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Antonio J. Nebro
Antonio José Nebro
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2020 – today
- 2024
- [j45]José F. Aldana-Martín
, María del Mar Roldán García
MOODY: An ontology-driven framework for standardizing multi-objective evolutionary algorithms. Inf. Sci. 661: 120184 (2024) - [j44]Antonio J. Nebro, Manuel López-Ibáñez, José García-Nieto
On the automatic design of multi-objective particle swarm optimizers: experimentation and analysis. Swarm Intell. 18(2): 105-139 (2024) - [c54]Antonio J. Nebro
Experiences Using Julia for Implementing Multi-objective Evolutionary Algorithms. MIC (2) 2024: 174-187 - [c53]Joel Cedeño-Muñoz, Cristian Zambrano-Vega, Antonio J. Nebro:
TM-MSAligner: A Tool for Multiple Sequence Alignment of Transmembrane Proteins. ICCS (4) 2024: 113-121 - [i4]Eneko Osaba, Esther Villar-Rodriguez, Javier Del Ser, Antonio J. Nebro, Daniel Molina, Antonio LaTorre, Ponnuthurai N. Suganthan, Carlos A. Coello Coello, Francisco Herrera:
A Tutorial on the Design, Experimentation and Application of Metaheuristic Algorithms to Real-World Optimization Problems. CoRR abs/2410.03205 (2024) - 2023
- [j43]Cristian Cardas, José F. Aldana-Martín
On the performance of SQL scalable systems on Kubernetes: a comparative study. Clust. Comput. 26(3): 1935-1947 (2023) - [j42]José F. Aldana-Martín
Evolver: Meta-optimizing multi-objective metaheuristics. SoftwareX 24: 101551 (2023) - [c52]Jesús Para
Solving a Multi-objective Job Shop Scheduling Problem with an Automatically Configured Evolutionary Algorithm. OLA 2023: 48-61 - 2022
- [c51]Daniel Doblas, Antonio J. Nebro
Automatic Design of Multi-objective Particle Swarm Optimizers. ANTS Conference 2022: 28-40 - 2021
- [j41]Sandro Hurtado
Reconstruction of gene regulatory networks with multi-objective particle swarm optimisers. Appl. Intell. 51(4): 1972-1991 (2021) - [j40]Cristóbal Barba-González, Antonio J. Nebro, José García-Nieto
Injecting domain knowledge in multi-objective optimization problems: A semantic approach. Comput. Stand. Interfaces 78: 103546 (2021) - [j39]Antonio Benítez-Hidalgo
TITAN: A knowledge-based platform for Big Data workflow management. Knowl. Based Syst. 232: 107489 (2021) - [j38]Eneko Osaba
A Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problems. Swarm Evol. Comput. 64: 100888 (2021) - [j37]Javier Moreno
Merge Nondominated Sorting Algorithm for Many-Objective Optimization. IEEE Trans. Cybern. 51(12): 6154-6164 (2021) - [c50]Eneko Osaba, Javier Del Ser, Aritz D. Martinez
MO-MFCGA: Multiobjective Multifactorial Cellular Genetic Algorithm for Evolutionary Multitasking. SSCI 2021: 1-8 - 2020
- [j36]Antonio Benítez-Hidalgo
Sequoya: multiobjective multiple sequence alignment in Python. Bioinform. 36(12): 3892-3893 (2020) - [j35]Cristóbal Barba-González
On the design of a framework integrating an optimization engine with streaming technologies. Future Gener. Comput. Syst. 107: 538-550 (2020) - [j34]Cristóbal Barba-González, Antonio J. Nebro
A multi-objective interactive dynamic particle swarm optimizer. Prog. Artif. Intell. 9(1): 55-65 (2020) - [j33]Esteban López-Camacho, María Jesús García-Godoy
Optimizing ligand conformations in flexible protein targets: a multi-objective strategy. Soft Comput. 24(14): 10705-10719 (2020)
2010 – 2019
- 2019
- [j32]María Jesús García-Godoy, Esteban López-Camacho, José García-Nieto
