the problem in both planning and operations mode, which has rarely been accomplished in the literature. For planning, we sequentially introduce different objectives to our gate assignment problem -such as maximization of connection revenues, minimization of zone usage at airport and maximization of schedule reliability -and include them to the model along with the relevant constraints. For operations, the main consideration is recovery of schedule by minimizing schedule variations and maintaining feasibility in the event of major disruptions. Additionally the operations models must have very, very short run times, in the order of a few seconds.These models are then applied to a real airline at one of its most congested hubs. Implementation is done using OPL and computational results for actual data sets are reported. For the planning mode, analyst perception of weights for the different objectives in the multiobjective model is used wherever actual dollar value of the objective coefficient is not available. The results are also reported for large, reasonable changes in objective function coefficients. For the operations mode, flight delays are simulated and the performance of the model studied. The final results indicate that it is possible to solve even large instances of real-life problems to optimality within short run times with conventional continuous time assignment model.