Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Evolutionary Neural Networks for Nonlinear Dynamics Modeling
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Fuzzy Recombination for the Breeder Genetic Algorithm
Proceedings of the 6th International Conference on Genetic Algorithms
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
Effective Learning with Heterogeneous Neural Networks
Neural Information Processing
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A large number of practical optimization problems involve elements of quite diverse nature, described as mixtures of qualitative and quantitative information, and whose description is possibly incomplete. In this work we present an extension of the breeder genetic algorithm that represents and manipulates this heterogeneous information in a natural way. The algorithm is illustrated in a set of optimization tasks involving the training of different kinds of neural networks. An extensive experimental study is presented in order to show the potential of the algorithm.