Intelligent Systems

ABOUT THE PROJECT

This group conducts basic and applied research to develop intelligent systems for solving problems across a wide range of application areas including optimization and logistics, ambient intelligence, web semantics, healthcare, forecasting and business intelligence, among others.

The investigation focuses on the development of innovative heuristic, metaheuristic and hyper-heuristic algorithms based on computational intelligence and other techniques to model and understand the complexity of the interaction between problems and algorithms with the intention to develop an automated and adaptable computational platform to efficiently solve a variety of real-world problems.

The group also explores strategies such as multi-agent systems, web semantics and data mining for integrating models and methodologies to trace a path toward intelligent organizations and more personalized systems.


Research lines

Nature-inspired systems
Context Intelligence

Leader

Hugo Terashima Marín

Core researchers

Alejandro Rosales Pérez
Iván Mauricio Amaya Contreras
José Carlos Ortiz Bayliss
Juan Arturo Nolazco Flores
Ramón Felipe Brena Pinero
Santiago Enrique Conant Pablos

Adjunct researchers

Francisco Javier Cantú Ortiz
Frumencio Olivas Alvarez
Héctor Gibrán Ceballos Cancino
Nimrod González Franco

RECENT PUBLICATIONS
Authors Title Publication
Herbert-Acero, J. F., Martínez-Lauranchet, J., Probst, O., Méndez-Díaz, S., Castillo- Villar, K., Valenzuela-Rendón, M. and Réthoré, P. A Hybrid Metaheuristic-Based Approach for the Aerodynamic Optimization of Small Hybrid. Wind Turbine Rotors, Mathematical Problems in Engineering, Vol. 2014, Article ID 746319, 18 pages, 2014. doi:10.1155/2014/746319
López-Camacho, E., Terashima-Marin, H., Ross, P. and Ochoa, G. A Unified Hyper- heuristic Framework for Solving Bin Packing Problems Expert Systems with Applications, Volume 41, Issue 15. 1 November 2014, pp 6876-6889
García-Ceja, E., Brena, R. F., Carrasco-Jiménez, J. C., Garrido, L. Long-term Activity Recognition from Wristwatch Accelerometer Data Sensors 2014, 14, 22500-22524; doi:10.3390/s141222500
Ortiz-Bayliss, J. C., Moreno-Scott, J. H., and Terashima-Marin, H. Automatic Generation of Heuristics for Constraint Satisfaction G. Terrazas et al. (eds.) Nature-inspired Cooperative Strategies for Optimisation (NICSO 2013), Studies in Computational Intelligence 512, 2014, pp315-327, Springer