José Carlos Ortiz-Bayliss

Orcid: 0000-0003-3408-2166

According to our database1, José Carlos Ortiz-Bayliss authored at least 82 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
A systematic review of metaheuristic algorithms in electric power systems optimization.
Appl. Soft Comput., January, 2024

Analysing hyper-heuristics based on Neural Networks for the automatic design of population-based metaheuristics in continuous optimisation problems.
Swarm Evol. Comput., 2024

A Generalist Reinforcement Learning Agent for Compressing Multiple Convolutional Networks Using Singular Value Decomposition.
IEEE Access, 2024

A Generalist Reinforcement Learning Agent for Compressing Convolutional Neural Networks.
IEEE Access, 2024

Robotic Mobile Fulfillment System: A Systematic Review.
IEEE Access, 2024

Improving Armed People Detection on Video Surveillance Through Heuristics and Machine Learning Models.
IEEE Access, 2024

Exploring Classificational Cellular Automaton Hyper-heuristics for Solving the Knapsack Problem.
Proceedings of the Advances in Soft Computing, 2024

An Exploratory Study on Machine-Learning-Based Hyper-heuristics for the Knapsack Problem.
Proceedings of the Pattern Recognition - 16th Mexican Conference, 2024

Missing Data and Their Effect on Algorithm Selection for the Bin Packing Problem.
Proceedings of the Pattern Recognition - 16th Mexican Conference, 2024

Beyond Traditional Tuning: Unveiling Metaheuristic Operator Trends in PID Control Tuning for Automatic Voltage Regulation.
Proceedings of the IEEE Congress on Evolutionary Computation, 2024

Tailoring Metaheuristics for Designing Thermodynamic-Optimal Cooling Devices for Microelectronic Thermal Management Applications.
Proceedings of the IEEE Congress on Evolutionary Computation, 2024

2023
Automatic Design of Metaheuristics for Practical Engineering Applications.
IEEE Access, 2023

SIGNRL: A Population-Based Reinforcement Learning Method for Continuous Control.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

On the Feasibility of Using a High-Level Solver within Robotic Mobile Fulfillment Systems.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Recursive Hyper-Heuristics for the Job Shop Scheduling Problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2023

Hyper-Heuristics Meet Controller Design: Improving Electrical Grid Performance through Microgrids.
Proceedings of the IEEE Congress on Evolutionary Computation, 2023

2022
MatHH: A Matlab-based Hyper-Heuristic framework.
SoftwareX, 2022

Combining Constructive and Perturbative Deep Learning Algorithms for the Capacitated Vehicle Routing Problem.
CoRR, 2022

Beyond Hyper-Heuristics: A Squared Hyper-Heuristic Model for Solving Job Shop Scheduling Problems.
IEEE Access, 2022

Detection of Violent Behavior Using Neural Networks and Pose Estimation.
IEEE Access, 2022

A Primary Study on Hyper-Heuristics Powered by Artificial Neural Networks for Customising Population-based Metaheuristics in Continuous Optimisation Problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022

A Transfer Learning Hyper-heuristic Approach for Automatic Tailoring of Unfolded Population-based Metaheuristics.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022

2021
Hyper-Heuristics to customise metaheuristics for continuous optimisation.
Swarm Evol. Comput., 2021

Algorithm selection for solving educational timetabling problems.
Expert Syst. Appl., 2021

Criminal Intention Detection at Early Stages of Shoplifting Cases by Using 3D Convolutional Neural Networks.
Comput., 2021

Enhancing Hyperheuristics for the Knapsack Problem through Fuzzy Logic.
Comput. Intell. Neurosci., 2021

Solving microelectronic thermal management problems using a generalized spiral optimization algorithm.
Appl. Intell., 2021

Tailoring Job Shop Scheduling Problem Instances Through Unified Particle Swarm Optimization.
IEEE Access, 2021

Sequence-Based Selection Hyper-Heuristic Model via MAP-Elites.
IEEE Access, 2021

Naïve Hyper-heuristic Online Learning to Generate Unfolded Population-based Metaheuristics to Solve Continuous Optimization Problems.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

A Straightforward Framework for Video Retrieval Using CLIP.
Proceedings of the Pattern Recognition - 13th Mexican Conference, 2021

Automated Design of Unfolded Metaheuristics and the Effect of Population Size.
Proceedings of the IEEE Congress on Evolutionary Computation, 2021

2020
CUSTOMHyS: Customising Optimisation Metaheuristics via Hyper-heuristic Search.
SoftwareX, 2020

Detecting Suspicious Behavior: How to Deal with Visual Similarity through Neural Networks.
CoRR, 2020

Suspicious Behavior Detection on Shoplifting Cases for Crime Prevention by Using 3D Convolutional Neural Networks.
CoRR, 2020

A Systematic Review of Hyper-Heuristics on Combinatorial Optimization Problems.
IEEE Access, 2020

Discovering Action Regions for Solving the Bin Packing Problem through Hyper-heuristics.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Exploring Reward-based Hyper-heuristics for the Job-shop Scheduling Problem.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

A Genetic Programming Framework for Heuristic Generation for the Job-Shop Scheduling Problem.
Proceedings of the Advances in Soft Computing, 2020

