Publications
The following is a list of my publications. You are also invited to check my publication list from other sources:
Google Scholar,
ORCID,
Scopus or
DBLP.
2025
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Heuristic Selection through Neural Networks: An Extended Analysis on the Pod Allocation Problem within Robotic Mobile Fulfillment Systems.
Maria Torcoroma Benavides-Robles,
Ivan Amaya, and
Jose Carlos Ortiz-Bayliss,
Neural Computing and Applications, 2025
(to appear).
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Viscoelastic Characterization of the Human Osteosarcoma Cancer Cell Line MG-63 Using a Fractional-Order Zener Model Through Automated Algorithm Design and Configuration.
Grecia C. Duque-Gimenez,
Daniel F. Zambrano-Gutierrez,
Maricela~Rodriguez-Nieto,
Jorge Luis Menchaca,
Jorge M. Cruz-Duarte,
Diana G. Zarate-Triviño,
Juan Gabriel Avina-Cervantes,
Jose Carlos Ortiz-Bayliss.
Scientific Reports, 2025
[DOI].
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How Much Is Too Much? Facing Practical Limitations in Hyper-Heuristic Design for Packing Problems.
Jose Carlos Ortiz-Bayliss,
Alonso Vela Morales, and
Ivan Amaya.
Algorithms, 2025
[DOI].
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A steady state micro genetic algorithm for hyper-heuristic generation in one-dimensional bin packing.
Julio Juarez,
Jesus Guillermo Falcon-Cardona, and
Jose Carlos Ortiz-Bayliss.
Scientific Reports, 2025
[DOI|Free access].
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Summarizing Recent Developments on Autism Spectrum Disorder Detection and Classification through Machine Learning and Deep Learning Techniques.
Masroor Ahmed,
Sadam Hussain,
Anna Karen Garate-Escamilla,
Ivan Amaya,
Gilberto Ochoa-Ruiz, and
Jose Carlos Ortiz-Bayliss.
Applied Sciences, 2025
[DOI].
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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,
Gerardo Humberto Valencia-Rivera,
Jose Carlos Ortiz-Bayliss, and
Ivan Amaya.
IEEE Access, 2025
[DOI].
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Heuristic-Based Optimization Using Elementary Cellular Automata: A Preliminary Study on the Knapsack Problem.
Jose Eduardo Zarate Aranda, and
Jose Carlos Ortiz-Bayliss.
Mexican Conference in Pattern Recognition (MCPR), 2025
[DOI|Free access].
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Tailoring Bounded Instances for the Job Shop Scheduling Problem through Unified Particle Swarm Optimization.
Alonso Vela Morales,
Jose Carlos Ortis Bayliss,
Jorge M. Cruz Duarte, and
Ivan Amaya.
Mexican Conference in Pattern Recognition (MCPR), 2025
[DOI|Free access].
-
Machine-learning-based hyper-heuristics for solving the Knapsack Problem.
Jose Eduardo Zarate Aranda, and
Jose Carlos Ortiz-Bayliss.
Pattern Recognition Letters, 2025
[DOI].
-
Comparative Analysis of Classification Models using Midjourney-Generated Images in the Realm of Machine Learning.
Anna Karen Garate-Escamilla,
Rafael Martinez,
Jose Carlos Ortiz-Bayliss, and
Amir Hajjam.
Computacion y Sistemas, 2025
[DOI].
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Machine Learning, Missing Values, and Algorithm Selectors: The Untold Story.
Anna Karen Garate-Escamilla,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima-Marin.
Computacion y Sistemas, 2024
[DOI].
-
Hyper-heuristics and Scheduling problems: Strategies, application areas, and performance metrics.
Alonso Vela Morales,
Gerardo Humberto Valencia-Rivera,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss, and
Ivan Amaya.
IEEE Access, 2025
[DOI].
-
Algorithm Selection for Allocating Pods within Robotic Mobile Fulfillment Systems: a Hyper-heuristic Approach.
Maria Torcoroma Benavides-Robles,
Gerardo Humberto Valencia-Rivera,
Jorge M. Cruz-Duarte,
Ivan Amaya, and
Jose Carlos Ortiz-Bayliss.
IEEE Access, 2025
[DOI].
2024
-
Automatic Selection of Machine Learning Models for Armed People Identification.
