Embedded Files
Current doctoral students
Current doctoral students
Cristina Esteban Saster
Cristian Valdés Pérez
Past doctoral students
Past doctoral students
Dr. David J. Poza (Doctoral special award in Engineering- Universidad de Valladolid)
Dra. Virginia Ahedo (Doctoral special award in Engineering and Architecture - Universidad de Burgos)
Dra. Silvia Díaz-de la Fuente (Nominated for the Doctoral special award in Humanities and Communication - Universidad de Burgos)
Past postdoctoral fellows
Past postdoctoral fellows
Dra. María Pereda (Universidad Politécnica de Madrid)
If you're my student at the University of Burgos, you should visit the following link
Genetic Algorithms Lab: Interactive Teaching Tools
Genetic Algorithms Lab: Interactive Teaching Tools
An open-source, bilingual (English/Spanish) collection of interactive tools for teaching and learning genetic algorithms, from representing a solution to evolving a population. Students follow each operator step by step, predict the result and check it in practice mode, and compare alternative operators on the same data.
Five modules cover the whole workflow: representation, initialisation and evaluation, selection, crossover and mutation. Each one includes animations with explanations, pseudocode, and Python and JavaScript code; teachers can also use ready-made Moodle question banks. Two simulators show the complete algorithm across generations: EvoTraveller (travelling salesman problem) and SelectionMechanisms (selection pressure, convergence and diversity).
Web app · Source code · Archived on Zenodo (DOI 10.5281/zenodo.23834484)
Companion book (free, CC BY 4.0)
Companion book (free, CC BY 4.0)
Eleven chapters that guide readers through every decision in a genetic algorithm. Each example opens the matching tool with the same settings, so readers can reproduce it; in the PDF, these links are QR codes. Every chapter has exercises with solutions.
Evolución a la vista. Algoritmos genéticos en un laboratorio interactivo
Spanish original.
Evolution Made Visible: Genetic Algorithms in an Interactive Laboratory
English translation (AI-assisted, reviewed by the authors).
If you use these materials, please reference:
Galán, J. M., Díaz-de la Fuente, S., Ahedo, V., Pereda, M., & Santos, J. I. (2026). Evolución a la vista. Algoritmos genéticos en un laboratorio interactivo. Zenodo. https://doi.org/10.5281/zenodo.23835732
Galán, J. M., Díaz-de la Fuente, S., Ahedo, V., Pereda, M., & Santos, J. I. (2026). Evolution Made Visible: Genetic Algorithms in an Interactive Laboratory (English translation). Zenodo. https://doi.org/10.5281/zenodo.23890033
Santos, J. I., Ahedo, V., Pereda, M., & Galán, J. M. (2025). Interactive Visualization of Genetic Algorithm Solutions for the Traveling Salesman Problem: An Educational Tool. In Organizational Engineering, Coping with Complexity (CIO 2024), Lecture Notes on Data Engineering and Communications Technologies, vol. 239, pp. 6–10. Springer. https://doi.org/10.1007/978-3-031-82334-3_2
Galán, J. M., Díaz-de la Fuente, S., Ahedo, V., Pereda, M., & Santos, J. I. (in press). Visualizing Selection Pressure in Genetic Algorithms: An Interactive Tool for Convergence and Diversity Analysis. CIO 2026, Springer Lecture Notes.
* A paper describing the platform is in preparation
Visualizing Selection Pressure in Genetic Algorithms: An Interactive Tool for Convergence and Diversity Analysis
Visualizing Selection Pressure in Genetic Algorithms: An Interactive Tool for Convergence and Diversity Analysis
An interactive web application for exploring how selection mechanisms affect convergence and population diversity in genetic algorithms. Users can adjust selection parameters, run repeated simulations, and compare methods including tournament, roulette wheel, stochastic universal sampling, rank, truncation, and Boltzmann selection. The tool visualizes changes in fitness and diversity over generations to support teaching and experimentation.
