Acompanhamento preventivo e agendamento de pacientes com câncer utilizando programação inteira e matroides

Abstract

Within the context of the growing number of cancer cases globally, optimization models can help physicians and health professionals to ensure the best use of available resources. This paper presents two constrained optimization models, one for the prioritization of patients for preventive follow-up of cervical cancer and the other for the scheduling of oncology patients in treatment, both using integer programming and AMPL. In addition, a performance analysis of a patient scheduling algorithm using matroids is presented. The models were tested on randomly generated instances, resulting in a list of hypothetical priority patients for performing tests, as well as a list of patients scheduled in their respective shifts.