Hyper-heuristics for the dynamic variable ordering in constraint satisfaction problems. - Hugo Terashima-Marín; José Carlos Ortiz-Bayliss; Peter Ross; Manuel Valenzuela-Rendón (GECCO, 2008)

Using Hyper-heuristics for the Dynamic Variable Ordering in Binary Constraint Satisfaction Problems. - Hugo Terashima-Marín; José Carlos Ortiz-Bayliss; Peter Ross; Manuel Valenzuela-Rendón (MICAI, 2008)

A neuro-evolutionary approach to produce general hyper-heuristics for the dynamic variable ordering in hard binary constraint satisfaction problems. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Peter Ross; Jorge Iván Fuentes-Rosado; Manuel Valenzuela-Rendón (GECCO, 2009)

Mapping the performance of heuristics for Constraint Satisfaction. - José Carlos Ortiz-Bayliss; Ender Özcan; Andrew J. Parkes; Hugo Terashima-Marín (IEEE Congress on Evolutionary Computation, 2010)

On the idea of evolving decision matrix hyper-heuristics for solving constraint satisfaction problems. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Ender Özcan; Andrew J. Parkes (GECCO (Companion), 2011)

Evolution of neural networks topologies and learning parameters to produce hyper-heuristics for constraint satisfaction problems. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Peter Ross; Santiago Enrique Conant-Pablos (GECCO (Companion), 2011)

Neural Networks to Guide the Selection of Heuristics within Constraint Satisfaction Problems. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Santiago E. Conant-Pablos (MCPR, 2011)

Variable and Value Ordering Decision Matrix Hyper-heuristics: A Local Improvement Approach. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Ender Özcan; Andrew J. Parkes; Santiago Enrique Conant-Pablos (MICAI (1), 2011)

Challenging heuristics: evolving binary constraint satisfaction problems. - Jorge Humberto Moreno-Scott; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Santiago Enrique Conant-Pablos (GECCO, 2012)

Improving the performance of vector hyper-heuristics through local search. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Santiago Enrique Conant-Pablos; Ender Özcan; Andrew J. Parkes (GECCO, 2012)

Using learning classifier systems to design selective hyper-heuristics for constraint satisfaction problems. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Santiago E. Conant-Pablos (IEEE Congress on Evolutionary Computation, 2013)

Exploring heuristic interactions in constraint satisfaction problems: A closer look at the hyper-heuristic space. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Ender Ozcan; Andrew J. Parkes; Santiago E. Conant-Pablos (IEEE Congress on Evolutionary Computation, 2013)

A Supervised Learning Approach to Construct Hyper-heuristics for Constraint Satisfaction. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Santiago Enrique Conant-Pablos (MCPR, 2013)

Automatic Generation of Heuristics for Constraint Satisfaction Problems. - José Carlos Ortiz-Bayliss; Jorge Humberto Moreno-Scott; Hugo Terashima-Marín (NICSO, 2013)

Branching Schemes and Variable Ordering Heuristics for Constraint Satisfaction Problems: Is There Something to Learn? - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Santiago Enrique Conant-Pablos (NICSO, 2013)

A genetic programming hyper-heuristic: Turning features into heuristics for constraint satisfaction. - José Carlos Ortiz-Bayliss; Ender Ozcan; Andrew J. Parkes; Hugo Terashima-Marín (UKCI, 2013)

Learning vector quantization for variable ordering in constraint satisfaction problems. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Santiago Enrique Conant-Pablos (Pattern Recognit. Lett., 2013)

A Recursive Split, Solve, and Join Strategy for Solving Constraint Satisfaction Problems. - José Carlos Ortiz-Bayliss; Dulce Jaqueline Magaña-Lozano; Hugo Terashima-Marín; Santiago Enrique Conant-Pablos (MICAI (Special Sessions), 2015)

Lifelong Learning Selection Hyper-heuristics for Constraint Satisfaction Problems. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Santiago Enrique Conant-Pablos (MICAI (1), 2015)

Selection and Generation Hyper-heuristics for Solving the Vehicle Routing Problem with Time Windows. - David Espinoza-Nevárez; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Gustavo Gatica (GECCO (Companion), 2016)

Grammar-based Selection Hyper-heuristics for Solving Irregular Bin Packing Problems. - Alejandro Sosa-Ascencio; Hugo Terashima-Marín; José Carlos Ortiz-Bayliss; Santiago E. Conant-Pablos (GECCO (Companion), 2016)

