Bioinspired Group @ ArTeCs

* New Book: “Parallel Architectures and Bio-inpired Algorithms” Studies in Computational Intelligence, Springer

Within the ArTeCs group, the objectives of this research area is the application of ideas taken from parallel, cluster and grid computing to algorithms inspired by nature and the application of Bioinspired Algorithm for solving optimization problems with special emphasis on parallel architectures and embedded systems optimization problems.

In particular, we develop our research in the following subjects:

• Dynamic Memory Manager Optimization (2009 - ...)

• Optimization of Dynamic Data Types (DDTs) in embedded systems (2007 - 2009)

• Improving SMT Performance: an Application of Genetic Algorithms to Configure Resizable Caches

• Parallel memetic approach to the problem of workforce distribution in dynamic multi-agent systems

• Multiobjective Optimization of Technical Market Indicators

• Bivariate empirical and n-variate Archimedean copulas in Estimation of Distribution Algorithms