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- Pedro Larrañaga, J. A. Lozano, +4 authors Ramón Sagarna
- 2004

Training artificial neural networks is a complex task of great practical importance. Besides classical ad-hoc algorithms such as backpropagation, this task can be approached by using evolutionary computation, a highly configurable and effective optimization paradigm. This chapter provides a brief overview of these techniques, and shows how they can be… (More)

- Eloísa F A Almeida, Mar Cabeza, +9 authors Fatos Xhafa
- 2002

The mallba project tackles the resolution of combinatorial 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)

A hybrid genetic algorithm based in local search is described. Local optimisation is not explicitly performed but it is embedded in the exploration of a search metaspace. This algorithm is applied to a NP-hard problem. When it is compared with other GA-based approaches and an exact technique (a branch & bound algorithm), this algorithm exhibits a better… (More)

- Enrique Alba, Francisco Almeida, +7 authors Jordi Petit
- Parallel Computing
- 2006

The MALLBA project tackles the resolution of combinatorial optimization problems using generic algorithmic skeletons implemented in C++. A skeleton in the MALLBA library implements an optimization method in one of the three families of generic optimization techniques offered: exact, heuristic and hybrid. Moreover, for each of those methods, MALLBA provides… (More)

- Carlos Cotta
- IWANN
- 2003

This work explores different evolutionary approaches to Protein Structure Prediction (PSP), a highly constrained problem. These are the utilization of a repair procedure, and the use of evolutionary operators whose functioning is closed in feasible space. Both approaches rely on hybridizing the evolutionary algorithm (EA) with a backtracking algorithm. The… (More)

The generic denomination of ‘Memetic Algorithms’ (MAs) is used to encompass a broad class of metaheuristics (i.e. general purpose methods aimed to guide an underlying heuristic). The method is based on a population of agents and proved to be of practical success in a variety of problem domains and in particular for the approximate solution of NP… (More)

- Ferrante Neri, Carlos Cotta
- Swarm and Evolutionary Computation
- 2012

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)

- José E. Gallardo, Carlos Cotta, Antonio J. Fernández
- IEEE Trans. Systems, Man, and Cybernetics, Part B
- 2007

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)

- Carlos Cotta, Jorge Muruzábal
- PPSN
- 2002

Bayesian networks (BNs) constitute a useful tool to model the joint distribution of a set of random variables of interest. This paper is concerned with the network induction problem. We propose a number of hybrid recombination operators for extracting BNs from data. These hybrid operators make use of phenotypic information in order to guide the processing… (More)