José Carlos Ortiz-Bayliss

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 62

Top Topics

Constraint Satisfaction Problems

Vehicle Routing

Scheduling Problem

Top Venues

Publications

Jose M. Tapia-Avitia, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Nelishia Pillay
Analysing hyper-heuristics based on Neural Networks for the automatic design of population-based metaheuristics in continuous optimisation problems. Swarm Evol. Comput. 89 (2024)
José Eduardo Zárate-Aranda, José Carlos Ortiz-Bayliss
An Exploratory Study on Machine-Learning-Based Hyper-heuristics for the Knapsack Problem. MCPR (2024)
Daniel F. Zambrano-Gutierrez, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya, Juan Gabriel Aviña-Cervantes
Beyond Traditional Tuning: Unveiling Metaheuristic Operator Trends in PID Control Tuning for Automatic Voltage Regulation. CEC (2024)
Guillermo Pérez-Espinosa, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Nelishia Pillay
Tailoring Metaheuristics for Designing Thermodynamic-Optimal Cooling Devices for Microelectronic Thermal Management Applications. CEC (2024)
Maria Torcoroma Benavides-Robles, Gerardo Humberto Valencia-Rivera, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss
Robotic Mobile Fulfillment System: A Systematic Review. IEEE Access 12 (2024)
Gabriel Gonzalez-Sahagun, Santiago Enrique Conant-Pablos, José Carlos Ortiz-Bayliss, Jorge M. Cruz-Duarte
A Generalist Reinforcement Learning Agent for Compressing Convolutional Neural Networks. IEEE Access 12 (2024)
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
A systematic review of metaheuristic algorithms in electric power systems optimization. Appl. Soft Comput. 150 (2024)
José Carlos Ortiz-Bayliss, Anna Karen Gárate-Escamilla, Hugo Terashima-Marín
Missing Data and Their Effect on Algorithm Selection for the Bin Packing Problem. MCPR (2024)
Alonso Vela, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya
Recursive Hyper-Heuristics for the Job Shop Scheduling Problem. CEC (2023)
Gerardo Humberto Valencia-Rivera, José Carlos Ortiz-Bayliss, Jorge M. Cruz-Duarte, Iván Amaya, Juan Gabriel Aviña-Cervantes
Hyper-Heuristics Meet Controller Design: Improving Electrical Grid Performance through Microgrids. CEC (2023)
Daniel F. Zambrano-Gutierrez, Jorge Mario Cruz-Duarte, Juan Gabriel Aviña-Cervantes, José Carlos Ortiz-Bayliss, Jesus J. Yanez-Borjas, Iván Amaya
Automatic Design of Metaheuristics for Practical Engineering Applications. IEEE Access 11 (2023)
Maria Torcoroma Benavides-Robles, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya
On the Feasibility of Using a High-Level Solver within Robotic Mobile Fulfillment Systems. SSCI (2023)
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
SIGNRL: A Population-Based Reinforcement Learning Method for Continuous Control. SSCI (2023)
Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Nelishia Pillay
A Transfer Learning Hyper-heuristic Approach for Automatic Tailoring of Unfolded Population-based Metaheuristics. CEC (2022)
Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya
MatHH: A Matlab-based Hyper-Heuristic framework. SoftwareX 18 (2022)
Roberto García-Torres, Alitzel Adriana Macias-Infante, Santiago Enrique Conant-Pablos, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín
Combining Constructive and Perturbative Deep Learning Algorithms for the Capacitated Vehicle Routing Problem. CoRR (2022)
Kevin B. Kwan-Loo, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos, Hugo Terashima-Marín, Peyman Najafirad
Detection of Violent Behavior Using Neural Networks and Pose Estimation. IEEE Access 10 (2022)
Jose M. Tapia-Avitia, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Nelishia Pillay
A Primary Study on Hyper-Heuristics Powered by Artificial Neural Networks for Customising Population-based Metaheuristics in Continuous Optimisation Problems. CEC (2022)
Alonso Vela, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya
Beyond Hyper-Heuristics: A Squared Hyper-Heuristic Model for Solving Job Shop Scheduling Problems. IEEE Access 10 (2022)
Guillermo A. Martínez-Mascorro, José R. Abreu-Pederzini, José Carlos Ortiz-Bayliss, Angel Garcia-Collantes, Hugo Terashima-Marín
