World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
8002
World Ranking
9197
National Ranking
569

Overview

Gabriela Ochoa is affiliated with the University of Stirling in the United Kingdom. Their research primarily focuses on areas within computer science, particularly in the domains of artificial intelligence and computational theory and mathematics.

The main fields of study for Gabriela Ochoa include:

  • Computer Science

Within this broad field, their work spans several subfields such as:

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Genetics
  • Industrial and Manufacturing Engineering
  • Molecular Biology

The scientist's main research topics include:

  • Metaheuristic Optimization Algorithms Research
  • Evolutionary Algorithms and Applications
  • Advanced Multi-Objective Optimization Algorithms
  • Evolution and Genetic Dynamics
  • Gene Regulatory Network Analysis
  • Data Visualization and Analytics
  • Machine Learning and Data Classification

Gabriela Ochoa's publication record includes contributions to journals and conferences focused on evolutionary computation and optimization. Some of the recent papers authored or coauthored by them are:

  • Search trajectory networks: A tool for analysing and visualising the behaviour of metaheuristics, 2021, Applied Soft Computing
  • Fitness landscape analysis of convolutional neural network architectures for image classification, 2022, Information Sciences
  • A comparative analysis of two matheuristics by means of merged local optima networks, 2020, European Journal of Operational Research
  • Management responses in Belize and Honduras, as stony coral tissue loss disease expands its prevalence in the Mesoamerican reef, 2022, Frontiers in Marine Science
  • Understanding parameter spaces using local optima networks, 2021, Proceedings of the Genetic and Evolutionary Computation Conference Companion

The frequent coauthors collaborating with Gabriela Ochoa include:

  • Yuri Lavinas
  • Francisco Chicano
  • Christian Blum
  • Claus Aranha
  • Sebástien Vérel

Gabriela Ochoa has published extensively in venues such as:

  • Proceedings of the Genetic and Evolutionary Computation Conference
  • arXiv (Cornell University)
  • Proceedings of the Genetic and Evolutionary Computation Conference Companion
  • ACM SIGEVOlution
  • Zenodo (CERN European Organization for Nuclear Research)

The scientist's book publications include contributions to volumes published by Springer Science+Business Media, specifically:

  • Parallel Problem Solving from Nature - PPSN XVII (2022)
  • Parallel Problem Solving from Nature - PPSN XVII (2022)

Best Publications

  • Hyper-heuristics: a survey of the state of the art

    Edmund K. Burke;Michel Gendreau;Matthew R. Hyde;Graham Kendall

  • A Classification of Hyper-heuristic Approaches

    Edmund K. Burke;Matthew Hyde;Graham Kendall;Gabriela Ochoa

  • Google Trends in Infodemiology and Infoveillance: Methodology Framework.

    Amaryllis Mavragani;Gabriela Ochoa

  • Assessing the Methods, Tools, and Statistical Approaches in Google Trends Research: Systematic Review

    Amaryllis Mavragani;Gabriela Ochoa;Konstantinos P Tsagarakis

  • Exploring Hyper-heuristic Methodologies with Genetic Programming

    Edmund K. Burke;Mathew R. Hyde;Graham Kendall;Gabriela Ochoa

  • HyFlex: a benchmark framework for cross-domain heuristic search

    Gabriela Ochoa;Matthew Hyde;Tim Curtois;Jose A. Vazquez-Rodriguez

  • A study of NK landscapes' basins and local optima networks

    Gabriela Ochoa;Marco Tomassini;Sebástien Vérel;Christian Darabos

  • A Classification of Hyper-Heuristic Approaches: Revisited

    Edmund K. Burke;Matthew R. Hyde;Graham Kendall;Gabriela Ochoa

  • A Reinforcement Learning-Great-Deluge Hyper-Heuristic for Examination Timetabling

    Ender Özcan;Mustafa Misir;Gabriela Ochoa;Edmund K. Burke

  • Contrasting meta-learning and hyper-heuristic research: the role of evolutionary algorithms

    Gisele L. Pappa;Gabriela Ochoa;Matthew R. Hyde;Alex A. Freitas

  • Effective learning hyper-heuristics for the course timetabling problem

    Jorge A. Soria-Alcaraz;Gabriela Ochoa;Jerry Swan;Martin Carpio

  • Local Optima Networks of NK Landscapes With Neutrality

    S. Verel;G. Ochoa;M. Tomassini

  • On Genetic Algorithms and Lindenmayer Systems

    Gabriela Ochoa

  • Local Optima Networks: A New Model of Combinatorial Fitness Landscapes

    Gabriela Ochoa;Sébastien Verel;Fabio Daolio;Marco Tomassini

  • Iterated local search vs. hyper-heuristics: Towards general-purpose search algorithms

    Edmund Burke;Tim Curtois;Matthew Hyde;Graham Kendall

  • A unified hyper-heuristic framework for solving bin packing problems

    Eunice López-Camacho;Hugo Terashima-Marin;Peter Ross;Gabriela Ochoa

  • An Integer Linear Programming approach to the single and bi-objective Next Release Problem

    Nadarajen Veerapen;Gabriela Ochoa;Mark Harman;Edmund K. Burke

  • Search trajectory networks: A tool for analysing and visualising the behaviour of metaheuristics

    Gabriela Ochoa;Katherine M Malan;Christian Blum

  • Analyzing the landscape of a graph based hyper-heuristic for timetabling problems

    Gabriela Ochoa;Rong Qu;Edmund K. Burke

  • Error thresholds in genetic algorithms

    Gabriela Ochoa

  • The Genetic and Evolutionary Computation Conference

    Gabriela Ochoa;Edmund Burke

  • HyFlex: A Benchmark Framework for Cross-domain Heuristic Search

    Edmund Burke;Tim Curtois;Matthew Hyde;Gabriela Ochoa

Frequent Co-Authors

Marco Tomassini
Marco Tomassini University of Lausanne
Edmund K. Burke
Edmund K. Burke Bangor University
Graham Kendall
Graham Kendall MILA University
Natalio Krasnogor
Natalio Krasnogor Newcastle University
Ender Özcan
Ender Özcan University of Nottingham
Christian Blum
Christian Blum Spanish National Research Council
Michel Gendreau
Michel Gendreau Polytechnique Montréal
L. Darrell Whitley
L. Darrell Whitley Colorado State University
Marc Schoenauer
Marc Schoenauer French Institute for Research in Computer Science and Automation - INRIA
Inman Harvey
Inman Harvey University of Sussex

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