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Agent-Based Evaluation of the Airplane Boarding Strategies’ Efficiency and Sustainability

Camelia Delcea (), Liviu-Adrian Cotfas () and Ramona Paun ()
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Camelia Delcea: Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, Bucharest 010552, Romania
Liviu-Adrian Cotfas: Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, Bucharest 010552, Romania
Ramona Paun: School of Business & Technology, Webster University, Bangkok 10120, Thailand

Sustainability, 2018, vol. 10, issue 6, 1-26

Abstract: The airplane turnaround time costs money to the airline companies and, over the years, it has been determined that the best way to reduce it is by using efficient boarding strategies. Many boarding strategies have been proposed but a consensus as to which is the best method has not been reached yet. The aim of this paper is to gather and test all these strategies considering the same initial conditions in order to help airline companies identify the best boarding strategy. Minimizing the costs not only contributes to airlines’ sustainability and long-term performance, but also influences their ticketing policy, and has an impact on their customers’ choices. Moreover, airports can benefit from the fact that the airline companies are optimizing their boarding strategies as they can extend the number of services offered to more airlines during one day without investing in new infrastructure. Thus, this paper considers 24 boarding strategies and builds a configurable agent-based model using NetLogo 6.0.2 to perform different simulations. The results are analysed using grey systems theory considering the aircraft dimensions, aircraft occupancy and whether or not passengers are carrying hand luggage that may need storage.

Keywords: airplane boarding strategies; agent-based modelling; NetLogo 6.0.2; grey systems theory; efficiency evaluation; sustainability (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2018
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