Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
Variable-Dimensional Optimization with Evolutionary Algorithms Using Fixed-Length Representations
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Variable Length Representation in Evolutionary Electronics
Evolutionary Computation
Tuning of a neuro-fuzzy controller by genetic algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper describes a new evolutionary methodology aimed at optimizing various and heterogeneous data in common evolution. The representation of solutions uses mixed-integer genotypes and variable-length chromosomes to face a complex problem of task decomposition and high-level control generation. A memory operator is introduced to face convergency uncertainties issued from the irregularities of both discontinuous evaluation function and heterogeneous solution representation. The stability of the evolutionary algorithm is analyzed with dimension changes in the optimization problem.