University of Stirling
Local Optima
Computing Science & Maths
ProfilesORCID   R. Gate   ACM DL    Springer
G. Scholar    DBPL     Scopus
Publications (All)
Online Contributions
Journal Papers
Best Paper Awards and Selected Conference papers
Book Chapters
Co-authorship Networks
GECCO       PPSN        EA
Lindenmayer Systems
Cross Domain Search 2011
Computing  Science and Mathematics
School of Natural Sciences
University of Stirling
Stirling FK9 4LA
Scotland, UK

Cottrel Building, Room: 4B118
+44(0) 1786 46-7438

Gabriela Ochoa

Gabriela Ochoa
is a Professor in Computing Science at the University of Stirling, Scotland.  She received BSc and MSc degrees in Computer Science from University Simon Bolivar, Venezuela and a PhD from University of Sussex, UK.  She worked in industry for 5 years before joining academia, and has held faculty and research positions at the University Simon Bolivar, Venezuela and the University of Nottingham, UK.  Her research interests lie in the foundations and application of evolutionary algorithms and heuristic search methods, with emphasis on autonomous search, hyper-heuristics, fitness landscape analysis, and applications to combinatorial optimisation, healthcare, and software engineering. She has published over 120 scholarly papers and serves various program committees. She has been associate editor of the IEEE Transactions on Evolutionary Computation, and the Evolutionary Computation Journal (MIT Press); and is a member of the Editorial Board for Genetic Programming and Evolvable Machines. She proposed the he first Cross-domain Heuristic Search Challenge (CHeSC 2011), has served as organiser and/or program chair for EvoCOP 2014, EvoCOP 2015FOGA 2015, PPSN 2016, and  served as the Editor-in-Chief for GECCO 2017

Editorial Roles

Conference Organisation


  • Website: Our goal is to develop and establish a set of methodologies, visualisation techniques and metrics to thoroughly characterise and exploit the structure of computational search spaces. This website intends to be a unified resource space offering a new perspective to understand problem structure and improve heuristic search algorithms.

Keynote Talks (TBC)

Best Paper Awards, Nominations and Selected Conference Papers

Online Contributions

                            Collaboration Co-authorship Networks
Introduction to
Lindenmayer Systems lsys
HyFlex and the
Cross-Domain Competitionchesc

Journal Papers

  1.  A. Mavragani, G. Ochoa (2018) Internet and the Anti-Vaccine Movement: Tracking the 2017 EU Measles Outbreak. Big Data and Cognitive Computing. Special issue on Health Assessment in the Big Data Era. Published online 13  January 2018  [Online]
  2. G. Ochoa, N. Veerapen. Mapping the global structure of TSP fitness landscapes. Journal of Heuristics, published online 29 May 2017. DOI:10.1007/s10732-017-9334-0 [dataset]
  3.  S. Herrmann G. Ochoa, F. Rothlauf. PageRank centrality for performance prediction: the impact of the local optima network model. Journal of Heuristics, published online 12 May 2017. DOI:10.1007/s10732-017-9333-1
  4. J. A. Soria-Alcaraz, G. Ochoa, M. A. Sotelo-Figeroa, E. K. Burke (2017) A methodology for determining an effective subset of heuristics in selection hyper-heuristics, European Journal of Operational Research. 260(3):  972–983 [Online]
  5. I. K. Paterson, A.S. Hoyle G. Ochoa, C. Baker-Austin and N.G.H. Taylor (2016) Optimising Antibiotic Usage to Treat Bacterial Infections. Nature Scientific Reports, 6, 37853; doi: 10.1038/srep37853 [Online]
  6. A. Sosa-Ascencio, G. Ochoa, H. Terashima-Marin, and S. E  Conant-Pablos (2016) Grammar-Based Generation of Variable-Selection Heuristics for Constraint Satisfaction Problems. Genetic Programming and Evolvable Machines, 17(2): 119-144. [Online version]
  7. N. Veerapen, G. Ochoa, M. Harman and E. Burke (2015) An Integer Linear Programming Approach to the Single and Bi-Objective Next Release Problem Information and Software Technology, Elsevier. Volume 65, September 2015, Pages 1–13 [Online version]
  8. D. Whitley, A. Sutton,  G. Ochoa, F. Chicano (2014) The Component Model for Elementary Landscapes and Partial Neighborhoods, Theoretical Computer Science (Special Issue: Theory of Evolutionary Algorithms).545: 59-75 (2014). [Online version] [bib entry]
  9. J.A Soria-Alcaraz,   G. Ochoa, J. Swan, M. Carpio,  H. Puga , E.K. Burke (2014) Effective Learning Hyper-heuristics for the Course Timetabling Problem. European Journal of Operational Research. 238(1): 77-86 [Online version] [bib entry]
  10. E. López-Camacho, H. Terashima-Marin, P. Ross, G. Ochoa (2014) A Unified Hyper-heuristic Framework for Solving Bin Packing Problems, Expert Systems with Applications. 41(15): 6876-6889 [Online version]  [bib entry]
  11. G.L. Pappa, G. Ochoa, M.R. Hyde, A.A. Freitas, J. Woodward, J. Swan (2014) Contrasting meta-learning and hyper-heuristic research: the role of evolutionary algorithms, Genetic Programming and Evolvable Machines 15(1): 3-35 [Online version] [bib entry]
  12. G. Ochoa, M. Villasana (2013) Population-based optimization of cytostatic/cytotoxic combination cancer chemotherapy, Soft Computing. Vol 17, No. 6, pp. 913-924. [Online version] [bib entry]
  13. E. K. Burke, M. Gendreau, M. Hyde, G. Kendall, G. Ochoa, E. Ozcan and R. Qu (2013) Hyper-heuristics: A Survey of the State of the Art, Journal of the Operational Research Society. 206(1): 241-264 [Online version] [bib entry]
  14. E. López-Camacho, G. Ochoa,  H. Terashima-Marin, E. K.  Burke (2013) An Effective Heuristic for the Two-dimensional Irregular Bin Packing Problem, Annals of Operations Research Vol. 206, Issue 1, pp.  241-264.  [Online version] [bib entry] [Source code (Java)] [Instance data: Set 1, Set 2]
  15. E. López-Camacho, H. Terashima-Marín, G. Ochoa, and S. E. Conant-Pablos (2013) Understanding the structure of bin packing problems through principal component analysisInternational Journal of Production Economics Vol. 145, No. 2, pp. 488-499. Special Issue on Cutting and Packing. [Description of the concave shape instance generator][Online version][bib entry].
  16. J. Swan, G. Ochoa,  G. Kendall, M. Edjvet (2012) Fitness Landscapes and the Andrew-Curtis ConjectureInternational Journal of Algebra and Computation, Vol. 2, No. 22, pp. 125009 (13 pages)
  17. S. Verel, G. Ochoa, M. Tomassini (2011) Local Optima Networks of NK Landscapes with Neutrality IEEE Transactions on Evolutionary Computation,Vol 15, No. 6, pp. 783-797. link to IEEXplore.
  18. F. Daolio, M. Tomassini, S. Verel, G. Ochoa (2011) Communities of Minima in Local Optima Networks of Combinatorial Spaces, Physica A: Statistical Mechanics and its Applications, Vol. 390, pp. 1684-1694.
  19. J. A. Vazquez-Rodriguez, G. Ochoa (2011) On the Automatic Discovery of Variants of the NEH Procedure for Flowshop Scheduling Using Genetic Programming, Journal of the Operations Research Society, 62(2), pp. 381-396, link to Journal.
  20. M. Villasana, G. Ochoa, S. Aguilar (2010) Modeling and Optimization of Combined Cytostatic and Cytotoxic Chemotherapy, Artificial Intelligence in Medicine, vol. 50, pp. 163 - 173.
  21. E. Özcan, M. Mısır, G. Ochoa, E. K. Burke (2010). A Reinforcement Learning - Great-Deluge Hyper-heuristic for Examination Timetabling, International Journal of Applied Metaheuristic Computing (IJAMC), 1:1, pp 39-59.
  22. M. Tomassini, S. Verel, G. Ochoa (2008) Complex-Network Analysis of Combinatorial Spaces: The NK landscape case, Physical Review E, Vol.78, No.6. ( link to journal)
  23. G. Ochoa, M. Villasana, and E. K. Burke (2007) An Evolutionary Approach to Cancer Chemotherapy Scheduling, Genetic Programming and Evolvable Machines Journal, 8:4, Springer, pp 301-318.
  24. G. Ochoa (2006) Error Thresholds in Genetic Algorithms. Evolutionary Computation Journal, 14:2, pp 157-182,  MIT Press.
  25. M. Villasana, G. Ochoa (2004) Heuristic Design of Cancer Quemotherapies. IEEE Transactions on Evolutionary Computation, 8:6, pp 513-521.
  26. G. Ochoa, K. Jaffe (1999) On Sex, Parasites, and the Red QueenJournal of Theoretical Biology, 199, pp 1-9.