Criminal Intention Detection at Early Stages of Shoplifting Cases by Using 3D Convolutional Neural Networks. Comput. 9 (2) (2021)
Felipe de la Rosa-Rivera, José I. Nuñez-Varela, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín
Algorithm selection for solving educational timetabling problems. Expert Syst. Appl. 174 (2021)
Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Nelishia Pillay
Automated Design of Unfolded Metaheuristics and the Effect of Population Size. CEC (2021)
Jesús Andrés Portillo-Quintero, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín
A Straightforward Framework for Video Retrieval Using CLIP. MCPR (2021)
Frumen Olivas, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos, Hugo Terashima-Marín
Enhancing Hyperheuristics for the Knapsack Problem through Fuzzy Logic. Comput. Intell. Neurosci. 2021 (2021)
Jesús Andrés Portillo-Quintero, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín
A Straightforward Framework For Video Retrieval Using CLIP. CoRR (2021)
Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Rodrigo Correa
Solving microelectronic thermal management problems using a generalized spiral optimization algorithm. Appl. Intell. 51 (8) (2021)
Alonso Vela, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya
Tailoring Job Shop Scheduling Problem Instances Through Unified Particle Swarm Optimization. IEEE Access 9 (2021)
Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos, Hugo Terashima-Marín, Yong Shi
Hyper-Heuristics to customise metaheuristics for continuous optimisation. Swarm Evol. Comput. 66 (2021)
Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Nelishia Pillay
Naïve Hyper-heuristic Online Learning to Generate Unfolded Population-based Metaheuristics to Solve Continuous Optimization Problems. SSCI (2021)
Melissa Sánchez, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya
Sequence-Based Selection Hyper-Heuristic Model via MAP-Elites. IEEE Access 9 (2021)
Erick Lara-Cárdenas, Xavier Sánchez-Díaz, Iván Amaya, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss
A Genetic Programming Framework for Heuristic Generation for the Job-Shop Scheduling Problem. MICAI (1) (2020)
Guillermo A. Martínez-Mascorro, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín
Detecting Suspicious Behavior: How to Deal with Visual Similarity through Neural Networks. CoRR (2020)
Guillermo A. Martínez-Mascorro, José R. Abreu-Pederzini, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín
Suspicious Behavior Detection on Shoplifting Cases for Crime Prevention by Using 3D Convolutional Neural Networks. CoRR (2020)
Frumen Olivas, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos, Hugo Terashima-Marín
A Fuzzy Hyper-Heuristic Approach for the 0-1 Knapsack Problem. CEC (2020)
Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Yong Shi
CUSTOMHyS: Customising Optimisation Metaheuristics via Hyper-heuristic Search. SoftwareX 12 (2020)
Erick Lara-Cárdenas, Arturo Silva-Gálvez, José Carlos Ortiz-Bayliss, Iván Amaya, Jorge M. Cruz-Duarte, Hugo Terashima-Marín
Exploring Reward-based Hyper-heuristics for the Job-shop Scheduling Problem. SSCI (2020)
Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín
A Primary Study on Hyper-Heuristics to Customise Metaheuristics for Continuous optimisation. CEC (2020)
Xavier Sánchez, José Carlos Ortiz-Bayliss, Iván Amaya, Jorge M. Cruz-Duarte, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín
A Preliminary Study on Feature-independent Hyper-heuristics for the 0/1 Knapsack Problem. CEC (2020)
Arturo Silva-Gálvez, Jorge Orozco-Sanchez, Erick Lara-Cárdenas, José Carlos Ortiz-Bayliss, Iván Amaya, Jorge M. Cruz-Duarte, Hugo Terashima-Marín
Discovering Action Regions for Solving the Bin Packing Problem through Hyper-heuristics. SSCI (2020)
Fernando Garza-Santisteban, Iván Amaya, Jorge Cruz, José Carlos Ortiz-Bayliss, Ender Özcan, Hugo Terashima-Marín
Exploring Problem State Transformations to Enhance Hyper-heuristics for the Job-Shop Scheduling Problem. CEC (2020)
Melissa Sánchez, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Hector G. Ceballos, Hugo Terashima-Marín, Iván Amaya
A Systematic Review of Hyper-Heuristics on Combinatorial Optimization Problems. IEEE Access 8 (2020)
