Otimização do roteamento de aeronaves com emparelhamento de tripulações para o transporte aéreo não regular

• Ano de defesa: 2024
• Autor(a) principal: Vieira, Thiago José dos Santos
• Orientador(a): Munari, Pedro
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia de Produção - PPGEP
• Palavras-chave em Português: Transporte aéreo não regular; Transporte aéreo sob demanda; Reprogramação de aeronaves; Emparelhamento de tripulações; Roteamento de aeronaves
• Palavras-chave em Inglês: Non-scheduled air transportation; Dial-a-flight problem; Aircraft recovery problem; Crew pairing; Aircraft routing
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA DE PRODUCAO::PESQUISA OPERACIONAL
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/20099

This dissertation addresses aircraft routing problems with crew pairing in the context of non-scheduled air transportation. These problems involve complex decisions in a highly dynamic and costly environment, where various civil aviation regulations must be followed. There is a lack of operations research literature on non-scheduled air transportation, and this type of service has significant differences from conventional (scheduled) transportation. Overall, this research covers real-world problems of two companies belonging to the sector, categorized in academia as a dial-a-flight problem and an aircraft recovery problem. The first refers to fractional ownership services with private aircraft sharing. In this scenario, the customer owns an equity part of aircraft managed by an airline, which entitles him/her to fly a certain amount of miles during the period. We proposed a detailed optimization model, MIP-based heuristics and an exact branch-and-price algorithm. The second problem refers to a rescheduling (recovery) of flights as a way to mitigate the damage arising from past disruptions (adverse weather conditions, mechanical failures, etc.). Given a flight timetable, we need to determine new departure times, redesign routes, reassign flights to different aircraft, and examine potential flight cancellations. We formulated network-flow, event-based and discrete-time models. Additionally, we developed tailored constructive and improvement heuristics. To verify the adequacy and coherence of the approaches, several experiments were performed with real-life data. In the first problem, all instances were solved optimally, and in the second, we were able to generate effective reschedules without canceling flights, in relatively short computing times.