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A decision support system for risk reduction in pandemic spread based on the management of passenger air traffic
Author(s) -
Peña Gabriel A.,
Mateos Alfonso,
JiménezMartín Antonio,
Sanchis Raúl G.
Publication year - 2025
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/itor.13576
Subject(s) - pandemic , reduction (mathematics) , covid-19 , decision support system , air traffic control , risk analysis (engineering) , risk management , air traffic management , computer science , aeronautics , transport engineering , operations research , business , engineering , medicine , aerospace engineering , disease , geometry , mathematics , finance , pathology , artificial intelligence , infectious disease (medical specialty)
Abstract A significant factor in the early spread of pandemics at an international level is passenger air traffic. Decisions regarding passenger air traffic could assist different countries in managing the risk of pandemic importation. However, flight cancelations would have economic and social impacts, leading to a multiobjective optimization problem. A decision support system (DSS) for reducing the risk of pandemic spread by managing passenger air traffic is introduced. This DSS enables decision makers (DMs) to parameterize the problem to be solved (time period, country of analysis, the percentage of targeted risk reduction, etc.), quantify DM preferences using ordinal information on the objectives, solve the resulting binary single‐objective optimization problem using a binary particle swarm optimization metaheuristic, and visualize the optimal solution. The methodology is illustrated using the example of Spain with 38 national airports and 5000 international connections, involving 9678 flights within the time period from September 24 to October 7, 2020.