Priorização de projetos de construção em instituição pública de ensino superior com enfoque multicritério

• Ano de defesa: 2025
• Autor(a) principal: Mota, Rayara Falkenstins Gois Mendes
• Orientador(a): Campos, Vanessa Ribeiro
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Área do conhecimento CNPq: CNPQ::ENGENHARIAS::ENGENHARIA CIVIL
• Link de acesso: http://repositorio.ufc.br/handle/riufc/82347

High costs and limited financial resources for infrastructure development in public institutions require the establishment of priorities for project execution. In this context, optimizing the use of available resources is essential to ensure their most effective allocation. The Federal University of Ceará (UFC), as a federal public institution, faces this challenge and requires a structured process for project selection and prioritization. This study proposes the application of a hybrid model based on Multi-Criteria Decision Analysis (MCDA) methods. Initially, the Analytic Hierarchy Process (AHP) is used to define the weights of the decision criteria, followed by the application of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank the alternatives according to the established weights. The proposed model stands out due to its simplicity and ease of understanding for decision-makers, contributing to a more rational and efficient project selection. The analysis of results indicates that the model enables satisfactory prioritization of alternatives, offering a methodology aligned with institutional objectives. Based on well-defined technical criteria, this approach supports more efficient allocation of public resources, resulting in a project portfolio better aligned with organizational interests. Thus, the model helps managers focus their efforts on projects with greater feasibility for completion, promoting rational use of time and available resources while serving the public interest. Although developed for a Federal Institution of Higher Education, the method can be adapted and applied to other organizations that require project selection based on multiple criteria, beyond purely quantitative measures.