David L. González-Álvarez
According to our database1,
David L. González-Álvarez
authored at least 37 papers
between 2010 and 2018.
Collaborative distances:
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Bibliography
2018
Searching for common patterns on protein sequences by means of a parallel hybrid honey-bee mating optimization algorithm.
Parallel Comput., 2018
2017
A hybrid MPI/OpenMP parallel implementation of NSGA-II for finding patterns in protein sequences.
J. Supercomput., 2017
2016
IEEE Trans. Evol. Comput., 2016
A Comparative Study of Different Motif Occurrence Models Applied to a Hybrid Multiobjective Shuffle Frog Leaping Algorithm.
Comput. J., 2016
Appl. Soft Comput., 2016
2015
Finding Patterns in Protein Sequences by Using a Hybrid Multiobjective Teaching Learning Based Optimization Algorithm.
IEEE ACM Trans. Comput. Biol. Bioinform., 2015
Parallel Comput., 2015
Genet. Program. Evolvable Mach., 2015
Comput. Optim. Appl., 2015
A Parallel Multiobjective Approach based on Honey Bees for Traffic Grooming in Optical Networks.
Comput. J., 2015
Proceedings of the 2015 IEEE TrustCom/BigDataSE/ISPA, 2015
2014
Parallelizing and optimizing a hybrid differential evolution with Pareto tournaments for discovering motifs in DNA sequences.
J. Supercomput., 2014
Convergence analysis of some multiobjective evolutionary algorithms when discovering motifs.
Soft Comput., 2014
J. Netw. Comput. Appl., 2014
Designing a fine-grained parallel differential evolution with Pareto tournaments for solving an optical networking problem.
Concurr. Comput. Pract. Exp., 2014
An improved multiobjective approach inspired by the flashing behaviour of fireflies for Traffic Grooming in optical WDM networks.
Appl. Soft Comput., 2014
The software project scheduling problem: A scalability analysis of multi-objective metaheuristics.
Appl. Soft Comput., 2014
2013
Metaheurísticas, optimización multiobjetivo y paralelismo para descubrir motifs en secuencias de ADN.
PhD thesis, 2013
A parallel cooperative team of multiobjective evolutionary algorithms for motif discovery.
J. Supercomput., 2013
Analysing the scalability of multiobjective evolutionary algorithms when solving the motif discovery problem.
J. Glob. Optim., 2013
Eng. Appl. Artif. Intell., 2013
Parallelizing a hybrid multiobjective differential evolution for identifying cis-regulatory elements.
Proceedings of the 20th European MPI Users's Group Meeting, 2013
Designing a novel hybrid swarm based multiobjective evolutionary algorithm for finding DNA motifs.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013
Hybrid Multiobjective Artificial Bee Colony with Differential Evolution Applied to Motif Finding.
Proceedings of the Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, 2013
Proceedings of the Computer Aided Systems Theory - EUROCAST 2013, 2013
2012
IEEE Trans. Syst. Man Cybern. Part C, 2012
Solving the reporting cells problem by using a parallel team of evolutionary algorithms.
Log. J. IGPL, 2012
A Parallel Multi-Core Team of Multiobjective Evolutionary Algorithms to Discover DNA Motifs.
Proceedings of the 14th IEEE International Conference on High Performance Computing and Communication & 9th IEEE International Conference on Embedded Software and Systems, 2012
Comparing Multiobjective Artificial Bee Colony Adaptations for Discovering DNA Motifs.
Proceedings of the Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, 2012
2011
Applying a Multiobjective Gravitational Search Algorithm (MO-GSA) to Discover Motifs.
Proceedings of the Advances in Computational Intelligence, 2011
On the scalability of multi-objective metaheuristics for the software scheduling problem.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011
Finding Motifs in DNA Sequences Applying a Multiobjective Artificial Bee Colony (MOABC) Algorithm.
Proceedings of the Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, 2011
Proceedings of the Computer Aided Systems Theory - EUROCAST 2011, 2011
2010
A Parallel Cooperative Evolutionary Strategy for Solving the Reporting Cells Problem.
Proceedings of the Soft Computing Models in Industrial and Environmental Applications, 2010
A Multiobjective Variable Neighborhood Search for Solving the Motif Discovery Problem.
Proceedings of the Soft Computing Models in Industrial and Environmental Applications, 2010
Using a Parallel Team of Multiobjective Evolutionary Algorithms to Solve the Motif Discovery Problem.
Proceedings of the Distributed Computing and Artificial Intelligence, 2010
Solving the motif discovery problem by using Differential Evolution with Pareto Tournaments.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010