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» Dynamic populations in genetic algorithms
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TEC
2008
135views more  TEC 2008»
15 years 11 days ago
Quantum Genetic Optimization
Abstract--The complexity of the selection procedure of a genetic algorithm that requires reordering, if we restrict the class of the possible fitness functions to varying fitness f...
Andrea Malossini, Enrico Blanzieri, T. Calarco
90
Voted
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
15 years 1 months ago
Threshold selecting: best possible probability distribution for crossover selection in genetic algorithms
The paper considers the problem of selecting individuals in the current population in Genetic Algorithms for crossover to find a solution of high fitness of a given combinatoria...
Jörg Lässig, Karl Heinz Hoffmann, Mihael...
103
Voted
CEC
2008
IEEE
15 years 2 months ago
Investigation of simply coded evolutionary artificial neural networks on robot control problems
One of the advantages of evolutionary robotics over other approaches in embodied cognitive science would be its parallel population search. Due to the population search, it takes a...
Yoshiaki Katada, Jun Nakazawa
APIN
2000
120views more  APIN 2000»
15 years 9 days ago
Two-Loop Real-Coded Genetic Algorithms with Adaptive Control of Mutation Step Sizes
Genetic algorithms are adaptive methods based on natural evolution that may be used for search and optimization problems. They process a population of search space solutions with t...
Francisco Herrera, Manuel Lozano
102
Voted
GECCO
2005
Springer
288views Optimization» more  GECCO 2005»
15 years 6 months ago
A comparison study between genetic algorithms and bayesian optimize algorithms by novel indices
Genetic Algorithms (GAs) are a search and optimization technique based on the mechanism of evolution. Recently, another sort of population-based optimization method called Estimat...
Naoki Mori, Masayuki Takeda, Keinosuke Matsumoto