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Ricardo Landa Becerra
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2020 – today
- 2024
- [j6]Mario Garza-Fabre
, Nicolás Cortés-García, Hiram Galeana-Zapién
Surrogate Models and Ensemble Strategies for Expensive Evolutionary Optimization: An Industrial Case Study. IEEE Access 12: 86144-86159 (2024) - 2022
- [j5]Mario Garza-Fabre
Decision Making in Evolutionary Multiobjective Clustering: A Machine Learning Challenge. IEEE Access 10: 117281-117303 (2022) - [c25]Aarón Leonardo Sánchez-Martínez
Machine Learning-Based Decision Making in Evolutionary Multiobjective Clustering. MICAI (1) 2022: 123-137
2010 – 2019
- 2019
- [j4]Ricardo Landa Becerra
Use of a goal-constraint-based approach for finding the region of interest in multi-objective problems. J. Heuristics 25(1): 107-139 (2019) - [c24]Auraham Camacho, Gregorio Toscano Pulido, Ricardo Landa Becerra, Hisao Ishibuchi:
Indicator-Based Weight Adaptation for Solving Many-Objective Optimization Problems. EMO 2019: 216-228 - 2017
- [j3]Gregorio Toscano Pulido
On the use of stochastic ranking for parent selection in differential evolution for constrained optimization. Soft Comput. 21(16): 4617-4633 (2017) - [j2]Oliver Schütze
Gradient subspace approximation: a direct search method for memetic computing. Soft Comput. 21(21): 6331-6350 (2017) - 2014
- [c23]Pedro Reta, Ricardo Landa:
Feature selection for problem decomposition on high dimensional optimization. SIS 2014: 298-304 - 2013
- [c22]Alan Díaz-Manríquez
A hybrid local search operator for multiobjective optimization. IEEE Congress on Evolutionary Computation 2013: 173-180 - [c21]Ricardo Landa Becerra, Carlos Artemio Coello Coello
Goal-constraint: Incorporating preferences through an evolutionary ε-constraint based method. IEEE Congress on Evolutionary Computation 2013: 741-747 - [c20]Alan Díaz-Manríquez
A ranking method based on the R2 indicator for many-objective optimization. IEEE Congress on Evolutionary Computation 2013: 1523-1530 - [c19]Alan Díaz-Manríquez
On the use of a BSP Tree to create local surrogate models. IEEE Congress on Evolutionary Computation 2013: 2540-2547 - 2012
- [c18]Ricardo Landa Becerra
An approach for estimating separability and its application on high dimensional optimization. GECCO 2012: 951-958 - [c17]Mario Rogelio Flores Mendez, Ricardo Landa:
An EDA based on Bayesian networks constructed with Archimedean copulas. NaBIC 2012: 188-193 - 2011
- [j1]Carlos Soza, Ricardo Landa Becerra
Solving timetabling problems using a cultural algorithm. Appl. Soft Comput. 11(1): 337-344 (2011) - [c16]Alan Díaz-Manríquez
A Surrogate-Based Intelligent Variation Operator for Multiobjective Optimization. Artificial Evolution 2011: 13-24 - [c15]Alan Díaz-Manríquez, Gregorio Toscano Pulido, Ricardo Landa Becerra:
A Long-term Memory Approach for Dynamic Multiobjective Evolutionary Algorithms. IJCCI (ECTA-FCTA) 2011: 333-337
2000 – 2009
- 2009
- [c14]Ricardo Landa Becerra
An evaluation of Differential Evolution in software test data generation. IEEE Congress on Evolutionary Computation 2009: 2850-2857 - 2008
- [c13]Ricardo Landa Becerra
Triangulation Using Differential Evolution. EvoWorkshops 2008: 359-364 - [p1]Ricardo Landa Becerra, Luis V. Santana-Quintero, Carlos A. Coello Coello
Knowledge Incorporation in Multi-objective Evolutionary Algorithms. Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases 2008: 23-46 - 2007
- [c12]Ricardo Landa Becerra
Alternative techniques to solve hard multi-objective optimization problems. GECCO 2007: 757-754 - [c11]Ricardo Landa Becerra, Carlos A. Coello Coello
Epsilon-constraint with an efficient cultured differential evolution. GECCO (Companion) 2007: 2787-2794 - [c10]Carlos Soza, Ricardo Landa Becerra, María Cristina Riff, Carlos A. Coello Coello:
A Cultural Algorithm with Operator Parameters Control for Solving Timetabling Problems. IFSA (1) 2007: 810-819 - 2006
- [c9]Ricardo Landa Becerra, Carlos A. Coello Coello:
Solving Hard Multiobjective Optimization Problems Using epsilon-Constraint with Cultured Differential Evolution. PPSN 2006: 543-552 - 2005
- [c8]Ricardo Landa Becerra, Carlos A. Coello Coello
Optimization with constraints using a cultured differential evolution approach. GECCO 2005: 27-34 - [c7]Ricardo Landa Becerra, Carlos A. Coello Coello:
Use of domain information to improve the performance of an evolutionary algorithm. GECCO Workshops 2005: 362-365 - 2004
- [c6]Ricardo Landa Becerra
Culturizing Differential Evolution for Constrained Optimization. ENC 2004: 304-311 - [c5]Ricardo Landa Becerra
A Cultural Algorithm with Differential Evolution to Solve Constrained Optimization Problems. IBERAMIA 2004: 881-890 - 2003
- [c4]Efrén Mezura-Montes, Carlos A. Coello Coello, Ricardo Landa Becerra
Engineering Optimization Using a Simple Evolutionary Algorithm. ICTAI 2003: 149-156 - [c3]Carlos A. Coello Coello
Evolutionary multiobjective optimization using a cultural algorithm. SIS 2003: 6-13 - 2002
- [c2]Carlos A. Coello Coello, Ricardo Landa Becerra:
Adding Knowledge And Efficient Data Structures To Evolutionary Programming: A Cultural Algorithm For Constrained Optimization. GECCO 2002: 201-209 - [c1]Carlos A. Coello Coello, Ricardo Landa Becerra:
A Cultural Algorithm for Constrained Optimization. MICAI 2002: 98-107
Coauthor Index
aka: Carlos Artemio Coello Coello
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last updated on 2024-11-13 23:48 CET by the dblp team
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