 | 2012 |
|---|
| 9 |       | J. Francisco Chicano,
Alejandro Cervantes,
Francisco Luna,
Gustavo Recio:
A Novel Multiobjective Formulation of the Robust Software Project Scheduling Problem.
EvoApplications 2012: 497-507 |
| 2009 |
|---|
| 8 | | Carlos Segura,
Alejandro Cervantes,
Antonio J. Nebro,
María Dolores Jaraíz-Simón,
Eduardo Segredo,
Sandra García,
Francisco Luna,
Juan Antonio Gómez Pulido,
Gara Miranda,
Cristóbal Luque,
Enrique Alba,
Miguel Ángel Vega Rodríguez,
Coromoto León,
Inés María Galván:
Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms.
EMO 2009: 305-319 |
| 7 | | Sandra García,
Cristóbal Luque,
Alejandro Cervantes,
Inés María Galván:
Multiobjective Algorithms Hybridization to Optimize Broadcasting Parameters in Mobile Ad-Hoc Networks.
IWANN (1) 2009: 728-735 |
| 6 | | Alejandro Cervantes,
Inés María Galván,
Pedro Isasi:
AMPSO: A New Particle Swarm Method for Nearest Neighborhood Classification.
IEEE Transactions on Systems, Man, and Cybernetics, Part B 39(5): 1082-1091 (2009) |
| 5 | | Alejandro Cervantes,
Inés María Galván,
Pedro Isasi Viñuela:
Michigan Particle Swarm Optimization for Prototype Reduction in Classification Problems.
New Generation Comput. 27(3): 239-257 (2009) |
| 2007 |
|---|
| 4 | | Enrique Alba,
Alejandro Cervantes,
J. A. Gómez,
Pedro Isasi,
M. D. Jaraíz,
Coromoto León,
Gabriel Luque,
Francisco Luna,
Gara Miranda,
Antonio J. Nebro,
R. Pérez,
Carlos Segura:
Metaheuristic Approaches for Optimal Broadcasting Design in Metropolitan MANETs.
EUROCAST 2007: 755-763 |
| 3 | | R. Perez-Perez,
Cristóbal Luque,
Alejandro Cervantes,
Pedro Isasi:
Multiobjective algorithms to optimize broadcasting parameters in mobile Ad-hoc networks.
IEEE Congress on Evolutionary Computation 2007: 3142-3149 |
| 2 | | Alejandro Cervantes,
Inés María Galván,
Pedro Isasi:
An Adaptive Michigan Approach PSO for Nearest Prototype Classification.
IWINAC (2) 2007: 287-296 |
| 2005 |
|---|
| 1 | | Alejandro Cervantes,
Inés María Galván,
Pedro Isasi:
A comparison between the Pittsburgh and Michigan approaches for the binary PSO algorithm.
Congress on Evolutionary Computation 2005: 290-297 |
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