Bio-inspired optimization for the molecular docking problem: State of the art, recent results and perspectives. Appl. Soft Comput. 79: 30-45 (2019) - [j31]José García-Nieto
Inference of gene regulatory networks with multi-objective cellular genetic algorithm. Comput. Biol. Chem. 80: 409-418 (2019) - [j30]Jesus Para
Analyze, Sense, Preprocess, Predict, Implement, and Deploy (ASPPID): An incremental methodology based on data analytics for cost-efficiently monitoring the industry 4.0. Eng. Appl. Artif. Intell. 82: 30-43 (2019) - [j29]Cristóbal Barba-González, José García-Nieto
BIGOWL: Knowledge centered Big Data analytics. Expert Syst. Appl. 115: 543-556 (2019) - [j28]Alejandro Santiago Pineda
A novel multi-objective evolutionary algorithm with fuzzy logic based adaptive selection of operators: FAME. Inf. Sci. 471: 233-251 (2019) - [j27]José García-Nieto
Multi-objective ligand-protein docking with particle swarm optimizers. Swarm Evol. Comput. 44: 439-452 (2019) - [j26]Antonio Benítez-Hidalgo
jMetalPy: A Python framework for multi-objective optimization with metaheuristics. Swarm Evol. Comput. 51 (2019) - [c49]Antonio J. Nebro
Automatic configuration of NSGA-II with jMetal and irace. GECCO (Companion) 2019: 1374-1381 - [i3]Antonio Benítez-Hidalgo, Antonio J. Nebro, José García-Nieto, Izaskun Oregi, Javier Del Ser:
jMetalPy: a Python Framework for Multi-Objective Optimization with Metaheuristics. CoRR abs/1903.02915 (2019) - 2018
- [j25]Cristóbal Barba-González, José García-Nieto
jMetalSP: A framework for dynamic multi-objective big data optimization. Appl. Soft Comput. 69: 737-748 (2018) - [j24]Antonio J. Nebro
InDM2: Interactive Dynamic Multi-Objective Decision Making Using Evolutionary Algorithms. Swarm Evol. Comput. 40: 184-195 (2018) - [c48]Eneko Osaba
Multi-objective Design of Time-Constrained Bike Routes Using Bio-inspired Meta-heuristics. BIOMA 2018: 197-210 - [c47]Cristian Zambrano-Vega
MORPHY: A Multiobjective Software Tool for Phylogenetic Inference of Protein Coded Sequences. ICITS 2018: 719-731 - [c46]Antonio Benítez-Hidalgo
About Designing an Observer Pattern-Based Architecture for a Multi-objective Metaheuristic Optimization Framework. IDC 2018: 50-60 - [c45]Cristóbal Barba-González, José García-Nieto
Scalable Inference of Gene Regulatory Networks with the Spark Distributed Computing Platform. IDC 2018: 61-70 - [c44]Jesus Para
Decision Making in Industry 4.0 Scenarios Supported by Imbalanced Data Classification. IDC 2018: 121-134 - [c43]Esteban López-Camacho, María Jesús García-Godoy, Javier Del Ser
Multi-objective Metaheuristics for a Flexible Ligand-Macromolecule Docking Problem in Computational Biology. IDC 2018: 369-379 - [c42]Eneko Osaba
Multi-Objective Optimization of Bike Routes for Last-Mile Package Delivery with Drop-Offs. ITSC 2018: 865-870 - [c41]Cristóbal Barba-González, Vesa Ojalehto, José García-Nieto
Artificial Decision Maker Driven by PSO: An Approach for Testing Reference Point Based Interactive Methods. PPSN (1) 2018: 274-285 - [c40]Antonio J. Nebro
Extending the Speed-Constrained Multi-objective PSO (SMPSO) with Reference Point Based Preference Articulation. PPSN (1) 2018: 298-310 - [c39]Gisele Lobo Pappa, Michael T. M. Emmerich
Tutorials at PPSN 2018. PPSN (2) 2018: 477-489 - [i2]Javier Moreno, Daniel Rodríguez, Antonio J. Nebro, José Antonio Lozano:
Merge Non-Dominated Sorting Algorithm for Many-Objective Optimization. CoRR abs/1809.06106 (2018) - 2017
