Uma proposta de solução para o aircraft recovery problem de companhias aéreas regulares de pequeno porte.

• Ano de defesa: 2015
• Autor(a) principal: Dias, Glend Kleiser Gouveia
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraíba; Brasil; Engenharia de Produção; Programa de Pós-Graduação em Engenharia de Produção; UFPB
• Palavras-chave em Português: Gestão das interrupções; Disruption management; Aviação civil; Aircraft Recovery Problem; Otimizacão; Civil aviation; Optimization; ENGENHARIAS::ENGENHARIA DE PRODUCAO
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/tede/8151

The airlines that operate regular ights de ne in advance the airports to be operated and the landing and takeo schedule of its aircraft. This scheduling is likely to su er interruptions causing nancial losses due to delays and/or cancellations of ights. In these situations, the airlines usually use the experience of their professionals and seek to minimize the impacts by relocating the aircraft, crew and then passengers. There is no guarantee that such method will lead to good results from an economic point of view, especially in periods of high demands of passengers. Due to this di culty, several authors have studied the Airline Recovery Problem using di erent optimization techniques. This problem is basically composed of three sub-problems: Aircraft Recovery Problem (ARP), Crew Recovery Problem (CRP) and Passenger Recovery Problem (PRP). In order to de- ne the new least-cost aircraft scheduling of a Brazilian airline (in operation interruption situations) due to delays and/or cancellations of ights, this research presents an ARP solution proposal starting from the representation of ights through a network time-space and mathematical modeling analogous to the minimum cost ow problem. To analyze the ARP, data was used from a Brazilian airline for building the time-space networks with bands of 30, 20 and 15 minutes, and 100 instances were utilized to simulate the unavailability of up to 3 aircraft on di erent nodes of such networks. The solutions based on these bands were solved via Integer Linear Programming and with average improvements of 38.24%, 40.44% and 41.15%, respectively, with respect to the trivial solutions. The band of 15 min was more appropriate because it provided a more realistic analysis of takeo s and landings events and resulted in a greater di erence, on average, between the optimal solutions and the trivial ones. Other 95 instances were tested for a time-space network with 15 min band and a spare aircraft located at the busiest airport. In this case the results were 38.68% better than the situation without a spare aircraft, but it was not conclusive because an economic feasibility analysis on the acquisition and deployment of a new aircraft in the eet must be performed.