Alonso J. Amado-Garfias,
Santiago Enrique Conant-Pablos,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima-Marin.
IEEE Access, 2024
[DOI].
-
A Generalist Reinforcement Learning Agent for Compressing Multiple Convolutional Networks using Singular Value Decomposition.
Gabriel Gonzalez-Sahagun,
Santiago Enrique Conant-Pablos,
Jose Carlos Ortiz-Bayliss, and
Jorge M. Cruz-Duarte.
IEEE Access, 2024
[DOI].
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Improving Armed People Detection on Video Surveillance through Heuristics and Machine Learning Models.
Alonso J. Amado-Garfias,
Santiago Enrique Conant-Pablos,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima-Marin.
IEEE Access, 2024
[DOI].
-
Selection Hyper-Heuristics and Job Shop Scheduling Problems: How Does Instance Size Influence Performance?
Fernando~Garza-Santisteban,
Jorge M. Cruz-Duarte,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Santiago Enrique Conant-Pablos, and
Hugo Terashima-Marin.
Journal of Scheduling, 2024
[DOI].
-
Exploring Classificational Cellular Automaton Hyper-heuristics for Solving the Knapsack Problem.
Jose Eduardo Zarate Aranda, and
Jose Carlos Ortiz-Bayliss.
Mexican International Conference in Artificial Intelligence (MICAI), 2024
[DOI].
-
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,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Nelishia Pillay.
Swarm and Evolutionary Computation, 2024
[DOI].
-
Optimal Hybrid Resonant Current Controller for Microgrids connected to an Unbalanced IEEE Test Distribution Network .
Gerardo Humberto Valencia-Rivera,
Ivan Amaya,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss,
Guillermo Tapia-Tinoco, and
Gabriel Avina-Cervantes.
Heliyon, 2024
[DOI].
-
An Exploratory Study on Machine-Learning-Based Hyper-heuristics for the Knapsack Problem
Jose Eduardo Zarate Aranda, and
Jose Carlos Ortiz-Bayliss
Mexican Conference in Pattern Recognition (MCPR), 2024
[DOI|PDF].
-
Missing Data and their effect on Algorithm Selection for the Bin Packing Problem
Anna Karen Garate-Escamilla,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima-Marin.
Mexican Conference in Pattern Recognition (MCPR), 2024
[DOI|PDF].
-
Beyond Traditional Tuning: Unveiling Metaheuristic Operator Trends in PID Control Tuning for Automatic Voltage Regulation.
Daniel Fernando Zambrano-Gutierrez,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss,
Ivan Amaya, and
Gabriel Avina-Cervantes.
IEEE Congress on Evolutionary Computation (CEC), 2024
[DOI|PDF].
-
Tailoring Metaheuristics for Designing Thermodynamic-Optimal Cooling Devices for Microelectronic Thermal Management Applications.
Guillermo Pérez Espinoza,
Jorge M. Cruz-Duarte,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima-Marín.
IEEE Congress on Evolutionary Computation (CEC), 2024.
[DOI|PDF].
-
A Generalist Reinforcement Learning Agent for Compressing Convolutional Neural Networks.
Gabriel Gonzalez-Sahagun,
Santiago Enrique Conant-Pablos,
Jose Carlos Ortiz-Bayliss, and
Jorge M. Cruz-Duarte.
IEEE Access, 2024
[DOI].
-
Robotic Mobile Fulfillment System: a Systematic Review.
Maria Torcoroma Benavides-Robles,
Gerardo Humberto Valencia-Rivera,
Jorge M. Cruz-Duarte,
Ivan Amaya, and
Jose Carlos Ortiz-Bayliss.
IEEE Access, 2024
[DOI].
-
A systematic review of metaheuristic algorithms in electric power systems optimization.
Gerardo Humberto Valencia-Rivera,
Maria Torcoroma Benavides-Robles,
Alonso Vela Morales,
Ivan Amaya,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss, and
Juan Gabriel Avina-Cervantes.
Applied Soft Computing, 2024
[DOI].
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,
Ivan Amaya, and
Jose Carlos Ortiz-Bayliss.
International Conference on Soft Computing & Machine Intelligence (ISCMI), 2023
[DOI].