- [j23]Cristian Zambrano-Vega
M2Align: parallel multiple sequence alignment with a multi-objective metaheuristic. Bioinform. 33(19): 3011-3017 (2017) - [j22]Cristian Zambrano-Vega
Multiple Sequence Alignment with Multiobjective Metaheuristics. A Comparative Study. Int. J. Intell. Syst. 32(8): 843-861 (2017) - [j21]Cristian Zambrano-Vega
Comparing multi-objective metaheuristics for solving a three-objective formulation of multiple sequence alignment. Prog. Artif. Intell. 6(3): 195-210 (2017) - [c38]Cristóbal Barba-González, José García-Nieto
Multi-objective Big Data Optimization with jMetal and Spark. EMO 2017: 16-30 - [c37]Antonio J. Nebro
Design and architecture of the jMetaISP framework. GECCO (Companion) 2017: 1239-1246 - [c36]Cristian Zambrano-Vega
A Multi-objective Optimization Framework for Multiple Sequence Alignment with Metaheuristics. IWBBIO (2) 2017: 245-256 - 2016
- [j20]Francisco Luna
Distributed Multi-Objective Metaheuristics for Real-World Structural Optimization Problems. Comput. J. 59(6): 777-792 (2016) - [c35]Esteban López-Camacho
A New Multi-objective Approach for Molecular Docking Based on RMSD and Binding Energy. AlCoB 2016: 65-77 - [c34]José García-Nieto
A Study of Archiving Strategies in Multi-objective PSO for Molecular Docking. ANTS Conference 2016: 40-52 - [c33]José A. Cordero, Antonio J. Nebro
Dynamic Multi-Objective Optimization with jMetal and Spark: A Case Study. MOD 2016: 106-117 - 2015
- [j19]Esteban López-Camacho
Solving molecular flexible docking problems with metaheuristics: A comparative study. Appl. Soft Comput. 28: 379-393 (2015) - [c32]Antonio J. Nebro
Redesigning the jMetal Multi-Objective Optimization Framework. GECCO (Companion) 2015: 1093-1100 - 2014
- [j18]Gustavo R. Zavala
Integrating a multi-objective optimization framework into a structural design software. Adv. Eng. Softw. 76: 161-170 (2014) - [j17]Esteban López-Camacho
jMetalCpp: optimizing molecular docking problems with a C++ metaheuristic framework. Bioinform. 30(3): 437-438 (2014) - 2013
- [j16]Bernabé Dorronsoro
Achieving super-linear performance in parallel multi-objective evolutionary algorithms by means of cooperative coevolution. Comput. Oper. Res. 40(6): 1552-1563 (2013) - [j15]Mirialys Machin Navas, Antonio José Nebro:
Metaheurísticas multiobjetivo adaptativas. Computación y Sistemas 17(1) (2013) - [c31]Francisco Luna
Solving a Real-World Structural Optimization Problem with a Distributed SMS-EMOA Algorithm. 3PGCIC 2013: 600-605 - [c30]Antonio J. Nebro
A Study of the Combination of Variation Operators in the NSGA-II Algorithm. CAEPIA 2013: 269-278 - [c29]Antonio J. Nebro
Analysis of leader selection strategies in a multi-objective Particle Swarm Optimizer. IEEE Congress on Evolutionary Computation 2013: 3153-3160 - 2012
- [j14]El-Ghazali Talbi, Matthieu Basseur, Antonio J. Nebro
Multi-objective optimization using metaheuristics: non-standard algorithms. Int. Trans. Oper. Res. 19(1-2): 283-305 (2012) - 2011
- [j13]Juan José Durillo
jMetal: A Java framework for multi-objective optimization. Adv. Eng. Softw. 42(10): 760-771 (2011) - [j12]Juan José Durillo
A study of the bi-objective next release problem. Empir. Softw. Eng. 16(1): 29-60 (2011) - [j11]Francisco Luna
Optimization algorithms for large-scale real-world instances of the frequency assignment problem. Soft Comput. 15(5): 975-990 (2011) - [c28]Francisco Chicano
