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Estatística
Título: PERSONNEL OPTIMAL LOCATIONALLOCATION MODEL: CASE STUDY AT ANAC
Autor: CHRISTOPHER FEITOSA DA SILVA
Colaborador(es): SILVIO HAMACHER - Orientador
JANAINA FIGUEIRA MARCHESI - Coorientador
Catalogação: 19/MAI/2022 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=59090&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=59090&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.59090
Resumo:
Over the last years, Research Operations development has become fundamental for Aviation Industry. In Brazil, the agency responsible for Civil Aviation inspection is the National Agency of Civil Aviation (ANAC). This work aims the development of an optimal personnel location-allocation model and application in a case study at ANAC in Safety Oversight context. One Literature Review has been done for gaps identification and to find the most recent solution techniques for facility location problems. The research objective has been achieved, and the proposed case study has validated the model. The model located 31 percent of ANAC personnel in Brazilian Southeast Region, 25 percent in Northeast Region, 17 percent in North Region, 17 percent in South Region and 10 percent in Central-West Region; decreasing in 66 percent the total quantity of allocated inspectors. A capacities matrix has been constructed with model results; decision-makers can analyze the optimal distribution of personnel capacities in each facility. Finally, a sensitivity analysis has been done to test the model flexibility, which prove the model is efficient for real problems application.
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