-
Using µ Genetic Algorithms for Hyper-heuristic Development: A Preliminary Study on Bin Packing Problems.
Jose Carlos Ortiz-Bayliss,
Julio Juarez, and
Jesus Guillermo Falcon-Cardona.
International Conference on Soft Computing & Machine Intelligence (ISCMI), 2023
[DOI|PDF].
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On the Feasibility of Using a High-level Solver within Robotic Mobile Fulfillment Systems.
Maria Torcoroma Benavides-Robles,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss, and
Ivan Amaya.
IEEE Symposium Series on Computational Intelligence (SSCI), 2023
[DOI|PDF].
-
SIGNRL: A Population-based Reinforcement Learning method for Continuous Control.
Daniel F. Zambrano-Gutierrez,
Alberto C. Molina-Porras,
Emmanuel Ovalle-Magallanes,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Juan G. Avina-Cervantes, and
Jorge M. Cruz-Duarte.
IEEE Symposium Series on Computational Intelligence (SSCI), 2023
[DOI].
-
Forecasting PM2.5 Concentration Levels using Shallow Machine Learning Models on the Monterrey Metropolitan Area in Mexico.
Cesar Alejandro Pozo-Luyo,
Jorge M. Cruz-Duarte,
Ivan Amaya, and
Jose Carlos Ortiz-Bayliss.
Atmospheric Pollution Research, 2023
[DOI].
-
Addressing the Algorithm Selection Problem through an Attention-Based Meta-Learner Approach.
Enrique Diaz de Leon-Hicks,
Santiago Enrique Conant-Pablos,
Jose Carlos Ortiz-Bayliss,
and Hugo Terashima-Marin.
Applied Sciences, 2023
[DOI].
-
Hyper-heuristics meet Controller Design: Improving Electrical Grid Performance through Microgrids.
Gerardo Humberto Valencia-Rivera,
Jorge M. Cruz-Duarte,
Juan Gabriel Avina-Cervantes,
Jose Carlos Ortiz-Bayliss, and
Ivan Amaya.
IEEE Congress on Evolutionary Computation (CEC), 2023
[DOI|PDF].
-
Recursive Hyper-heuristics for the Job Shop Scheduling Problem.
Alonso Vela,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss, and
Ivan Amaya.
IEEE Congress on Evolutionary Computation (CEC), 2023
[DOI|PDF].
-
Automatic Design of Metaheuristics for Practical Engineering Applications.
Daniel F. Zambrano-Gutierrez,
Jorge M. Cruz-Duarte,
Juan Gabriel Avina-Cervantes,
Jose Carlos Ortiz-Bayliss,
Jesus Joaquin Yanes-Borjas, and
Ivan Amaya.
IEEE Access, 2023
[DOI].
2022
-
A Sequence-based Hyper-heuristic for Traveling Thieves.
Daniel Rodríguez,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss,
and Ivan Amaya.
Applied Sciences, 2022
[DOI].
-
Identifying Hyper-heuristic Trends through a Text Mining Approach on the Current Literature.
Anna Karen Gárate-Escamilla,
Ivan Amaya,
Jorge M. Cruz-Duarte,
Hugo Terashima Marin, and
Jose Carlos Ortiz-Bayliss.
Applied Sciences, 2022
[DOI].
-
Engagement and social impact in tech-based Citizen Science initiatives for achieving the SDGs: A Systematic Literature Review with a perspective on complex thinking.
Berenice Alfaro-Ponce,
Jorge Sanabria-Z,
Omar Israel González Peña,
Hugo Terashima Marin, and
Jose Carlos Ortiz-Bayliss.
Sustainability, 2022
[DOI].
-
Detection of Violent Behavior using Neural Networks and Pose Estimation.
Kevin B. Kwan-Loo,
Jose Carlos Ortiz-Bayliss,
Santiago Enrique Conant-Pablos,
Hugo Terashima-Marin, and
Paul Rad.
IEEE Access, 2022
[DOI].
-
Leveraging a Neuroevolutionary Approach for Classifying Violent Behavior in Video.
Carlos Flores-Munguia,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima-Marin.
Computational Intelligence and Neuroscience, 2022
[DOI].
-
A Primary Study on Hyper-Heuristics Powered by Artificial Neural Networks for Customising Population-based Metaheuristics in Continuous Optimisation Problems.
