Universidade Federal do Ceará
Mestrado Acadêmico em Modelagem e Métodos Quantitativos

The Academic Master’s program on Modeling and Quantitative Methods (PPGMMQ) of the Federal University of Ceará (UFC) has a single concentration area, called Modeling and Quantitative Methods, which covers the development and application of quantitative models and methods for the study and solution of complex problems that require a multi or interdisciplinary approach involving mathematical, statistical or computational techniques.

     The description and analysis of problems through quantitative models are widespread activities. One of the biggest difficulties, however, in this process is the fact that understanding the problem and translating it into mathematical expressions often requires, especially in the case of complex problems, the integrated work of professionals with knowledge in the domain of application  and in mathematical modeling. These professionals need to establish collaboration at different levels, from the use of a clear language to the definition of an evaluation of the results obtained that actually reflects the expectations of the areas involved. Interdisciplinary training is of great value in these contexts.

     This concentration area is divided into two research lines:

• Modeling and Quantitative Analysis.
• Computational Intelligence and Optimization.

The main common feature of these research lines, which are part of the Multidisciplinary/Interdisciplinary area, is that the problems studied have motivations and require skills that go beyond the fields of Computing, Statistics, and Mathematics, as it is necessary to interact with other areas of knowledge to achieve appropriate modeling and satisfactory solutions. It is worth noting that the faculty of this graduate program is trained across all areas of knowledge required to advance understanding in the interdisciplinary scope of the mentioned subjects.
 

RESEARCH LINES

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Modeling and Quantitative Analysis

This line of research aims to act in the modeling of complex systems, which involve applications in the areas of physics, chemistry, engineering, biological systems, social behavior, among others. It is expected to develop statistical and mathematical models that guarantee forecasts, trend indicators and treatment of uncertain/inaccurate data, which can assist decision making and contribute to the development of technological innovations. One direction of action in this research line is the study of random phenomena, when two possible approaches are the following: Parametric and Non-Parametric Inference. Another direction is related to the mathematical modeling of phenomena (physical, chemical, biological, social, etc.) that can be described by mathematical models.

Computational Intelligence and Optimization

This research line aims to effectively develop and apply advanced computation methods and techniques, using as a basis mathematical models representative of highly complex problems. The methodologies employed, in an integrated manner, come from areas such as computational intelligence, discrete and continuous optimization, and high performance computing. The growing challenge of finding optimized solutions to real problems arising from companies/industries, aiming to add value to their products, has inspired the development of methods based on more efficient computational intelligence and optimization. This line proposes to address optimization problems, dealing with issues such as obtaining theoretical properties, developing and implementing solution algorithms and their application to real problems, dedicating themselves to the exact or approximate resolution of these problems.