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  de recherche New Low Cost and Undedicated Genetic Operators

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by Blaise Madeline, Blaise Madeline, Thème Génie Logiciel, Projet Coprin
ftp://ftp.inria.fr/INRIA/publication/publi-ps-gz/RR/RR-4573.ps.gz
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Abstract:

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Citations

441 Uniform Crossover in Genetic Algorithms – Syswerda - 1989
114 How genetic algorithms really works I: Mutation and hill-climbing – Mühlenbein - 1992
111 Parameter control in evolutionary algorithms – Eiben, Hinterding, et al. - 1999
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60 Adaptive and Self-Adaptive Evolutionary Computations – Angeline - 1995
56 Varying the probability of mutation in the genetic algorithm – Fogarty - 1989
51 Hybrid evolutionary algorithms for graph coloring – Galinier, Hao - 1999
42 Fundamental limitations on search algorithms: Evolutionary computing in perspective – Radcliffe, Surry - 1995
38 Intelligent mutation rate control in canonical genetic algorithms – Bäck, Schütz - 1996
36 Towards an optimal mutation probability for genetic algorithms – Hesser, Manner - 1991
29 Genetic set recombination – Radcliffe - 1993
18 Applying the genetic approach to simulated annealing in solving some NP-hard problems – Lin, Kao, et al. - 1993
15 der Hauw. Adaptive penalties for evolutionary graph-coloring – Eiben, van - 1998
6 Adaptively Parameterised Evolutionary Systems: Self Adaptive Recombination and Mutation in a Genetic Algorithm – Smith, Fogarty - 1996
2 une bibliothèque de classes C++ pour le développement d’opérateurs génétiques pour CSP. Thèse en préparation – AgCSP - 2002
2 Zsofia Ruttkay. GA-easy and GA-hard constraint satisfaction problems – Eiben, Raue - 1994
1 A network-based adaptive evolutionary algorithm for constraint satisfaction problems – Riff-Rojas - 1998
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