Manuel Lozano
Manuel Lozano
Dept. Computer Science and A.I. - University Granada
Zweryfikowany adres z decsai.ugr.es
Tytuł
Cytowane przez
Cytowane przez
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Tackling real-coded genetic algorithms: Operators and tools for behavioural analysis
F Herrera, M Lozano, JL Verdegay
Artificial intelligence review 12 (4), 265-319, 1998
15411998
A study on the use of non-parametric tests for analyzing the evolutionary algorithms’ behaviour: a case study on the CEC’2005 special session on real parameter optimization
S García, D Molina, M Lozano, F Herrera
Journal of Heuristics 15 (6), 617, 2009
13312009
Tuning fuzzy logic controllers by genetic algorithms
F Herrera, M Lozano, JL Verdegay
International Journal of Approximate Reasoning 12 (3-4), 299-315, 1995
5171995
A taxonomy for the crossover operator for real‐coded genetic algorithms: An experimental study
F Herrera, M Lozano, AM Sánchez
International Journal of Intelligent Systems 18 (3), 309-338, 2003
4332003
Real-coded memetic algorithms with crossover hill-climbing
M Lozano, F Herrera, N Krasnogor, D Molina
Evolutionary computation 12 (3), 273-302, 2004
3782004
Using evolutionary algorithms as instance selection for data reduction in KDD: an experimental study
JR Cano, F Herrera, M Lozano
IEEE transactions on evolutionary computation 7 (6), 561-575, 2003
3702003
Gradual distributed real-coded genetic algorithms
F Herrera, M Lozano
IEEE transactions on evolutionary computation 4 (1), 43-63, 2000
3472000
A learning process for fuzzy control rules using genetic algorithms
F Herrera, M Lozano, JL Verdegay
Fuzzy sets and systems 100 (1-3), 143-158, 1998
3001998
Global and local real-coded genetic algorithms based on parent-centric crossover operators
C García-Martínez, M Lozano, F Herrera, D Molina, AM Sánchez
European journal of operational research 185 (3), 1088-1113, 2008
2242008
Fuzzy connectives based crossover operators to model genetic algorithms population diversity
F Herrera, M Lozano, JL Verdegay
Fuzzy Sets and Systems 92 (1), 21-30, 1997
2161997
Hybrid metaheuristics with evolutionary algorithms specializing in intensification and diversification: Overview and progress report
M Lozano, C García-Martínez
Computers & Operations Research 37 (3), 481-497, 2010
1842010
Replacement strategies to preserve useful diversity in steady-state genetic algorithms
M Lozano, F Herrera, JR Cano
Information Sciences 178 (23), 4421-4433, 2008
1762008
Memetic algorithms for continuous optimisation based on local search chains
D Molina, M Lozano, C García-Martínez, F Herrera
Evolutionary computation 18 (1), 27-63, 2010
1742010
Hybrid crossover operators for real-coded genetic algorithms: an experimental study
F Herrera, M Lozano, AM Sánchez
Soft Computing 9 (4), 280-298, 2005
1582005
MOGUL: A methodology to obtain genetic fuzzy rule‐based systems under the iterative rule learning approach
O Cordón, MJ del Jesus, F Herrera, M Lozano
International Journal of Intelligent Systems 14 (11), 1123-1153, 1999
1571999
Fuzzy adaptive genetic algorithms: design, taxonomy, and future directions
F Herrera, M Lozano
Soft computing 7 (8), 545-562, 2003
1432003
Stratification for scaling up evolutionary prototype selection
JR Cano, F Herrera, M Lozano
Pattern Recognition Letters 26 (7), 953-963, 2005
1342005
Adaptive genetic operators based on coevolution with fuzzy behaviors
F Herrera, M Lozano
IEEE Transactions on Evolutionary Computation 5 (2), 149-165, 2001
1182001
Evolutionary stratified training set selection for extracting classification rules with trade off precision-interpretability
JR Cano, F Herrera, M Lozano
Data & Knowledge Engineering 60 (1), 90-108, 2007
1132007
Continuous scatter search: an analysis of the integration of some combination methods and improvement strategies
F Herrera, M Lozano, D Molina
European Journal of Operational Research 169 (2), 450-476, 2006
1042006
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