| Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI AB Arrieta, N Díaz-Rodríguez, J Del Ser, A Bennetot, S Tabik, A Barbado, ... Information fusion 58, 82-115, 2020 | 9073 | 2020 |
| 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 | 5405 | 2011 |
| 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, 617-644, 2009 | 1813 | 2009 |
| Bio-inspired computation: Where we stand and what's next J Del Ser, E Osaba, D Molina, XS Yang, S Salcedo-Sanz, D Camacho, ... Swarm and Evolutionary Computation 48, 220-250, 2019 | 617 | 2019 |
| 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 Garcıa, D Molina, M Lozano, F Herrera Journal of Heuristics 15 (6), 617-644, 2009 | 515 | 2009 |
| Real-coded memetic algorithms with crossover hill-climbing M Lozano, F Herrera, N Krasnogor, D Molina Evolutionary computation 12 (3), 273-302, 2004 | 441 | 2004 |
| 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 | 310 | 2008 |
| A tutorial on the design, experimentation and application of metaheuristic algorithms to real-world optimization problems E Osaba, E Villar-Rodriguez, J Del Ser, AJ Nebro, D Molina, A LaTorre, ... Swarm and Evolutionary Computation 64, 100888, 2021 | 292 | 2021 |
| Comprehensive taxonomies of nature-and bio-inspired optimization: Inspiration versus algorithmic behavior, critical analysis recommendations D Molina, J Poyatos, JD Ser, S García, A Hussain, F Herrera Cognitive Computation 12, 897-939, 2020 | 243 | 2020 |
| A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects I Palomares, E Martínez-Cámara, R Montes, P García-Moral, M Chiachio, ... Applied Intelligence 51, 6497-6527, 2021 | 229 | 2021 |
| Memetic algorithms for continuous optimisation based on local search chains D Molina, M Lozano, C Garcia-Martinez, F Herrera Evolutionary computation 18 (1), 27-63, 2010 | 214 | 2010 |
| 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 | 200 | 2010 |
| Editorial scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems M Lozano, D Molina, F Herrera Soft computing 15, 2085-2087, 2011 | 172 | 2011 |
| 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 | 142 | 2005 |
| 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 | 129 | 2010 |
| A prescription of methodological guidelines for comparing bio-inspired optimization algorithms A LaTorre, D Molina, E Osaba, J Poyatos, J Del Ser, F Herrera Swarm and Evolutionary Computation 67, 100973, 2021 | 123 | 2021 |
| 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 | 122 | 2006 |
| 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, 2201-2220, 2011 | 119 | 2011 |
| SHADE with iterative local search for large-scale global optimization D Molina, A LaTorre, F Herrera 2018 IEEE congress on evolutionary computation (CEC), 1-8, 2018 | 112 | 2018 |
| 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, 517-544, 2018 | 110 | 2018 |
Francisco HerreraProfessor Computer Science and AI, DaSCI Research Institute, Granada University, Spaindecsai.ugr.es의 이메일 확인됨