Jose Manuel Tapia-Avitia,
Jorge M. Cruz-Duarte,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Nelishia Pillay.
IEEE Congress on Evolutionary Computation (CEC), 2022
[DOI|PDF].
-
A Transfer Learning Hyper-heuristic Approach for Automatic Tailoring of Unfolded Population-based Metaheuristics.
Jorge M. Cruz-Duarte,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss, and
Nelishia Pillay.
IEEE Congress on Evolutionary Computation (CEC), 2022
[DOI|PDF].
-
Beyond Hyper-Heuristics: A Squared Hyper-Heuristic model for solving Job Shop Scheduling Problems.
Alonso Vela,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss, and
Ivan Amaya.
IEEE Access, 2022
[DOI].
-
MatHH: A Matlab-based Hyper-heuristic Framework.
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss, and
Ivan Amaya.
SoftwareX, 2022
[DOI].
2021
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A Feature-Independent Hyper-heuristic Approach for Solving the Knapsack Problem.
Xavier Sanchez-Diaz,
Jose Carlos Ortiz-Bayliss,
Ivan Amaya,
Jorge M. Cruz-Duarte,
Santiago Enrique Conant-Pablos, and
Hugo Terashima-Marín.
Applied Sciences, 2021
[DOI].
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Hybrid Controller Based on LQR Applied to Interleaved Boost Converter and Microgrids under Power Quality Events.
Gerardo Humberto Valencia-Rivera,
Ivan Amaya,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss, and
Juan Gabriel Avina-Cervantes.
Energies, 2021
[DOI].
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Exploring the Knowledge Embedded in Class Visualizations and their Application in Dataset and Extreme Model Compression.
Jose Ricardo Abreu-Pederzini,
Guillermo Arturo Martinez-Mascorro,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima Marin.
Applied Sciences, 2021
[DOI].
-
Naive Hyper-heuristic Online Learning to Generate Unfolded Population-based Metaheuristics to Solve Continuous Optimization Problems.
Jorge M. Cruz-Duarte,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss, and
Nelishia Pillay.
IEEE Symposium Series on Computational Intelligence (SSCI), 2021
[DOI].
-
Sequence-based Selection Hyper-heuristic Model via MAP-Elites.
Melissa Sanchez,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss, and
Ivan Amaya.
IEEE Access, 2021
[DOI].
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Hyper-Heuristics to Customise Metaheuristics for Continuous Optimisation.
Jorge M. Cruz-Duarte,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Santiago Enrique Conant Pablos,
Hugo Terashima-Marin, and
Yong Shi.
Swarm and Evolutionary Computation, 2021
[DOI].
-
Global Optimisation through Hyper-Heuristics: Unfolding Population-Based Metaheuristics.
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss,
Ivan Amaya, and
Nelishia Pillay.
Applied Sciences, 2021
[DOI].
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Tailoring Job Shop Scheduling Problem Instances through Unified Particle Swarm Optimization.
Alonso Vela,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss, and
Ivan Amaya.
IEEE Access, 2021
[DOI].
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Automated Design of Unfolded Metaheuristics and the Effect of Population Size.
Jorge M. Cruz-Duarte,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss, and
Nelishia Pillay.
IEEE Congress on Evolutionary Computation (CEC), 2021
[DOI|PDF].
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A Straightforward Framework For Video Retrieval Using CLIP.
Jesus Andres Portillo-Quintero,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima-Marin.
Mexican Conference in Pattern Recognition (MCPR), 2021
[DOI|PDF].
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A General Framework based on Machine Learning for Algorithm Selection in Constraint Satisfaction Problems.
Jose Carlos Ortiz-Bayliss,
Ivan Amaya,
Jorge M. Cruz-Duarte,
Andres Eduardo Gutierrez-Rodriguez,
Santiago Enrique Conant Pablos, and
Hugo Terashima-Marin.
Applied Sciences, 2021
[DOI].
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Criminal Intention Detection at Early Stages of Shoplifting Cases by Using 3D Convolutional Neural Networks.
Guillermo Arturo Martinez-Mascorro,
Jose Ricardo Abreu-Pederzini,
Jose Carlos Ortiz-Bayliss,
Angel Garcia-Collantes, and
Hugo Terashima-Marin.
