An analysis of reproduction and crossover in a binary-coded genetic algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Fractals everywhere
The Simple Genetic Algorithm: Foundations and Theory
The Simple Genetic Algorithm: Foundations and Theory
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Models of Genetic Algorithms
Simple genetic algorithms with linear fitness
Evolutionary Computation
General cardinality genetic algorithms
Evolutionary Computation
The simple genetic algorithm and the walsh transform: Part i, theory
Evolutionary Computation
The simple genetic algorithm and the walsh transform: Part ii, the inverse
Evolutionary Computation
Schemata evolution and building blocks
Evolutionary Computation
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The original schema theorem (an inequality) has been replaced by an equality that determines the expected next generation for a simple genetic algorithm. This has made possible the computation of the trajectory of expected next generations. Visualization of these evolutionary trajectories beginning from different initial populations has led to the discovery of fractal structures.