Combine and conquer: an evolutionary hyper-heuristic approach for solving constraint satisfaction problems. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Santiago Enrique Conant-Pablos (Artif. Intell. Rev., 2016)

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems. - Jorge Humberto Moreno-Scott; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Santiago Enrique Conant-Pablos (Comput. Intell. Neurosci., 2016)

A Neuro-evolutionary Hyper-heuristic Approach for Constraint Satisfaction Problems. - José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Santiago Enrique Conant-Pablos (Cogn. Comput., 2016)

Improving hyper-heuristic performance through feature transformation. - Iván Amaya; José Carlos Ortiz-Bayliss; Andrés Eduardo Gutiérrez-Rodríguez; Hugo Terashima-Marín; Carlos A. Coello Coello (CEC, 2017)

Applying automatic heuristic-filtering to improve hyper-heuristic performance. - Andrés Eduardo Gutiérrez-Rodríguez; José Carlos Ortiz-Bayliss; Alejandro Rosales-Pérez; Ivan M. Amaya-Contreras; Santiago E. Conant-Pablos; Hugo Terashima-Marín; Carlos A. Coello Coello (CEC, 2017)

Evolutionary multilabel hyper-heuristic design. - Alejandro Rosales-Pérez; Andrés Eduardo Gutiérrez-Rodríguez; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Carlos A. Coello Coello (CEC, 2017)

A Quartile-Based Hyper-heuristic for Solving the 0/1 Knapsack Problem. - Fernando Gómez-Herrera; Rodolfo A. Ramirez-Valenzuela; José Carlos Ortiz-Bayliss; Iván Amaya; Hugo Terashima-Marín (MICAI (1), 2017)

An Experimental Study on Ant Colony Optimization Hyper-Heuristics for Solving the Knapsack Problem. - Bronson Duhart; Fernando Camarena; José Carlos Ortiz-Bayliss; Iván Amaya; Hugo Terashima-Marín (MCPR, 2018)

Tailoring Instances of the 1D Bin Packing Problem for Assessing Strengths and Weaknesses of Its Solvers. - Iván Amaya; José Carlos Ortiz-Bayliss; Santiago Enrique Conant-Pablos; Hugo Terashima-Marín; Carlos A. Coello Coello (PPSN (2), 2018)

Enhancing Selection Hyper-Heuristics via Feature Transformations. - Iván Amaya; José Carlos Ortiz-Bayliss; Alejandro Rosales-Pérez; Andrés Eduardo Gutiérrez-Rodríguez; Santiago E. Conant-Pablos; Hugo Terashima-Marín; Carlos A. Coello Coello (IEEE Comput. Intell. Mag., 2018)

Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems. - José Carlos Ortiz-Bayliss; Iván Amaya; Santiago Enrique Conant-Pablos; Hugo Terashima-Marín (Comput. Intell. Neurosci., 2018)

Hyper-heuristics Reversed: Learning to Combine Solvers by Evolving Instances. - Iván Amaya; José Carlos Ortiz-Bayliss; Santiago E. Conant-Pablos; Hugo Terashima-Marín (CEC, 2019)

A Simulated Annealing Hyper-heuristic for Job Shop Scheduling Problems. - Fernando Garza-Santisteban; Roberto Sánchez-Pámanes; Luis Antonio Puente Rodríguez; Iván Amaya; José Carlos Ortiz-Bayliss; Santiago E. Conant-Pablos; Hugo Terashima-Marín (CEC, 2019)

Improving Hyper-heuristic Performance for Job Shop Scheduling Problems Using Neural Networks. - Erick Lara-Cárdenas; Xavier Sánchez-Díaz; Iván Amaya; José Carlos Ortiz-Bayliss (MICAI, 2019)

Influence of Instance Size on Selection Hyper-Heuristics for Job Shop Scheduling Problems. - Fernando Garza-Santisteban; Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss; Santiago Enrique Conant-Pablos; Hugo Terashima-Marín (SSCI, 2019)

Selecting meta-heuristics for solving vehicle routing problems with time windows via meta-learning. - Andrés Eduardo Gutiérrez-Rodríguez; Santiago E. Conant-Pablos; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín (Expert Syst. Appl., 2019)

Evolutionary-based tailoring of synthetic instances for the Knapsack problem. - Luis Fernando Plata-González; Iván Amaya; José Carlos Ortiz-Bayliss; Santiago Enrique Conant-Pablos; Hugo Terashima-Marín; Carlos A. Coello Coello (Soft Comput., 2019)

