Daniel Molina Cabrera
Daniel Molina Cabrera
Computer Science, Granada University
Verified email at decsai.ugr.es
TitleCited byYear
A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms
J Derrac, S García, D Molina, F Herrera
Swarm and Evolutionary Computation 1 (1), 3-18, 2011
19332011
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
11862009
Real-coded memetic algorithms with crossover hill-climbing
M Lozano, F Herrera, N Krasnogor, D Molina
Evolutionary computation 12 (3), 273-302, 2004
3522004
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
2052008
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
1662010
Editorial scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems
M Lozano, D Molina, F Herrera
Soft Computing 15 (11), 2085-2087, 2011
1222011
Adaptive local search parameters for real-coded memetic algorithms
D Molina, F Herrera, M Lozano
2005 IEEE Congress on Evolutionary Computation 1, 888-895, 2005
1182005
MA-SW-Chains: Memetic algorithm based on local search chains for large scale continuous global optimization
D Molina, M Lozano, F Herrera
IEEE Congress on evolutionary computation, 1-8, 2010
1162010
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
962006
Test suite for the special issue of soft computing on scalability of evolutionary algorithms and other metaheuristics for large scale continuous optimization problems
F Herrera, M Lozano, D Molina
Last accessed: July, 2010
932010
Memetic algorithms based on local search chains for large scale continuous optimisation problems: MA-SSW-Chains
D Molina, M Lozano, AM Sánchez, F Herrera
Soft Computing 15 (11), 2201-2220, 2011
762011
Iterated greedy for the maximum diversity problem
M Lozano, D Molina, C Garcı
European Journal of Operational Research 214 (1), 31-38, 2011
512011
A walk into metaheuristics for engineering optimization: principles, methods and recent trends
N Xiong, D Molina, ML Ortiz, F Herrera
international journal of computational intelligence systems 8 (4), 606-636, 2015
452015
Variable mesh optimization for continuous optimization problems
A Puris, R Bello, D Molina, F Herrera
Soft Computing 16 (3), 511-525, 2012
452012
Memetic algorithm with local search chaining for large scale continuous optimization problems
D Molina, M Lozano, F Herrera
2009 IEEE Congress on Evolutionary Computation, 830-837, 2009
38*2009
A high performance memetic algorithm for extremely high-dimensional problems
M Lastra, D Molina, JM Benítez
Information Sciences 293, 35-58, 2015
262015
Variable mesh optimization for the 2013 CEC special session niching methods for multimodal optimization
D Molina, A Puris, R Bello, F Herrera
2013 IEEE Congress on Evolutionary Computation, 87-94, 2013
262013
Since CEC 2005 competition on real-parameter optimisation: a decade of research, progress and comparative analysis’s weakness
C García-Martínez, PD Gutiérrez, D Molina, M Lozano, F Herrera
Soft Computing 21 (19), 5573-5583, 2017
232017
Performance evaluation of automatically tuned continuous optimizers on different benchmark sets
T Liao, D Molina, T Stützle
Applied Soft Computing 27, 490-503, 2015
232015
An insight into bio-inspired and evolutionary algorithms for global optimization: review, analysis, and lessons learnt over a decade of competitions
D Molina, A LaTorre, F Herrera
Cognitive Computation 10 (4), 517-544, 2018
202018
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