A Preliminary Study on Score-Based Hyper-heuristics for Solving the Bin Packing Problem.
Proceedings of the Pattern Recognition - 12th Mexican Conference, 2020

A Preliminary Study on Feature-independent Hyper-heuristics for the 0/1 Knapsack Problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

A Fuzzy Hyper-Heuristic Approach for the 0-1 Knapsack Problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

Exploring Problem State Transformations to Enhance Hyper-heuristics for the Job-Shop Scheduling Problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

A Primary Study on Hyper-Heuristics to Customise Metaheuristics for Continuous optimisation.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019
Evolutionary-based tailoring of synthetic instances for the Knapsack problem.
Soft Comput., 2019

Selecting meta-heuristics for solving vehicle routing problems with time windows via meta-learning.
Expert Syst. Appl., 2019

Influence of Instance Size on Selection Hyper-Heuristics for Job Shop Scheduling Problems.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Improving Hyper-heuristic Performance for Job Shop Scheduling Problems Using Neural Networks.
Proceedings of the Advances in Soft Computing, 2019

A Simulated Annealing Hyper-heuristic for Job Shop Scheduling Problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2019

Hyper-heuristics Reversed: Learning to Combine Solvers by Evolving Instances.
Proceedings of the IEEE Congress on Evolutionary Computation, 2019

2018
Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems.
Comput. Intell. Neurosci., 2018

Enhancing Selection Hyper-Heuristics via Feature Transformations.
IEEE Comput. Intell. Mag., 2018

Tailoring Instances of the 1D Bin Packing Problem for Assessing Strengths and Weaknesses of Its Solvers.
Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018

An Experimental Study on Ant Colony Optimization Hyper-Heuristics for Solving the Knapsack Problem.
Proceedings of the Pattern Recognition - 10th Mexican Conference, 2018

2017
A Quartile-Based Hyper-heuristic for Solving the 0/1 Knapsack Problem.
Proceedings of the Advances in Soft Computing, 2017

Evolutionary multilabel hyper-heuristic design.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

Applying automatic heuristic-filtering to improve hyper-heuristic performance.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

Improving hyper-heuristic performance through feature transformation.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

2016
A Neuro-evolutionary Hyper-heuristic Approach for Constraint Satisfaction Problems.
Cogn. Comput., 2016

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.
Comput. Intell. Neurosci., 2016

Combine and conquer: an evolutionary hyper-heuristic approach for solving constraint satisfaction problems.
Artif. Intell. Rev., 2016

Grammar-based Selection Hyper-heuristics for Solving Irregular Bin Packing Problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2016

Selection and Generation Hyper-heuristics for Solving the Vehicle Routing Problem with Time Windows.
Proceedings of the Genetic and Evolutionary Computation Conference, 2016

2015
Lifelong Learning Selection Hyper-heuristics for Constraint Satisfaction Problems.
Proceedings of the Advances in Artificial Intelligence and Soft Computing, 2015

A Recursive Split, Solve, and Join Strategy for Solving Constraint Satisfaction Problems.
Proceedings of the Fourteenth Mexican International Conference on Artificial Intelligence, 2015

2013
Learning vector quantization for variable ordering in constraint satisfaction problems.
Pattern Recognit. Lett., 2013

A genetic programming hyper-heuristic: Turning features into heuristics for constraint satisfaction.
Proceedings of the 13th UK Workshop on Computational Intelligence, 2013

Branching Schemes and Variable Ordering Heuristics for Constraint Satisfaction Problems: Is There Something to Learn?
Proceedings of the Nature Inspired Cooperative Strategies for Optimization (NICSO 2013), 2013

Automatic Generation of Heuristics for Constraint Satisfaction Problems.
Proceedings of the Nature Inspired Cooperative Strategies for Optimization (NICSO 2013), 2013

A Supervised Learning Approach to Construct Hyper-heuristics for Constraint Satisfaction.
Proceedings of the Pattern Recognition - 5th Mexican Conference, 2013

Exploring heuristic interactions in constraint satisfaction problems: A closer look at the hyper-heuristic space.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013

Using learning classifier systems to design selective hyper-heuristics for constraint satisfaction problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013

2012
Improving the performance of vector hyper-heuristics through local search.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

Challenging heuristics: evolving binary constraint satisfaction problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

2011
Variable and Value Ordering Decision Matrix Hyper-heuristics: A Local Improvement Approach.
Proceedings of the Advances in Artificial Intelligence, 2011

Neural Networks to Guide the Selection of Heuristics within Constraint Satisfaction Problems.
Proceedings of the Pattern Recognition - Third Mexican Conference, 2011

Evolution of neural networks topologies and learning parameters to produce hyper-heuristics for constraint satisfaction problems.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

On the idea of evolving decision matrix hyper-heuristics for solving constraint satisfaction problems.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

2010
Mapping the performance of heuristics for Constraint Satisfaction.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010

2009
A neuro-evolutionary approach to produce general hyper-heuristics for the dynamic variable ordering in hard binary constraint satisfaction problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

2008
Using Hyper-heuristics for the Dynamic Variable Ordering in Binary Constraint Satisfaction Problems.
Proceedings of the MICAI 2008: Advances in Artificial Intelligence, 2008

Hyper-heuristics for the dynamic variable ordering in constraint satisfaction problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2008


  Loading...