A Primary Study on Hyper-Heuristics to Customise Metaheuristics for Continuous optimisation. - Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss; Santiago Enrique Conant-Pablos; Hugo Terashima-Marín (CEC, 2020)

Exploring Problem State Transformations to Enhance Hyper-heuristics for the Job-Shop Scheduling Problem. - Fernando Garza-Santisteban; Iván Amaya; Jorge Cruz 002; José Carlos Ortiz-Bayliss; Ender Özcan; Hugo Terashima-Marín (CEC, 2020)

A Fuzzy Hyper-Heuristic Approach for the 0-1 Knapsack Problem. - Frumen Olivas; Iván Amaya; José Carlos Ortiz-Bayliss; Santiago E. Conant-Pablos; Hugo Terashima-Marín (CEC, 2020)

A Preliminary Study on Feature-independent Hyper-heuristics for the 0/1 Knapsack Problem. - Xavier Sánchez 001; José Carlos Ortiz-Bayliss; Iván Amaya; Jorge M. Cruz-Duarte; Santiago Enrique Conant-Pablos; Hugo Terashima-Marín (CEC, 2020)

A Preliminary Study on Score-Based Hyper-heuristics for Solving the Bin Packing Problem. - Arturo Silva-Gálvez; Erick Lara-Cárdenas; Iván Amaya; Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss (MCPR, 2020)

A Genetic Programming Framework for Heuristic Generation for the Job-Shop Scheduling Problem. - Erick Lara-Cárdenas; Xavier Sánchez-Díaz; Iván Amaya; Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss (MICAI (1), 2020)

Exploring Reward-based Hyper-heuristics for the Job-shop Scheduling Problem. - Erick Lara-Cárdenas; Arturo Silva-Gálvez; José Carlos Ortiz-Bayliss; Iván Amaya; Jorge M. Cruz-Duarte; Hugo Terashima-Marín (SSCI, 2020)

Discovering Action Regions for Solving the Bin Packing Problem through Hyper-heuristics. - Arturo Silva-Gálvez; Jorge Orozco-Sanchez; Erick Lara-Cárdenas; José Carlos Ortiz-Bayliss; Iván Amaya; Jorge M. Cruz-Duarte; Hugo Terashima-Marín (SSCI, 2020)

A Systematic Review of Hyper-Heuristics on Combinatorial Optimization Problems. - Melissa Sánchez; Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss; Hector G. Ceballos; Hugo Terashima-Marín; Iván Amaya (IEEE Access, 2020)

Suspicious Behavior Detection on Shoplifting Cases for Crime Prevention by Using 3D Convolutional Neural Networks. - Guillermo A. Martínez-Mascorro; José R. Abreu-Pederzini; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín (CoRR, 2020)

Detecting Suspicious Behavior: How to Deal with Visual Similarity through Neural Networks. - Guillermo A. Martínez-Mascorro; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín (CoRR, 2020)

CUSTOMHyS: Customising Optimisation Metaheuristics via Hyper-heuristic Search. - Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Yong Shi 001 (SoftwareX, 2020)

Automated Design of Unfolded Metaheuristics and the Effect of Population Size. - Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss; Nelishia Pillay (CEC, 2021)

A Straightforward Framework for Video Retrieval Using CLIP. - Jesús Andrés Portillo-Quintero; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín (MCPR, 2021)

Naïve Hyper-heuristic Online Learning to Generate Unfolded Population-based Metaheuristics to Solve Continuous Optimization Problems. - Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss; Nelishia Pillay (SSCI, 2021)

Sequence-Based Selection Hyper-Heuristic Model via MAP-Elites. - Melissa Sánchez; Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss; Iván Amaya (IEEE Access, 2021)

Tailoring Job Shop Scheduling Problem Instances Through Unified Particle Swarm Optimization. - Alonso Vela; Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss; Iván Amaya (IEEE Access, 2021)

Solving microelectronic thermal management problems using a generalized spiral optimization algorithm. - Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss; Rodrigo Correa (Appl. Intell., 2021)

Enhancing Hyperheuristics for the Knapsack Problem through Fuzzy Logic. - Frumen Olivas; Iván Amaya; José Carlos Ortiz-Bayliss; Santiago E. Conant-Pablos; Hugo Terashima-Marín (Comput. Intell. Neurosci., 2021)

