Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Punctuated equilibria: a parallel genetic algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Parallel genetic algorithms for a hypercube
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
An investigation of niche and species formation in genetic function optimization
Proceedings of the third international conference on Genetic algorithms
Parallel genetic algorithms, population genetics and combinatorial optimization
Proceedings of the third international conference on Genetic algorithms
ASPARAGOS an asynchronous parallel genetic optimization strategy
Proceedings of the third international conference on Genetic algorithms
Fine-grained parallel genetic algorithms
Proceedings of the third international conference on Genetic algorithms
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Optimization Using Distributed Genetic Algorithms
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
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We propose to show from a study of population genetics that convergence in the simple genetic algorithm is due to the homogeneous nature of its population. By applying an adaptive clustering algorithm we demonstrate that highly fit yet diverse populations result. Heterogenity is established using both genotypic and phenotypic measures, and we show that genetic algorithms using genotypic measures out perform both the simple genetic algorithm and ones using a phenotypic measure.