Here are my main research topics
I have interest in operations research, optimization, evolutionary algorithms, and experiments planning. My main research topic consists in the development of mathematical models and algorithms for mixed-integer linear optimization problems. Such problems are solved by exact methods, such as branch-and-bound based algorithms, dynamic programming, cutting-plane methods, or other advanced decomposition methods. Besides, heuristic algorithms, such as local search-based techniques, evolutionary algorithms and lagrangian heuristics, are also used to get good solutions for hard instances. Such methods and algorithms are generally applied to solve a class of problems, or a specific problem of great practical relevance.
I also have interest in studying evolutionary algorithms, researching new operators for different problem's classes. Besides, another interesting research field is to study the population dynamics of such algorithms, characterizing how individuals (solutions) interact with each other by means of the genetic operators.
Computational intelligence is a set methodologies and approaches that addresses complex real-world problems to which mathematical or traditional modelling can be useless. Such problems might contain some uncertainties during the process, or the process might simply be stochastic in nature. Indeed, many real-life problems cannot be translated into binary language for computers to process it. Computational Intelligence therefore provides solutions for such problems.
Evolutionary algorithms, mathematical modelling, heuristics and metaheuristics, neural networks, and fuzzy logic are the main approaches employed in computational intelligence, among other stochastic methods.
Do you have an interesting work, project or idea? It is on my interest fields? Let's work together!