Adding Knowledge And Efficient Data Structures To Evolutionary Programming: A Cultural Algorithm For Constrained Optimization. - Carlos A. Coello Coello; Ricardo Landa Becerra (GECCO, 2002)

A Cultural Algorithm for Constrained Optimization. - Carlos A. Coello Coello; Ricardo Landa Becerra (MICAI, 2002)

Engineering Optimization Using a Simple Evolutionary Algorithm. - Efrén Mezura-Montes; Carlos A. Coello Coello; Ricardo Landa Becerra (ICTAI, 2003)

Evolutionary multiobjective optimization using a cultural algorithm. - Carlos A. Coello Coello; Ricardo Landa Becerra (SIS, 2003)

Culturizing Differential Evolution for Constrained Optimization. - Ricardo Landa Becerra; Carlos A. Coello Coello (ENC, 2004)

A Cultural Algorithm with Differential Evolution to Solve Constrained Optimization Problems. - Ricardo Landa Becerra; Carlos A. Coello Coello (IBERAMIA, 2004)

Optimization with constraints using a cultured differential evolution approach. - Ricardo Landa Becerra; Carlos A. Coello Coello (GECCO, 2005)

Use of domain information to improve the performance of an evolutionary algorithm. - Ricardo Landa Becerra; Carlos A. Coello Coello (GECCO Workshops, 2005)

Solving Hard Multiobjective Optimization Problems Using epsilon-Constraint with Cultured Differential Evolution. - Ricardo Landa Becerra; Carlos A. Coello Coello (PPSN, 2006)

Epsilon-constraint with an efficient cultured differential evolution. - Ricardo Landa Becerra; Carlos A. Coello Coello (GECCO (Companion), 2007)

Alternative techniques to solve hard multi-objective optimization problems. - Ricardo Landa Becerra; Carlos A. Coello Coello; Alfredo García Hernández-Díaz; Rafael Caballero 002; Julián Molina Luque (GECCO, 2007)

A Cultural Algorithm with Operator Parameters Control for Solving Timetabling Problems. - Carlos Soza; Ricardo Landa Becerra; María Cristina Riff; Carlos A. Coello Coello (IFSA (1), 2007)

Triangulation Using Differential Evolution. - Ricardo Landa Becerra; Luis Gerardo de la Fraga (EvoWorkshops, 2008)

Knowledge Incorporation in Multi-objective Evolutionary Algorithms. - Ricardo Landa Becerra; Luis V. Santana-Quintero; Carlos A. Coello Coello (Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases, 2008)

An evaluation of Differential Evolution in software test data generation. - Ricardo Landa Becerra; Ramón Sagarna; Xin Yao 001 (IEEE Congress on Evolutionary Computation, 2009)

A Surrogate-Based Intelligent Variation Operator for Multiobjective Optimization. - Alan Díaz-Manríquez; Gregorio Toscano Pulido; Ricardo Landa Becerra (Artificial Evolution, 2011)

A Long-term Memory Approach for Dynamic Multiobjective Evolutionary Algorithms. - Alan Díaz-Manríquez; Gregorio Toscano Pulido; Ricardo Landa Becerra (IJCCI (ECTA-FCTA), 2011)

Solving timetabling problems using a cultural algorithm. - Carlos Soza; Ricardo Landa Becerra; María Cristina Riff; Carlos A. Coello Coello (Appl. Soft Comput., 2011)

An approach for estimating separability and its application on high dimensional optimization. - Ricardo Landa Becerra; Yazmin Rojas; Gregorio Toscano Pulido (GECCO, 2012)

An EDA based on Bayesian networks constructed with Archimedean copulas. - Mario Rogelio Flores Mendez; Ricardo Landa (NaBIC, 2012)

A hybrid local search operator for multiobjective optimization. - Alan Díaz-Manríquez; Gregorio Toscano Pulido; Ricardo Landa Becerra (IEEE Congress on Evolutionary Computation, 2013)

On the use of a BSP Tree to create local surrogate models. - Alan Díaz-Manríquez; Gregorio Toscano Pulido; Ricardo Landa Becerra (IEEE Congress on Evolutionary Computation, 2013)

A ranking method based on the R2 indicator for many-objective optimization. - Alan Díaz-Manríquez; Gregorio Toscano Pulido; Carlos Artemio Coello Coello; Ricardo Landa Becerra (IEEE Congress on Evolutionary Computation, 2013)

Goal-constraint: Incorporating preferences through an evolutionary ε-constraint based method. - Ricardo Landa Becerra; Carlos Artemio Coello Coello; Gregorio Toscano Pulido (IEEE Congress on Evolutionary Computation, 2013)

Feature selection for problem decomposition on high dimensional optimization. - Pedro Reta; Ricardo Landa (SIS, 2014)

On the use of stochastic ranking for parent selection in differential evolution for constrained optimization. - Gregorio Toscano Pulido; Ricardo Landa Becerra; Giomara Lárraga; Guillermo Leguizamón (Soft Comput., 2017)

Gradient subspace approximation: a direct search method for memetic computing. - Oliver Schütze 001; Sergio Alvarado; Carlos Segura; Ricardo Landa (Soft Comput., 2017)

Indicator-Based Weight Adaptation for Solving Many-Objective Optimization Problems. - Auraham Camacho; Gregorio Toscano Pulido; Ricardo Landa Becerra; Hisao Ishibuchi (EMO, 2019)

Use of a goal-constraint-based approach for finding the region of interest in multi-objective problems. - Ricardo Landa Becerra; Giomara Lárraga; Gregorio Toscano Pulido (J. Heuristics, 2019)

Machine Learning-Based Decision Making in Evolutionary Multiobjective Clustering. - Aarón Leonardo Sánchez-Martínez; Mario Garza-Fabre; Ricardo Landa Becerra; Edwin Aldana-Bobadilla (MICAI (1), 2022)

Decision Making in Evolutionary Multiobjective Clustering: A Machine Learning Challenge. - Mario Garza-Fabre; Aarón Leonardo Sánchez-Martínez; Edwin Aldana-Bobadilla; Ricardo Landa Becerra (IEEE Access, 2022)

Surrogate Models and Ensemble Strategies for Expensive Evolutionary Optimization: An Industrial Case Study. - Mario Garza-Fabre; Nicolás Cortés-García; Hiram Galeana-Zapién; Ricardo Landa (IEEE Access, 2024)