Edited Volumes



  • P-I: The Cartography of Computational Search Spaces. Research grant funded by The Leverhulme Trust. March 2106 - February 2018.
  • Co-I: Dynamic Adaptive Automated Software Engineering (DAASE). Programme grant funded by the Engineering and Physical Sciences Research Council (EPSRC), collaboration with 5 Universities across the UK: UCL, Queen Mary, Stirling, York and Birmingham.  June 2012 - Marc 2019.
  • Co-I: Controlling Antibiotic Resistance in Aquatic Environments. University of Stirling IMPACT Research Partnership Studentships. In collaboration with the governmental agency Cefas (Centre for Environment, Fisheries and Aquaculture Science). October 2013 – September 2017.

Book Chapters

  1. G. Ochoa, S. Verel, F. Daolio and M. Tomassini (2014) Local Optima Networks: A New Model of
    Combinatorial Fitness Landscapes
    , Recent Advances in the Theory and Application of Fitness Landscapes. A. Engelbecht and H. Richter (Eds.), Emergence, Complexity and Computation, Vol. 6, pp. 233-262. Springer. [online version] [bib entry]
  2. G. Ochoa (2011) [in Spanish] Introduccion a la Computacion Evolutiva y la Morfogenesis Artificial, Evolution, Bicentenario del Nacimiento de Charles Darwin, Editorial Equinoccio.
  3. E. K. Burke,  M. Hyde, G. Kendall, G. Ochoa, E. Ozcan, and J. Woodward (2010). A Classification of Hyper-heuristics Approaches, Handbook of Metaheuristics,  International Series in Operations Research & Management Science, M. Gendreau and J-Y Potvin (Eds.), Springer, pp.449-468.
  4. E. K. Burke, M. R. Hyde, G. Kendall,  G. Ochoa, E. Ozcan and J. R. Woodward (2009)  Exploring Hyper-heuristic Methodologies with Genetic ProgrammingComputational Intelligence: Collaboration, Fusion and Emergence, In C. Mumford and L. Jain (eds.), Intelligent Systems Reference Library, Springer, pp. 177-201.
  5. G. Ochoa,  I. Harvey  (1999) Recombination and Error Thresholds in Finite Populations. Foundations of Genetic Algorithms 5 (FOGA 5), Edited by Wolfgang Banzhaf and Colin Reeves, pp 245-264, Morgan Kaufmann, San Francisco, CA.

Last Update: 12 March 2020.