Using multi-objective metaheuristics to solve the software project scheduling problem. GECCO 2011: 1915-1922 - [c27]Juan José Durillo
Distribution of Computational Effort in Parallel MOEA/D. LION 2011: 488-502 - [p7]Bernabé Dorronsoro
Multi-objective Cooperative Coevolutionary Evolutionary Algorithms for Continuous and Combinatorial Optimization. Intelligent Decision Systems in Large-Scale Distributed Environments 2011: 49-74 - 2010
- [j10]Juan José Durillo
A Study of Multiobjective Metaheuristics When Solving Parameter Scalable Problems. IEEE Trans. Evol. Comput. 14(4): 618-635 (2010) - [c26]Juan José Durillo
The jMetal framework for multi-objective optimization: Design and architecture. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c25]Antonio J. Nebro
A Study of the Parallelization of the Multi-Objective Metaheuristic MOEA/D. LION 2010: 303-317 - [p6]Juan José Durillo
On the Velocity Update in Multi-Objective Particle Swarm Optimizers. Advances in Multi-Objective Nature Inspired Computing 2010: 45-62
2000 – 2009
- 2009
- [j9]Antonio José Nebro
MOCell: A cellular genetic algorithm for multiobjective optimization. Int. J. Intell. Syst. 24(7): 726-746 (2009) - [c24]Antonio J. Nebro
SMPSO: A new PSO-based metaheuristic for multi-objective optimization. MCDM 2009: 66-73 - [c23]Juan José Durillo
On the Effect of the Steady-State Selection Scheme in Multi-Objective Genetic Algorithms. EMO 2009: 183-197 - [c22]Carlos Segura
Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms. EMO 2009: 305-319 - [c21]Juan José Durillo
Multi-Objective Particle Swarm Optimizers: An Experimental Comparison. EMO 2009: 495-509 - [c20]Francisco Luna
A Scatter Search Approach for Solving the Automatic Cell Planning Problem. LSSC 2009: 334-342 - [p5]Thomas Weise, Michael Zapf, Raymond Chiong
Why Is Optimization Difficult?. Nature-Inspired Algorithms for Optimisation 2009: 1-50 - [p4]Antonio J. Nebro
On the Effect of Applying a Steady-State Selection Scheme in the Multi-Objective Genetic Algorithm NSGA-II. Nature-Inspired Algorithms for Optimisation 2009: 435-456 - 2008
- [j8]Antonio J. Nebro
DNA fragment assembly using a grid-based genetic algorithm. Comput. Oper. Res. 35(9): 2776-2790 (2008) - [j7]Enrique Alba
Guest Editorial. J. Heuristics 14(4): 311-312 (2008) - [j6]Antonio J. Nebro
AbYSS: Adapting Scatter Search to Multiobjective Optimization. IEEE Trans. Evol. Comput. 12(4): 439-457 (2008) - [c19]Juan José Durillo
A comparative study of the effect of parameter scalability in multi-objective metaheuristics. IEEE Congress on Evolutionary Computation 2008: 1893-1900 - [c18]Francisco Luna, César Estébanez, Coromoto León, José Manuel Chaves-González, Enrique Alba, Ricardo Aler, Carlos Segura
Metaheuristics for solving a real-world frequency assignment problem in GSM networks. GECCO 2008: 1579-1586 - [c17]Juan José Durillo
A study of master-slave approaches to parallelize NSGA-II. IPDPS 2008: 1-8 - [c16]Juan José Durillo
Solving Three-Objective Optimization Problems Using a New Hybrid Cellular Genetic Algorithm. PPSN 2008: 661-670 - [c15]Antonio J. Nebro
A Study of Convergence Speed in Multi-objective Metaheuristics. PPSN 2008: 763-772 - [p3]Francisco Luna
Search Intensification in Metaheuristics for Solving the Automatic Frequency Problem in GSM. Recent Advances in Evolutionary Computation for Combinatorial Optimization 2008: 151-166 - [i1]Francisco R. Villatoro, Antonio J. Nebro, Jose E. Fernández:
