Fran Sérgio Lobato
Professor
Chemical Engineering
Federal University of Uberlandia(UFU)
Brazil
Biography
Fran Sérgio Lobato Born in Araguari-MG. He obtained his Chemical Engineering Degree in 2002 at the Faculty of Chemical Engineering of the Federal University of Uberlândia, where he concluded his Master's Dissertation, which focused on the Algorithmic-Differential Optimum Control Theory in 2004. He concluded his PhD Thesis in 2008 in the Faculty of Mechanical Engineering of the Federal University of Uberlândia, where he worked with the Algorithm of Differential Evolution applied to multi-objective problems. He is currently an associate professor at the Federal University of Uberlândia. Its areas of interest are:
Research Interest
i) Algebraic-Differential Supervisory Control with Floating Index, with applications in diverse areas, mainly in biotechnological processes and medicine for the development of strategies for the treatment of carcinomas; ii) Classical Optimization Methods, Heuristic, Structural and Bio-Inspired in Nature; iii) Updating parameters of evolutionary algorithms using Chaotic Search Models and the Convergence Rate Concept based on the Concept of Homogeneity of Population; iv) Inverse Problems; v) Design of Multi-objective Engineering Systems; vi) Treatment of Robust Optimization Problems and vii) Treatment of Optimization Problems with Reliability.
Publications
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LOBATO, FRAN SÉRGIO ; MACHADO, VINICIUS SILVÉRIO; STEFFEN, VALDER. Determination of an optimal control strategy for drug administration in tumor treatment using multi-objective optimization differential evolution. Computer Methods and Programs in Biomedicine (Print), v. 131, p. 51-61, 2016.
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LOBATO, FS ; SILVA, MA. Robust Multiobjective Optimization Applied for the Preparation of Bone Alveoli Used in Dental Implants. Master Magazine, v. 1, p. 1-15, 2016.
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LOBATO, FRAN S .; GONÇALVES, MATHEUS S.; JAHN, BARBARA; CAVALINI, ALDEMIR AP. ; STEFFEN, VALDER. Reliability-Based Optimization Using Differential Evolution and Inverse Reliability Analysis for Engineering System Design. Journal of Optimization Theory and Applications, v. 1, p. 1-33, 2017.