Computation, 2021
[DOI].
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Algorithm Selection for Solving Educational Timetabling Problems.
Felipe de la Rosa-Rivera,
Jose I. Nunez-Varela,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima-Marin.
Expert Systems with Applications, 2021
[DOI].
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Enhancing Hyper-Heuristics for the Knapsack Problem through Fuzzy Logic.
Frumen Olivas,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Santiago Enrique Conant-Pablos, and
Hugo Terashima-Marin.
Computational Intelligence and Neuroscience, 2021
[DOI].
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Solving microelectronic thermal management problems using a generalized spiral optimization algorithm.
Ivan Amaya,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss, and
Rodrigo Correa.
Applied Intelligence, 2021
[DOI].
2020
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Towards a Generalised Metaheuristic Model for Continuous Optimisation Problems.
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss,
Ivan Amaya,
Yong Shi,
Hugo Terashima-Marin, and
Nelishia Pillay.
Mathematics, 2020
[DOI].
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CUSTOMHyS: Customising Optimisation Metaheuristics via Hyper-heuristic Search.
Jorge M. Cruz-Duarte,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Yong Shi.
SoftwareX, 2020
[DOI].
-
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Una mirada a las hiper-heurísticas.
Jorge M. Cruz-Duarte,
Ivan Amaya, and
Jose Carlos Ortiz-Bayliss.
Transferencia Tec, 2020
[Web].
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Exploring Reward-based Hyper-heuristics for the Job-shop Scheduling Problem.
Erick Lara-Cardenas,
Arturo Silva-Galvez,
Jose Carlos Ortiz-Bayliss,
Ivan Amaya,
Jorge M. Cruz-Duarte, and
Hugo Terashima-Marin.
IEEE Symposium Series on Computational Intelligence (SSCI), 2020
[DOI|PDF].
-
Discovering Action Regions for Solving the Bin Packing Problem through Hyper-heuristics.
Arturo Silva-Galvez,
Jorge Orozco-Sanchez,
Erick Lara-Cardenas,
Jose Carlos Ortiz-Bayliss,
Ivan Amaya,
Jorge M. Cruz-Duarte, and
Hugo Terashima-Marin.
IEEE Symposium Series on Computational Intelligence (SSCI), 2020
[DOI|PDF].
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A Genetic Programming Framework for Heuristic Generation for the Job-Shop Scheduling Problem.
Erick Lara-Cardenas,
Xavier Sanchez-Diaz,
Ivan Amaya,
Jorge M. Cruz-Duarte, and
Jose Carlos Ortiz-Bayliss.
Mexican International Conference in Artificial Intelligence (MICAI), 2020
[DOI|PDF].
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Detecting Suspicious Behavior on Surveillance Videos: Dealing with visual Similarity between Bystanders and Offenders.
Guillermo Arturo Martinez-Mascorro,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima-Marin.
IEEE ANDESCON, 2020
[DOI|PDF].
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A Systematic Review of Hyper-heuristics on Combinatorial Optimization Problems.
Melissa Sanchez,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss,
Hector Ceballos,
Hugo Terashima-Marin, and
Ivan Amaya.
IEEE Access, 2020
[DOI].
-
A Preliminary Study on Score-based Hyper-heuristics for Solving the Bin Packing Problem.
Arturo Silva-Galvez,
Erick Lara-Cardenas,
Ivan Amaya,
Jorge M. Cruz-Duarte, and
Jose Carlos Ortiz-Bayliss.
Mexican Conference in Pattern Recognition (MCPR), 2020
[DOI|PDF].
-
A Preliminary Study on Feature-independent Hyper-heuristics for the 0/1 Knapsack Problem.
Xavier Sanchez-Diaz,
Jose Carlos Ortiz-Bayliss,
Ivan Amaya,
Jorge M. Cruz-Duarte,
Santiago Enrique Conant-Pablos, and
Hugo Terashima-Marin.
IEEE Congress on Evolutionary Computation (CEC), 2020
[DOI|PDF].
-
Exploring Problem State Transformations to Enhance Hyper-heuristics for the Job-Shop Scheduling Problem.