PVM-Distributed Implementation of the Radiance Code. CoRR abs/0802.3355 (2008) - 2007
- [j5]Enrique Alba
A cellular multi-objective genetic algorithm for optimal broadcasting strategy in metropolitan MANETs. Comput. Commun. 30(4): 685-697 (2007) - [j4]Antonio J. Nebro
Multi-Objective Optimization using Grid Computing. Soft Comput. 11(6): 531-540 (2007) - [c14]Antonio J. Nebro, Juan José Durillo, Francisco Luna
Design Issues in a Multiobjective Cellular Genetic Algorithm. EMO 2007: 126-140 - [c13]Enrique Alba, Alejandro Cervantes
Metaheuristic Approaches for Optimal Broadcasting Design in Metropolitan MANETs. EUROCAST 2007: 755-763 - [c12]Francisco Luna
Evolutionary Algorithms for Real-World Instances of the Automatic Frequency Planning Problem in GSM Networks. EvoCOP 2007: 108-120 - [c11]Francisco Luna
ACO vs EAs for solving a real-world frequency assignment problem in GSM networks. GECCO 2007: 94-101 - [c10]Antonio J. Nebro
Optimal antenna placement using a new multi-objective chc algorithm. GECCO 2007: 876-883 - [p2]Antonio J. Nebro
DNA Fragment Assembly Using Grid Systems. Grid Computing for Bioinformatics and Computational Biology 2007: 357-374 - 2006
- [j3]Francisco Luna
Observations in using Grid-enabled technologies for solving multi-objective optimization problems. Parallel Comput. 32(5-6): 377-393 (2006) - [c9]Francisco Luna
Optimal Broadcasting in Metropolitan MANETs Using Multiobjective Scatter Search. EvoWorkshops 2006: 255-266 - [p1]Francisco Luna
Parallel Evolutionary Multiobjective Optimization. Parallel Evolutionary Computations 2006: 33-56 - 2005
- [c8]Antonio J. Nebro, Francisco Luna, Enrique Alba:
New Ideas in Applying Scatter Search to Multiobjective Optimization. EMO 2005: 443-458 - [c7]Enrique Alba
A Cellular Multi-Objective Genetic Algorithm for Optimal Broadcasting Strategy in Metropolitan MANETs. IPDPS 2005 - [r1]Antonio J. Nebro, Gabriel Luque, Francisco Luna, Enrique Alba, J. Francisco Chicano:
Advanced Evolutionary Algorithms for Training Neural Networks. Handbook of Bioinspired Algorithms and Applications 2005 - 2004
- [j2]Enrique Alba
Parallel heterogeneous genetic algorithms for continuous optimization. Parallel Comput. 30(5-6): 699-719 (2004) - 2003
- [c6]Enrique Alba, Francisco Luna
Parallel Heterogeneous Genetic Algorithms for Continuous Optimization. IPDPS 2003: 147 - 2002
- [j1]Enrique Alba
Heterogeneous Computing and Parallel Genetic Algorithms. J. Parallel Distributed Comput. 62(9): 1362-1385 (2002) - [c5]Antonio J. Nebro
.NET as a Platform for Implementing Concurrent Objects (Research Note). Euro-Par 2002: 125-130
1990 – 1999
- 1998
- [c4]Antonio J. Nebro
Evaluating a Multithreaded Runtime System for Concurrent Object-Oriented Languages. ISCOPE 1998: 167-174 - 1997
- [c3]Antonio J. Nebro
Applying Distributed Shared Memory Techniques for Implementing Distributed Objects. ECOOP Workshops 1997: 499-506 - [c2]Antonio J. Nebro, Ernesto Pimentel, José M. Troya:
Integrating an Entry Consistency Memory Model and Concurrent Object-Oriented Programming. Euro-Par 1997: 567-571 - 1995
- [c1]Carlos Cotta, José Francisco Aldana Montes, Antonio J. Nebro, José M. Troya:
Hybridizing Genetic Algorithms with Branch and Bound Techniques for the Resolution of the TSP. ICANNGA 1995: 277-280
Coauthor Index
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last updated on 2024-12-10 21:43 CET by the dblp team
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