Criminal Intention Detection at Early Stages of Shoplifting Cases by Using 3D Convolutional Neural Networks. - Guillermo A. Martínez-Mascorro; José R. Abreu-Pederzini; José Carlos Ortiz-Bayliss; Angel Garcia-Collantes; Hugo Terashima-Marín (Comput., 2021)

Algorithm selection for solving educational timetabling problems. - Felipe de la Rosa-Rivera; José I. Nuñez-Varela; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín (Expert Syst. Appl., 2021)

Hyper-Heuristics to customise metaheuristics for continuous optimisation. - Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss; Santiago E. Conant-Pablos; Hugo Terashima-Marín; Yong Shi 001 (Swarm Evol. Comput., 2021)

A Transfer Learning Hyper-heuristic Approach for Automatic Tailoring of Unfolded Population-based Metaheuristics. - Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss; Nelishia Pillay (CEC, 2022)

A Primary Study on Hyper-Heuristics Powered by Artificial Neural Networks for Customising Population-based Metaheuristics in Continuous Optimisation Problems. - Jose M. Tapia-Avitia; Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Nelishia Pillay (CEC, 2022)

Detection of Violent Behavior Using Neural Networks and Pose Estimation. - Kevin B. Kwan-Loo; José Carlos Ortiz-Bayliss; Santiago E. Conant-Pablos; Hugo Terashima-Marín; Peyman Najafirad (IEEE Access, 2022)

Beyond Hyper-Heuristics: A Squared Hyper-Heuristic Model for Solving Job Shop Scheduling Problems. - Alonso Vela; Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss; Iván Amaya (IEEE Access, 2022)

Combining Constructive and Perturbative Deep Learning Algorithms for the Capacitated Vehicle Routing Problem. - Roberto García-Torres; Alitzel Adriana Macias-Infante; Santiago Enrique Conant-Pablos; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín (CoRR, 2022)

MatHH: A Matlab-based Hyper-Heuristic framework. - Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss; Iván Amaya (SoftwareX, 2022)

Hyper-Heuristics Meet Controller Design: Improving Electrical Grid Performance through Microgrids. - Gerardo Humberto Valencia-Rivera; José Carlos Ortiz-Bayliss; Jorge M. Cruz-Duarte; Iván Amaya; Juan Gabriel Aviña-Cervantes (CEC, 2023)

Recursive Hyper-Heuristics for the Job Shop Scheduling Problem. - Alonso Vela; Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss; Iván Amaya (CEC, 2023)

On the Feasibility of using Neural Networks as High-level solvers for the Pod Allocation Problem within Robotic Mobile Fulfillment Systems. - Maria Torcoroma Benavides-Robles; Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss (ISCMI, 2023)

Using μ Genetic Algorithms for Hyper-heuristic Development: A Preliminary Study on Bin Packing Problems. - José Carlos Ortiz-Bayliss; Julio Juárez; Jesús Guillermo Falcón-Cardona (ISCMI, 2023)

On the Feasibility of Using a High-Level Solver within Robotic Mobile Fulfillment Systems. - Maria Torcoroma Benavides-Robles; Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss; Iván Amaya (SSCI, 2023)

SIGNRL: A Population-Based Reinforcement Learning Method for Continuous Control. - Daniel F. Zambrano-Gutierrez; Alberto C. Molina-Porras; Emmanuel Ovalle-Magallanes; Iván Amaya; José Carlos Ortiz-Bayliss; Juan Gabriel Aviña-Cervantes; Jorge M. Cruz-Duarte (SSCI, 2023)

Automatic Design of Metaheuristics for Practical Engineering Applications. - Daniel F. Zambrano-Gutierrez; Jorge Mario Cruz-Duarte; Juan Gabriel Aviña-Cervantes; José Carlos Ortiz-Bayliss; Jesus J. Yanez-Borjas; Iván Amaya (IEEE Access, 2023)

Tailoring Metaheuristics for Designing Thermodynamic-Optimal Cooling Devices for Microelectronic Thermal Management Applications. - Guillermo Pérez-Espinosa; Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Nelishia Pillay (CEC, 2024)

Beyond Traditional Tuning: Unveiling Metaheuristic Operator Trends in PID Control Tuning for Automatic Voltage Regulation. - Daniel F. Zambrano-Gutierrez; Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss; Iván Amaya; Juan Gabriel Aviña-Cervantes (CEC, 2024)

Missing Data and Their Effect on Algorithm Selection for the Bin Packing Problem. - José Carlos Ortiz-Bayliss; Anna Karen Gárate-Escamilla; Hugo Terashima-Marín (MCPR, 2024)