Arturo Silva-Gálvez, Erick Lara-Cárdenas, Iván Amaya, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss
A Preliminary Study on Score-Based Hyper-heuristics for Solving the Bin Packing Problem. MCPR (2020)
Fernando Garza-Santisteban, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín
Influence of Instance Size on Selection Hyper-Heuristics for Job Shop Scheduling Problems. SSCI (2019)
Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos, Hugo Terashima-Marín
Hyper-heuristics Reversed: Learning to Combine Solvers by Evolving Instances. CEC (2019)
Luis Fernando Plata-González, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín, Carlos A. Coello Coello
Evolutionary-based tailoring of synthetic instances for the Knapsack problem. Soft Comput. 23 (23) (2019)
Andrés Eduardo Gutiérrez-Rodríguez, Santiago E. Conant-Pablos, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín
Selecting meta-heuristics for solving vehicle routing problems with time windows via meta-learning. Expert Syst. Appl. 118 (2019)
Fernando Garza-Santisteban, Roberto Sánchez-Pámanes, Luis Antonio Puente Rodríguez, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos, Hugo Terashima-Marín
A Simulated Annealing Hyper-heuristic for Job Shop Scheduling Problems. CEC (2019)
Erick Lara-Cárdenas, Xavier Sánchez-Díaz, Iván Amaya, José Carlos Ortiz-Bayliss
Improving Hyper-heuristic Performance for Job Shop Scheduling Problems Using Neural Networks. MICAI (2019)
Iván Amaya, José Carlos Ortiz-Bayliss, Alejandro Rosales-Pérez, Andrés Eduardo Gutiérrez-Rodríguez, Santiago E. Conant-Pablos, Hugo Terashima-Marín, Carlos A. Coello Coello
Enhancing Selection Hyper-Heuristics via Feature Transformations. IEEE Comput. Intell. Mag. 13 (2) (2018)
Iván Amaya, José Carlos Ortiz-Bayliss, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín, Carlos A. Coello Coello
Tailoring Instances of the 1D Bin Packing Problem for Assessing Strengths and Weaknesses of Its Solvers. PPSN (2) (2018)
Bronson Duhart, Fernando Camarena, José Carlos Ortiz-Bayliss, Iván Amaya, Hugo Terashima-Marín
An Experimental Study on Ant Colony Optimization Hyper-Heuristics for Solving the Knapsack Problem. MCPR (2018)
Iván Amaya, José Carlos Ortiz-Bayliss, Alejandro Rosales-Pérez, Andrés Eduardo Gutiérrez-Rodríguez, Santiago E. Conant-Pablos, Hugo Terashima-Marín, Carlos A. Coello Coello
Enhancing Selection Hyper-heuristics via Feature Transformations. CoRR (2018)
José Carlos Ortiz-Bayliss, Iván Amaya, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín
Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems. Comput. Intell. Neurosci. 2018 (2018)
Iván Amaya, José Carlos Ortiz-Bayliss, Andrés Eduardo Gutiérrez-Rodríguez, Hugo Terashima-Marín, Carlos A. Coello Coello
Improving hyper-heuristic performance through feature transformation. CEC (2017)
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
Applying automatic heuristic-filtering to improve hyper-heuristic performance. CEC (2017)
Fernando Gómez-Herrera, Rodolfo A. Ramirez-Valenzuela, José Carlos Ortiz-Bayliss, Iván Amaya, Hugo Terashima-Marín
A Quartile-Based Hyper-heuristic for Solving the 0/1 Knapsack Problem. MICAI (1) (2017)
Alejandro Rosales-Pérez, Andrés Eduardo Gutiérrez-Rodríguez, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Carlos A. Coello Coello
Evolutionary multilabel hyper-heuristic design. CEC (2017)
Jorge Humberto Moreno-Scott, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Santiago Enrique Conant-Pablos
Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems. Comput. Intell. Neurosci. 2016 (2016)
David Espinoza-Nevárez, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Gustavo Gatica
Selection and Generation Hyper-heuristics for Solving the Vehicle Routing Problem with Time Windows. GECCO (Companion) (2016)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Santiago Enrique Conant-Pablos
A Neuro-evolutionary Hyper-heuristic Approach for Constraint Satisfaction Problems. Cogn. Comput. 8 (3) (2016)
Alejandro Sosa-Ascencio, Hugo Terashima-Marín, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos
Grammar-based Selection Hyper-heuristics for Solving Irregular Bin Packing Problems. GECCO (Companion) (2016)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Santiago Enrique Conant-Pablos
