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The mallba project tackles the resolution of combinato-rial optimization problems using algorithmic skeletons implemented in C ++. mallba offers three families of generic resolution methods: exact, heuristic and hybrid. Moreover, for each resolution method, mallba provides three different implementations: sequential, parallel for local area networks, and(More)
An evolutionary approach to the design of fuzzy logic controllers is presented in this paper. We propose the use of the genetic programming paradigm to evolve fuzzy rule-bases (internally represented as type-constrained syntactic trees). This model has been applied to the cart-centering problem, although it can be readily extended to other problems. The(More)
Branch-and-bound (BnB) and memetic algorithms represent two very different approaches for tackling combinatorial optimization problems. However, these approaches are compatible. In this correspondence, a hybrid model that combines these two techniques is considered. To be precise, it is based on the interleaved execution of both approaches. Since the(More)
Diverse methods have been developed to generate terrains under constraints to control terrain features, but most of them use strict restrictions. However, there are situations were more flexible restrictions are sufficient, such as ensuring that terrains have enough accessible area, which is an important trait for video games. The Genetic Terrain Program(More)
We deal with two important problems in pattern recognition that arise in the analysis of large datasets. While most feature subset selection methods use statistical techniques to preprocess the labeled datasets, these methods are generally not linked with the combinatorial properties of the final solutions. We prove that it is N P −hard to obtain an(More)