Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Theoretical Computer Science - Special issue on evolutionary computation
The Simple Genetic Algorithm: Foundations and Theory
The Simple Genetic Algorithm: Foundations and Theory
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory
The simple genetic algorithm and the walsh transform: Part ii, the inverse
Evolutionary Computation
Theory of the simple genetic algorithm with α-selection
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Coarse graining selection and mutation
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
Theory of the simple genetic algorithm with α-selection, uniform crossover and bitwise mutation
WSEAS TRANSACTIONS on SYSTEMS
ICS'10 Proceedings of the 14th WSEAS international conference on Systems: part of the 14th WSEAS CSCC multiconference - Volume II
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Genetic algorithms are random heuristic search (RHS) algorithmswhich can be theoretically described with the help of a dynamicalsystem model. This model characterises the stochastic trajectory ofa population using a deterministic heuristic function and its fixedpoints. For practical problem sizes the determination of the fixedpoints is unfeasible even for the simple genetic algorithm (SGA).In this paper the novel intrinsic system model is introduced forthe genetic algorithm with α-selection and thecorresponding unique fixed point is determined. It is shown thatthis model is compatible with the equivalence relation imposed byschemata. In addition to the theoretical analysis experimentalresults are presented which confirm the theoreticalpredictions.