Fernando Garza-Santisteban,
Ivan Amaya,
Jorge M. Cruz-Duarte,
Jose Carlos Ortiz-Bayliss,
Santiago Enrique Conant-Pablos,
Ender Ozcan, and
Hugo Terashima-Marin.
IEEE Congress on Evolutionary Computation (CEC), 2020
[DOI|PDF].
-
A Fuzzy Hyper-Heuristic Approach for the 0-1 Knapsack Problem.
Frumen Olivas,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Santiago Enrique Conant-Pablos, and
Hugo Terashima-Marin.
IEEE Congress on Evolutionary Computation (CEC), 2020
[DOI|PDF].
-
A Primary Study on Hyper-Heuristics to Customise Metaheuristics for Continuous Optimisation.
Jorge M. Cruz-Duarte,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Santiago Enrique Conant-Pablos, and
Hugo Terashima-Marin.
IEEE Congress on Evolutionary Computation (CEC), 2020
[DOI|PDF].
2019
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Influence of Instance Size on Selection Hyper-Heuristics for Job Shop Scheduling Problems.
Fernando Garza-Santisteban,
Jorge M. Cruz-Duarte,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Santiago Enrique Conant-Pablos, and
Hugo Terashima-Marin.
IEEE Symposium Series on Computational Intelligence (SSCI), 2019
[DOI|PDF].
-
Improving Hyper-heuristic Performance for Job Shop Scheduling Problems using Neural Networks.
Erick Lara-Cardenas,
Xavier Sanchez-Diaz,
Ivan Amaya, and
Jose Carlos Ortiz-Bayliss.
Mexican International Conference in Artificial Intelligence (MICAI), 2019
[DOI|PDF].
-
Hyper-heuristics Reversed: Learning to Combine Solvers by Evolving Instances.
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Santiago Enrique Conant-Pablos, and
Hugo Terashima-Marin.
IEEE Congress on Evolutionary Computation (CEC), 2019
[DOI|PDF].
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A Simulated Annealing Hyper-heuristic for Job Shop Scheduling Problems.
Fernando Garza-Santisteban,
Roberto Sanchez-Pamanes,
Luis-Antonio Puente-Rodriguez,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Santiago Enrique Conant-Pablos, and
Hugo Terashima-Marin.
IEEE Congress on Evolutionary Computation (CEC), 2019
[DOI|PDF].
-
Evolutionary-based tailoring of synthetic instances for the Knapsack problem.
Luis Fernando Plata-Gonzalez,
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Santiago Enrique Conant-Pablos, and
Hugo Terashima-Marin.
Soft Computing, 2019
[DOI].
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Selecting Meta-heuristics for Solving Vehicle Routing Problems with Time Windows via Meta-learning.
Andres Eduardo Gutierrez-Rodriguez,
Santiago Enrique Conant-Pablos,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima-Marin.
Experts System with Applications, 2019
[DOI].
2018
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Tailoring Instances of the 1D Bin Packing Problem for Assessing Strengths and Weaknesses of its Solvers.
Ivan Amaya,
Jose Carlos Ortiz-Bayliss,
Santiago Enrique Conant-Pablos,
Hugo Terashima-Marin, and
Carlos Artemio Coello-Coello.
Parallel Problem Solving from Nature (PPSN), 2018
[DOI|PDF].
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An Experimental Study on Ant Colony Optimization Hyper-heuristics for Solving the Knapsack Problem.
Bronson Duhart,
Fernando Camarena,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima-Marin.
Mexican Conference in Pattern Recognition (MCPR), 2018
[DOI|PDF].
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Enhancing Selection Hyper-heuristics via Feature Transformations.
Ivan Mauricio Amaya-Contreras,
Jose Carlos Ortiz-Bayliss,
Alejandro Rosales-Perez,
Andres Eduardo Gutierrez-Rodriguez,
Santiago Enrique Conant-Pablos,
Hugo Terashima-Marin, and
Carlos Artemio Coello-Coello.
IEEE Computational Intelligence Magazine, 2018
[DOI].
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Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems.
Jose Carlos Ortiz-Bayliss,
Ivan Mauricio Amaya-Contreras,
Santiago Enrique Conant-Pablos, and
Hugo Terashima-Marin.
Computational Intelligence and Neuroscience, 2018
[DOI].
