| Defining and simulating open-ended novelty: requirements, guidelines, and challenges W Banzhaf, B Baumgaertner, G Beslon, R Doursat, JA Foster, B McMullin, ... Theory in Biosciences 135, 131-161, 2016 | 124 | 2016 |
| An improved Jaya optimization algorithm with Lévy flight G Iacca, VC dos Santos Junior, VV de Melo Expert Systems with Applications 165, 113902, 2021 | 123 | 2021 |
| Investigating multi-view differential evolution for solving constrained engineering design problems VCV De Melo, GLC Carosio Expert Systems with Applications 40 (9), 3370-3377, 2013 | 77 | 2013 |
| A modified covariance matrix adaptation evolution strategy with adaptive penalty function and restart for constrained optimization VV De Melo, G Iacca Expert Systems with Applications 41 (16), 7077-7094, 2014 | 67 | 2014 |
| Kaizen programming VV De Melo Proceedings of the 2014 annual conference on genetic and evolutionary …, 2014 | 67 | 2014 |
| Investigating smart sampling as a population initialization method for differential evolution in continuous problems VV de Melo, ACB Delbem Information Sciences 193, 36-53, 2012 | 58 | 2012 |
| Drone Squadron Optimization: a novel self-adaptive algorithm for global numerical optimization VV de Melo, W Banzhaf Neural Computing and Applications 30, 3117-3144, 2018 | 54 | 2018 |
| A Literature Analysis of Research on Artificial Intelligence in Management Information System (MIS). AM Nascimento, MAVC da Cunha, F de Souza Meirelles, ... AMCIS, 2018 | 49 | 2018 |
| Automatic Feature Engineering for Regression Models with Machine Learning: an Evolutionary Computation and Statistics Hybrid VV de Melo, W Banzhaf Information Sciences, 2017 | 35 | 2017 |
| Improving the prediction of material properties of concrete using Kaizen Programming with Simulated Annealing VV de Melo, W Banzhaf Neurocomputing 246, 25-44, 2017 | 35 | 2017 |
| Evaluating differential evolution with penalty function to solve constrained engineering problems VV de Melo, GLC Carosio Expert Systems with Applications 39 (9), 7860-7863, 2012 | 34 | 2012 |
| Studying bloat control and maintenance of effective code in linear genetic programming for symbolic regression LF dal Piccol Sotto, VV de Melo Neurocomputing 180, 79-93, 2016 | 24 | 2016 |
| Improving global numerical optimization using a search-space reduction algorithm VV De Melo, ACB Delbem, DL Pinto, FM Federson Proceedings of the 9th annual conference on Genetic and evolutionary …, 2007 | 24 | 2007 |
| A probabilistic linear genetic programming with stochastic context-free grammar for solving symbolic regression problems LFDP Sotto, VV de Melo Proceedings of the Genetic and Evolutionary Computation Conference, 1017-1024, 2017 | 20 | 2017 |
| Batch tournament selection for genetic programming: the quality of lexicase, the speed of tournament VV De Melo, DV Vargas, W Banzhaf Proceedings of the genetic and evolutionary computation conference, 994-1002, 2019 | 19 | 2019 |
| Convergence detection for optimization algorithms: approximate-KKT stopping criterion when Lagrange multipliers are not available G Haeser, VV de Melo Operations Research Letters 43 (5), 484-488, 2015 | 19 | 2015 |
| Immersive virtual environments in corporate education and training AC Muller Queiroz, A Moreira Nascimento, R Tori, T Brashear Alejandro, ... | 17 | 2018 |
| Predicting high-performance concrete compressive strength using features constructed by Kaizen Programming VV de Melo, W Banzhaf 2015 Brazilian Conference on Intelligent Systems (BRACIS), 80-85, 2015 | 17 | 2015 |
| -LGP: an improved version of linear genetic programming evaluated in the Ant Trail problem LFDP Sotto, VV de Melo, MP Basgalupp Knowledge and Information Systems 52 (2), 445-465, 2017 | 16 | 2017 |
| Evaluating methods for constant optimization of symbolic regression benchmark problems VV de Melo, B Fowler, W Banzhaf 2015 Brazilian Conference on Intelligent Systems (BRACIS), 25-30, 2015 | 16 | 2015 |
Alneu de Andrade LopesUniversity of São PauloVerified email at icmc.usp.br
