Aircraft routing under uncertainty via robust optimization

Detalhes bibliográficos
Ano de defesa: 2022
Autor(a) principal: Campos, Rafael Ajudarte de
Orientador(a): Munari Junior, Pedro Augusto lattes
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
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
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/17073
Resumo: We address the robust vehicle routing problem (RVRP), focusing on the development of mathematical models and solution methods to incorporate uncertainties regarding travel times and demand, in traditional and practical variants. We are particularly interested in a practical variant, the aircraft routing problem, motivated by the real case of an on-demand airline company. Features such as heterogeneous fleet, time windows and maintenance requests are incorporated into robust optimization models that allow for the variability of uncertain parameters to be addressed. In particular, a new type of commodity flow model formulation, not yet explored in the robust optimization literature, even in classical variants, was developed for both the traditional RVRP and the aircraft routing problem. Moreover, we propose new compact models and tailored branch-and-cut methods considering different types of uncertainty sets, namely the cardinality constrained set and the single and multiple knapsack sets, using a recent approach based on dynamic programming to obtain the robust counterparts. The developed approaches were implemented and analyzed through computational experiments using instances from the literature as well as real-world data related to aircraft routing.