Grey clustering of the variations in the back-to-front airplane boarding method considering COVID-19 flying restrictions

被引:14
作者
Delcea, Camelia [1 ]
Cotfas, Liviu-Adrian [1 ]
Milne, R. John [2 ]
Xie, Naiming [3 ]
Mierzwiak, Rafal [4 ]
机构
[1] Bucharest Univ Econ Studies, Fac Econ Cybernet Stat & Informat, Bucharest, Romania
[2] Clarkson Univ, David D Reh Sch Business, Potsdam, NY USA
[3] Nanjing Univ Aeronaut & Astronaut, Coll Econ & Management, Nanjing, Peoples R China
[4] Poznan Univ Tech, Fac Engn Management, Poznan, Poland
关键词
Grey analysis; Grey clustering; Agent-based modelling; Airplane boarding; Back-to-front; One-door boarding; COVID-19; Social distancing;
D O I
10.1108/GS-11-2020-0142
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Purpose The airline industry has been significantly hit by the occurrence of the new coronavirus SARS-CoV-2, facing one of its worst crises in history. In this context, the present paper analyses one of the well-known boarding methods used in practice by the airlines before and during the coronavirus outbreak, namely back-to-front and suggests which variations of this method to use when three passenger boarding groups are considered and a jet bridge connects the airport terminal with the airplane. Design/methodology/approach Based on the importance accorded by the airlines to operational performance, health risks, and passengers' comfort, the variations in three passenger groups back-to-front boarding are divided into three clusters using the grey clustering approach offered by the grey systems theory. Findings Having the clusters based on the selected metrics and considering the social distance among the passengers, airlines can better understand how the variations in back-to-front perform in the new conditions imposed by the novel coronavirus and choose the boarding approach that better fits its policy and goals. Originality/value The paper combines the advantages offered by grey clustering and agent-based modelling for offering to determine which are the best configurations that offer a reduced boarding time, while accounting for reduced passengers' health risk, measured through three indicators: aisle risk, seat risk and type-3 seat interferences and for an increased comfort for the passengers manifested through a continuous walking flow while boarding.
引用
收藏
页码:25 / 59
页数:35
相关论文
共 75 条
[1]  
Alitalia, 2020, FLYING SAFELY
[2]   A dynamic cellular automaton model for evacuation process with obstacles [J].
Alizadeh, R. .
SAFETY SCIENCE, 2011, 49 (02) :315-323
[3]  
[Anonymous], 2020, The Guardian
[4]  
[Anonymous], DELTA NEWS HUB
[5]  
[Anonymous], 2020, Future Travel Experience
[6]  
Ash L ., 2020, SIMPLE FLYING
[7]  
Audenaert J., 2009, P 21 BEN C ART INT, P3
[8]   Analysis of Airplane Boarding Times [J].
Bachmat, Eitan ;
Berend, Daniel ;
Sapir, Luba ;
Skiena, Steven ;
Stolyarov, Natan .
OPERATIONS RESEARCH, 2009, 57 (02) :499-513
[9]  
Barnett A, 2020, PUBLIC GLOBAL HLTH, DOI [DOI 10.1101/2020.07.02.20143826, 10.1101/2020.07.02.20143826]
[10]   A linear programming approach for aircraft boarding strategy [J].
Bazargan, Massoud .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 183 (01) :394-411