2017
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A Quartile-Based Hyper-Heuristic for Solving the 0/1 Knapsack Problem.
Fernando Gomez-Herrera,
Rodolfo A. Ramirez-Valenzuela,
Jose Carlos Ortiz-Bayliss,
Ivan Amaya, and
Hugo Terashima-Marin.
Mexican International Conference in Artificial Intelligence (MICAI), 2017
[DOI|PDF].
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Improving Hyper-heuristic Performance Through Feature Transformation.
Ivan Mauricio Amaya-Contreras,
Jose Carlos Ortiz-Bayliss,
Andres Eduardo Gutierrez-Rodriguez,
Hugo Terashima-Marin, and
Carlos Artemio Coello-Coello.
IEEE Congress on Evolutionary Computation (CEC), 2017
[DOI|PDF].
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Evolutionary Multilabel Hyper-Heuristic Design.
Alejandro Rosales-Perez,
Andres Eduardo Gutierrez-Rodriguez,
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Carlos Artemio Coello-Coello.
IEEE Congress on Evolutionary Computation (CEC), 2017
[DOI|PDF].
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Applying Automatic Heuristic-Filtering to Improve Hyper-heuristic Performance .
Andres Eduardo Gutierrez-Rodriguez,
Jose Carlos Ortiz-Bayliss,
Alejandro Rosales-Perez,
Ivan Mauricio Amaya-Contreras,
Santiago Enrique Conant-Pablos,
Hugo Terashima-Marin, and
Carlos Artemio Coello-Coello.
IEEE Congress on Evolutionary Computation (CEC), 2017
[DOI|PDF].
2016
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Selection and Generation Hyper-heuristics for Solving the Vehicle Routing Problem with Time Windows.
David Espinoza-Nevarez,
Hugo Terashima-Marin,
Jose Carlos Ortiz-Bayliss, and
Gustavo Gatica.
Genetic and Evolutionary Computation Conference (GECCO), 2016
[DOI|PDF].
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Grammar-based Selection Hyper-heuristics for Solving Irregular Bin Packing Problems.
Alejandro Sosa-Ascencio,
Hugo Terashima-Marin,
Jose Carlos Ortiz-Bayliss, and
Santiago Enrique Conant-Pablos.
Genetic and Evolutionary Computation Conference (GECCO), 2016
[DOI|PDF].
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Combine and conquer: an evolutionary hyper-heuristic approach for solving constraint satisfaction problems.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Santiago Enrique Conant-Pablos.
Artificial Intelligence Review, 2016
[DOI].
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Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.
Jorge Humberto Moreno-Scott,
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Santiago Enrique Conant-Pablos.
Computational Intelligence and Neuroscience, 2016
[DOI].
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A Neuro-evolutionary Hyper-heuristic Approach for Constraint Satisfaction Problems.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Santiago Enrique Conant-Pablos.
Cognitive Computation, 2016
[DOI].
2015
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A Recursive Split, Solve and Join Strategy for Solving Constraint Satisfaction Problems.
Jose Carlos Ortiz-Bayliss,
Dulce Jaqueline Magana-Lozano,
Hugo Terashima-Marin, and
Santiago Enrique Conant-Pablos.
Mexican International Conference in Artificial Intelligence (MICAI), 2015
[DOI|PDF].
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Lifelong Learning Selection Hyper-heuristics for Constraint Satisfaction Problems.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Santiago Enrique Conant-Pablos.
Mexican International Conference in Artificial Intelligence (MICAI), 2015
[DOI|PDF].
2013
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Learning vector quantization for variable ordering in constraint satisfaction problems.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Santiago Enrique Conant-Pablos.
Pattern Recognition Letters, 2013
[DOI].
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A Genetic Programming Hyper-heuristic: Turning Features into Heuristics for Constraint Satisfaction.
Jose Carlos Ortiz-Bayliss,
Ender Ozcan,
Andrew J. Parkes, and
Hugo Terashima-Marin.
UK Workshop on Computational Intelligence (UKCI), 2013
[DOI|PDF].
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Branching Schemes and Variable Ordering Heuristics for Constraint Satisfaction Problems: Is There Something to Learn?
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Santiago Enrique Conant-Pablos.
International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), 2013
[DOI|PDF].
