Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
The dynamical systems model of the simple genetic algorithm
Theoretical aspects of evolutionary computing
Modeling simple genetic algorithms
Evolutionary Computation
Fractal Dimension of Trajectory as Invariant of Genetic Algorithms
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
On Convergence of a Simple Genetic Algorithm
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Foundations of Global Genetic Optimization
Foundations of Global Genetic Optimization
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
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Convergence of genetic algorithms in the form of asymptotic stability requirements is discussed. Some tools to measure convergence properties of genetic algorithms are introduced. A classification procedure is proposed that is based on the following conjecture: the entropy and the fractal dimension of trajectories of genetic algorithms produced by them are quantities that can characterize the algorithms. The role of these quantities as invariants of the algorithm classes is discussed together with the compression ratio of points of genetic algorithms.