You can find the web app here: https://josemagalan.shinyapps.io/SelectionMechanisms/
Source Code: https://github.com/josemagalan/SelectionMechanisms
If you use it, please reference this work:
Galán, J.M., Díaz-de la Fuente, S., Ahedo, V., Pereda, M., Santos, J.I. Visualizing Selection Pressure in Genetic Algorithms: An Interactive Tool for Convergence and Diversity Analysis. Accepted for publication in Lecture Notes on Data Engineering and Communications Technologies; publication details pending.
Interactive Visualization of Genetic Algorithm Solutions for the Traveling Salesman Problem: An Educational Tool
Interactive Visualization of Genetic Algorithm Solutions for the Traveling Salesman Problem: An Educational Tool
An educational tool for visualizing genetic algorithm solutions for the Traveling Salesman Problem. The tool, developed as a web-based application, provides an interactive experience to explore the algorithm's approach to the problem. The application graphically represents the evolution of solutions over generations, offering insights into the algorithm's convergence and effectiveness. Key features include visualizations of the fitness evolution, optimal solutions, and the entire solution population, enhancing comprehension of the algorithmic processes and decision-making in optimization challenges.
You can find the web app here: https://evotraveller.streamlit.app/
Source Code: https://github.com/jismartin/evotraveller
If you use it, please reference this work:
- Santos, J., Ahedo, V., Pereda, M., Galán, J. (2025). Interactive Visualization of Genetic Algorithm Solutions for the Traveling Salesman Problem: An Educational Tool. In: Carrasco-Gallego, R., Moreno-Serna, J., Gutierrez, M., Avilés-Palacios, C. (eds) Organizational Engineering, Coping with Complexity. CIO 2024. Lecture Notes on Data Engineering and Communications Technologies, vol 239. Springer, Cham. https://doi.org/10.1007/978-3-031-82334-3_2
NetLogo Teaching Tool to Illustrate the Cooling Process in Simulated Annealing Using the Metropolis Model
NetLogo Teaching Tool to Illustrate the Cooling Process in Simulated Annealing Using the Metropolis Model
In this work, we present a teaching tool implemented in NetLogo that illustrates the metaphor of both processes and the effect of annealing cooling schedules on the quality of the solutions obtained.
The tool can be downloaded from https://www.comses.net/codebases/6088b061-d836-4f98-9945-0601aafe0570/releases/1.0.0/ in two different versions (A and B), which differ in the type of dynamic visualization offered.
If you use it, please reference this work:
- Santos, J.I., Pereda, M., Ahedo, V., Galán, J.M. (2023). NetLogo Teaching Tool to Illustrate the Cooling Process in Simulated Annealing Using the Metropolis Model. In: Izquierdo, L.R., Santos, J.I., Lavios, J.J., Ahedo, V. (eds) Industry 4.0: The Power of Data. Lecture Notes in Management and Industrial Engineering, vol 160, pp.19-27. Springer, Cham. https://doi.org/10.1007/978-3-031-29382-5_3
NetExtractor
NetExtractor
NetExtractor is a web software to generate interaction networks between characters from script movies (in imsdb database) or novels (in ePub format).
The original web application is currently unavailable. Project documentation.
If you use it, please reference this work:
- Cabrejas-Arce L.M., Navarro J., Ahedo V., Galán J.M. (2021) NetExtractor. A Semi-automatic Educational Tool for Network Extraction Conceived to Differentiate by Student Interest. In: Herrero Á., Cambra C., Urda D., Sedano J., Quintián H., Corchado E. (eds) The 11th International Conference on EUropean Transnational Educational (ICEUTE 2020). ICEUTE 2020. Advances in Intelligent Systems and Computing, vol 1266. Springer, Cham. https://doi.org/10.1007/978-3-030-57799-5_22
Online lessons (Mostly in Spanish)
Online lessons (Mostly in Spanish)
Curso completo de teoría de redes (in Spanish) - Course in Network Science
Other teaching stuff
Other teaching stuff
Gamification in Management Engineering: Video · Interactive games repository · Learning assistant · Code and documentation
Lecture notes in MS Project (In Spanish). Apuntes MS Project
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