Eduardo Krempser

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Bilevel programming problems are characterized by two optimization problems which are hierarchically related, where to each feasible upper level solution an optimal solution in the lower level problem must be associated. These problems appear in many practical applications, and a variety of solution techniques can be found in the literature. In this paper,(More)
Bilevel programming is used to model decentralized problems involving two levels of decision makers that are hierarchically related. Those problems, which arise in many practical applications, are recognized to be challenging. This paper reports a Differential Evolution (DE) method assisted by a surrogate model to solve bilevel programming problems (BLPs).(More)
OBJECTIVE This paper describes NICeSim, an open-source simulator that uses machine learning (ML) techniques to aid health professionals to better understand the treatment and prognosis of premature newborns. METHODS The application was developed and tested using data collected in a Brazilian hospital. The available data were used to feed an ML pipeline(More)
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