Research lines
Optimization and Computational Intelligence
This research line aims to develop Computational Intelligence methods to solve optimization problems arising from various areas of Production Engineering. It encompasses a range of techniques inspired by biological or physical systems, such as genetic algorithms, artificial neural networks, and simulated annealing, among others. Researchers in this area develop heuristic and metaheuristic methods to solve complex problems from real-world systems within acceptable computational time.
Modeling and Development of Decision Support Systems
This research line aims to develop computational models to support decision-making processes in various contexts within the broad field of Production Engineering. It encompasses different modeling techniques, data analysis methods, and decision theory approaches to create systems that assist planners and managers of real-world systems in their decision-making. The developed systems should enable data analysis, simulation of different operational scenarios, and the ranking of multiple alternatives to be considered by decision-makers. In addition to creating new methodologies, researchers in this line also focus on implementing efficient and accessible decision support systems, considering aspects such as usability, integration with existing information systems, and the interpretability of the results obtained.