Combine and conquer: an evolutionary hyper-heuristic approach for solving constraint satisfaction problems. Artif. Intell. Rev. 46 (3) (2016)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Santiago Enrique Conant-Pablos
Lifelong Learning Selection Hyper-heuristics for Constraint Satisfaction Problems. MICAI (1) (2015)
José Carlos Ortiz-Bayliss, Dulce Jaqueline Magaña-Lozano, Hugo Terashima-Marín, Santiago Enrique Conant-Pablos
A Recursive Split, Solve, and Join Strategy for Solving Constraint Satisfaction Problems. MICAI (Special Sessions) (2015)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Santiago Enrique Conant-Pablos
Learning vector quantization for variable ordering in constraint satisfaction problems. Pattern Recognit. Lett. 34 (4) (2013)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Santiago Enrique Conant-Pablos
Branching Schemes and Variable Ordering Heuristics for Constraint Satisfaction Problems: Is There Something to Learn? NICSO (2013)
José Carlos Ortiz-Bayliss, Ender Ozcan, Andrew J. Parkes, Hugo Terashima-Marín
A genetic programming hyper-heuristic: Turning features into heuristics for constraint satisfaction. UKCI (2013)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Santiago E. Conant-Pablos
Using learning classifier systems to design selective hyper-heuristics for constraint satisfaction problems. IEEE Congress on Evolutionary Computation (2013)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Ender Ozcan, Andrew J. Parkes, Santiago E. Conant-Pablos
Exploring heuristic interactions in constraint satisfaction problems: A closer look at the hyper-heuristic space. IEEE Congress on Evolutionary Computation (2013)
José Carlos Ortiz-Bayliss, Jorge Humberto Moreno-Scott, Hugo Terashima-Marín
Automatic Generation of Heuristics for Constraint Satisfaction Problems. NICSO (2013)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Santiago Enrique Conant-Pablos
A Supervised Learning Approach to Construct Hyper-heuristics for Constraint Satisfaction. MCPR (2013)
Jorge Humberto Moreno-Scott, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Santiago Enrique Conant-Pablos
Challenging heuristics: evolving binary constraint satisfaction problems. GECCO (2012)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Santiago Enrique Conant-Pablos, Ender Özcan, Andrew J. Parkes
Improving the performance of vector hyper-heuristics through local search. GECCO (2012)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Ender Özcan, Andrew J. Parkes, Santiago Enrique Conant-Pablos
Variable and Value Ordering Decision Matrix Hyper-heuristics: A Local Improvement Approach. MICAI (1) (2011)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Santiago E. Conant-Pablos
Neural Networks to Guide the Selection of Heuristics within Constraint Satisfaction Problems. MCPR (2011)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Ender Özcan, Andrew J. Parkes
On the idea of evolving decision matrix hyper-heuristics for solving constraint satisfaction problems. GECCO (Companion) (2011)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Peter Ross, Santiago Enrique Conant-Pablos
Evolution of neural networks topologies and learning parameters to produce hyper-heuristics for constraint satisfaction problems. GECCO (Companion) (2011)
José Carlos Ortiz-Bayliss, Ender Özcan, Andrew J. Parkes, Hugo Terashima-Marín
Mapping the performance of heuristics for Constraint Satisfaction. IEEE Congress on Evolutionary Computation (2010)
José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Peter Ross, Jorge Iván Fuentes-Rosado, Manuel Valenzuela-Rendón
A neuro-evolutionary approach to produce general hyper-heuristics for the dynamic variable ordering in hard binary constraint satisfaction problems. GECCO (2009)
Hugo Terashima-Marín, José Carlos Ortiz-Bayliss, Peter Ross, Manuel Valenzuela-Rendón
Using Hyper-heuristics for the Dynamic Variable Ordering in Binary Constraint Satisfaction Problems. MICAI (2008)
Hugo Terashima-Marín, José Carlos Ortiz-Bayliss, Peter Ross, Manuel Valenzuela-Rendón
Hyper-heuristics for the dynamic variable ordering in constraint satisfaction problems. GECCO (2008)