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Automatic Generation of Heuristics for Constraint Satisfaction Problems.
Jose Carlos Ortiz-Bayliss,
Jorge Humberto Moreno-Scott, and
Hugo Terashima-Marin.
International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), 2013
[DOI|PDF].
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Using Learning Classifier Systems to Design Selective Hyper-Heuristics for Constraint Satisfaction Problems.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Santiago Enrique Conant-Pablos.
IEEE Congress on Evolutionary Computation (CEC), 2013
[DOI|PDF].
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Exploring Heuristic Interactions in Constraint Satisfaction Problems: A Closer Look at the Hyper-Heuristic Space.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Santiago Enrique Conant-Pablos,
Ender Ozcan and
Andrew J. Parkes.
IEEE Congress on Evolutionary Computation (CEC), 2013
[DOI|PDF].
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A Supervised Learning Approach to Construct Hyper-heuristics for Constraint Satisfaction.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Santiago Enrique Conant-Pablos.
Mexican Conference on Pattern Recognition (MCPR), 2011
[DOI|PDF].
2012
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Challenging Heuristics: Evolving Binary Constraint Satisfaction Problems.
Jorge Humberto Moreno-Scott,
Jose Carlos Ortiz-Bayliss, and
Hugo Terashima-Marin.
Genetic and Evolutionary Computation Conference (GECCO), 2012
[DOI].
-
Improving the Performance of Vector Hyper-heuristics through Local Search.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin,
Santiago Enrique Conant-Pablos,
Ender Ozcan, and
Andrew J. Parkes.
Genetic and Evolutionary Computation Conference (GECCO), 2012
[DOI|PDF].
2011
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Variable and Value Ordering Decision Matrix Hyper-heuristics: a Local Improvement Approach.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin,
Ender Ozcan,
Andrew J. Parkes, and
Santiago Enrique Conant-Pablos.
Mexican Conference on Artificial Intelligence (MICAI), 2011
[DOI|PDF].
-
Neural Networks to Guide the Selection of Heuristics within Constraint Satisfaction Problems.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin, and
Santiago Enrique Conant-Pablos.
Mexican Conference on Pattern Recognition (MCPR), 2011
[DOI|PDF].
-
Evolution of Neural Networks Topologies and Learning Parameters to Produce Hyper-heuristics for Constraint Satisfaction Problems.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin,
Peter Ross, and
Santiago Enrique Conant-Pablos.
Genetic and Evolutionary Computation Conference (GECCO), 2011
[DOI|PDF].
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On the Idea of Evolving Decision Matrix Hyper-Heuristics for Solving Constraint Satisfaction Problems.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin,
Ender Ozcan, and
Andrew J. Parkes.
Genetic and Evolutionary Computation Conference (GECCO), 2011
[DOI|PDF].
2010
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Mapping the Performance of Heuristics for Constraint Satisfaction.
Jose Carlos Ortiz-Bayliss,
Ender Ozcan,
Andrew J. Parkes, and
Hugo Terashima-Marin.
Congress on Evolutionary Computation (CEC), 2010
[DOI|PDF].
2009
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A Neuro-Evolutionary Approach to Produce General Hyper-heuristics for the Dynamic Variable Ordering in Hard Binary Constraint Satisfaction Problems.
Jose Carlos Ortiz-Bayliss,
Hugo Terashima-Marin,
Peter Ross,
Jorge Ivan Fuentes-Rosado, and
Manuel Valenzuela-Rendon.
Genetic and Evolutionary Computation Conference (GECCO), 2009
[DOI|PDF].
2008
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Using Hyper-heuristics for the Dynamic Variable Ordering in Hard Binary Constraint Satisfaction Problems.
Hugo Terashima-Marin,
Jose Carlos Ortiz-Bayliss,
Peter Ross, and
Manuel Valenzuela-Rendon.
Mexican International Conference on Artificial Intelligence (MICAI), 2008
[DOI|PDF].
-
Hyper-heuristics for the Dynamic Variable Ordering in Constraint Satisfaction Problems.
Hugo Terashima-Marin,
Jose Carlos Ortiz-Bayliss,
Peter Ross, and
Manuel Valenzuela-Rendon.
Genetic and Evolutionary Computation Conference (GECCO), 2008
[DOI|PDF].