An Exploratory Study on Machine-Learning-Based Hyper-heuristics for the Knapsack Problem. - José Eduardo Zárate-Aranda; José Carlos Ortiz-Bayliss (MCPR, 2024)

Exploring Classificational Cellular Automaton Hyper-heuristics for Solving the Knapsack Problem. - José Eduardo Zárate-Aranda; José Carlos Ortiz-Bayliss (MICAI (2), 2024)

Improving Armed People Detection on Video Surveillance Through Heuristics and Machine Learning Models. - Alonso Javier Amado-Garfias; Santiago Enrique Conant-Pablos; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín (IEEE Access, 2024)

Automatic Selection of Machine Learning Models for Armed People Identification. - Alonso Javier Amado-Garfias; Santiago Enrique Conant-Pablos; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín (IEEE Access, 2024)

Robotic Mobile Fulfillment System: A Systematic Review. - Maria Torcoroma Benavides-Robles; Gerardo Humberto Valencia-Rivera; Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss (IEEE Access, 2024)

A Generalist Reinforcement Learning Agent for Compressing Convolutional Neural Networks. - Gabriel Gonzalez-Sahagun; Santiago Enrique Conant-Pablos; José Carlos Ortiz-Bayliss; Jorge M. Cruz-Duarte (IEEE Access, 2024)

A Generalist Reinforcement Learning Agent for Compressing Multiple Convolutional Networks Using Singular Value Decomposition. - Gabriel Gonzalez-Sahagun; Santiago Enrique Conant-Pablos; José Carlos Ortiz-Bayliss; Jorge M. Cruz-Duarte (IEEE Access, 2024)

Analysing hyper-heuristics based on Neural Networks for the automatic design of population-based metaheuristics in continuous optimisation problems. - Jose M. Tapia-Avitia; Jorge M. Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín; Nelishia Pillay (Swarm Evol. Comput., 2024)

A systematic review of metaheuristic algorithms in electric power systems optimization. - Gerardo Humberto Valencia-Rivera; Maria Torcoroma Benavides-Robles; Alonso Vela Morales; Iván Amaya; Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss; Juan Gabriel Aviña-Cervantes (Appl. Soft Comput., 2024)

Tailoring Bounded Instances for the Job Shop Scheduling Problem Through Unified Particle Swarm Optimization. - Alonso Vela Morales; José Carlos Ortiz-Bayliss; Jorge M. Cruz-Duarte; Iván Amaya (MCPR, 2025)

Heuristic-Based Optimization Using Elementary Cellular Automata: A Preliminary Study on the Knapsack Problem. - José Eduardo Zárate-Aranda; José Carlos Ortiz-Bayliss (MCPR, 2025)

Algorithm Selection for Allocating Pods Within Robotic Mobile Fulfillment Systems: A Hyper-Heuristic Approach. - Maria Torcoroma Benavides-Robles; Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss; Iván Amaya (IEEE Access, 2025)

Hyper-Heuristics and Scheduling Problems: Strategies, Application Areas, and Performance Metrics. - Alonso Vela; Gerardo Humberto Valencia-Rivera; Jorge M. Cruz-Duarte; José Carlos Ortiz-Bayliss; Iván Amaya (IEEE Access, 2025)

Robotic Mobile Fulfillment Systems: Are Hyper-Heuristics a Feasible Approach When Dealing With the Pod Allocation and Item Storage Problems? - Toby Yung; Maria Torcoroma Benavides-Robles; José Carlos Ortiz-Bayliss; Iván Amaya (IEEE Access, 2025)

Comparative Analysis of Classification Models Using Midjourney-generated Images in the Realm of Machine Learning. - Anna Karen Gárate-Escamilla; Rafael Martínez; José Carlos Ortiz-Bayliss; Amir Hajjam (Computación y Sistemas (CyS), 2025)

Machine Learning, Missing Values, and Algorithm Selectors: The Untold Story. - Anna Karen Gárate-Escamilla; José Carlos Ortiz-Bayliss; Hugo Terashima-Marín (Computación y Sistemas (CyS), 2025)

Selection hyper-heuristics and job shop scheduling problems: How does instance size influence performance? - Fernando Garza-Santisteban; Jorge Mario Cruz-Duarte; Iván Amaya; José Carlos Ortiz-Bayliss; Santiago Enrique Conant-Pablos; Hugo Terashima-Marín (J. Sched., 2025)