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Publications of Author

1. Eduardo G. Carrano, Ricardo H. C. Takahashi, Carlos M. Fonseca, Oriane M. Neto
   Bi-objective Combined Facility Location and Network Design. [Citation Graph (0, 0)][DBLP]
   EMO, 2006, pp:486-500 [Conf]
   
2. Roselito de Albuquerque Teixeira, Antônio de Pádua Braga, Ricardo H. C. Takahashi, Rodney R. Saldanha
   A Multi-Objective Optimization Approach for Training Artificial Neural Networks. [Citation Graph (0, 0)][DBLP]
   SBRN, 2000, pp:168-172 [Conf]
   
3. Roselito de Albuquerque Teixeira, Antônio de Pádua Braga, Ricardo H. C. Takahashi, Rodney R. Saldanha
   Decisior Implementation in Neural Model Selection by Multi-objective Optimization. [Citation Graph (0, 0)][DBLP]
   SBRN, 2002, pp:234- [Conf]
   
4. Roselito de Albuquerque Teixeira, Antônio de Pádua Braga, Ricardo H. C. Takahashi, Rodney R. Saldanha
   Recent Advances in the MOBJ Algorithm for Training Artifical Neural Networks. [Citation Graph (0, 0)][DBLP]
   Int. J. Neural Syst., 2001, v:11, n:3, pp:265-270 [Journal]
   
5. Roselito de Albuquerque Teixeira, Antônio de Pádua Braga, Ricardo H. C. Takahashi, Rodney R. Saldanha
   Improving generalization of MLPs with multi-objective optimization. [Citation Graph (0, 0)][DBLP]
   Neurocomputing, 2000, v:35, n:1-4, pp:189-194 [Journal]
   
6. Eduardo N. Gonçalves, Reinaldo M. Palhares, Ricardo H. C. Takahashi, Renato C. Mesquita
   Algorithm 860: SimpleS---an extension of Freudenthal's simplex subdivision. [Citation Graph (0, 0)][DBLP]
   ACM Trans. Math. Softw., 2006, v:32, n:4, pp:609-621 [Journal]
   
7. Roselito A. Teixeira, Antônio P. Braga, Rodney R. Saldanha, Ricardo H. C. Takahashi, Talles H. Medeiros
   The Usage of Golden Section in Calculating the Efficient Solution in Artificial Neural Networks Training by Multi-objective Optimization. [Citation Graph (0, 0)][DBLP]
   ICANN (1), 2007, pp:289-298 [Conf]
   
8. Elizabeth F. Wanner, Frederico G. Guimarães, Rodney R. Saldanha, Ricardo H. C. Takahashi, Peter J. Fleming
   Constraint quadratic approximation operator for treating equality constraints with genetic algorithms. [Citation Graph (0, 0)][DBLP]
   Congress on Evolutionary Computation, 2005, pp:2255-2262 [Conf]
   
9. 
   Feedback-Control Operators for Evolutionary Multiobjective Optimization. [Citation Graph (, )][DBLP]
   
   
10. 
    A new decision strategy in multi-objective training of the artificial neural networks. [Citation Graph (, )][DBLP]
    
    
11. 
    The micro-genetic operator in the search of global trends. [Citation Graph (, )][DBLP]
    
    
12. 
    Coordinate change operators for genetic algorithms. [Citation Graph (, )][DBLP]
    
    
13. 
    An enhanced statistical approach for evolutionary algorithm comparison. [Citation Graph (, )][DBLP]
    
    
14. 
    Geographic Delineation of Disease Clusters through Multi-Objective Optimization. [Citation Graph (, )][DBLP]
    
    
15. 
    Hybrid multiobjective approach for designing wireless sensor networks. [Citation Graph (, )][DBLP]
    
    
16. 
    A preliminary comparison of tree encoding schemes for evolutionary algorithms. [Citation Graph (, )][DBLP]
    
    
17. 
    A multiobjective non-linear dynamic programming approach for optimal biological control in soy farming via NSGA-II. [Citation Graph (, )][DBLP]
    
    
18. 
    Projection-based local search operator for multiple equality constraints within genetic algorithms. [Citation Graph (, )][DBLP]
    
    
19. 
    Local search with quadratic approximation in Genetic Algorithms for expensive optimization problems. [Citation Graph (, )][DBLP]
    
    
20. 
    A new performance metric for multiobjective optimization: the integrated sphere counting. [Citation Graph (, )][DBLP]
    
    
21. 
    An Immune Inspired Memetic Algorithm for power distribution system design under load evolution uncertainties. [Citation Graph (, )][DBLP]
    
    
22. 
    A genetic algorithm for multiobjective training of ANFIS fuzzy networks. [Citation Graph (, )][DBLP]
    
    
23. 
    Semi-supervised training of Least Squares Support Vector Machine using a multiobjective evolutionary algorithm. [Citation Graph (, )][DBLP]
    
    
24. 
    A dynamic multiobjective hybrid approach for designing Wireless Sensor Networks. [Citation Graph (, )][DBLP]
    
    
25. 
    A quality metric for multi-objective optimization based on Hierarchical Clustering Techniques. [Citation Graph (, )][DBLP]
    
    
26. 
    Continuous-space embedding genetic algorithm applied to the Degree Constrained Minimum Spanning Tree Problem. [Citation Graph (, )][DBLP]
    
    
27. 
    Designing a multilayer microwave heating device using a multiobjective genetic algorithm. [Citation Graph (, )][DBLP]
    
    
28. 
    Incipient fault detection in induction machine stator-winding using a fuzzy-Bayesian change point detection approach. [Citation Graph (, )][DBLP]
    
    
29. 
    A note on Bayesian identification of change points in data sequences. [Citation Graph (, )][DBLP]
    
    
30. 
    Local Search with Quadratic Approximations into Memetic Algorithms for Optimization with Multiple Criteria. [Citation Graph (, )][DBLP]