Máster de Estructuras

Curso: Optimización y Computación Inteligente

Francisco Herrera (Dpto. de Ciencias de la Computación e I.A.)

Documentación

  • Sesión 0: Algoritmos Evolutivos en Ingeniería Civil. 
  • Sesión 1: Algoritmos Genéticos. 
  • Sesión 2: Algoritmos Bioinspirados. 
  • Código: Código de Algoritmos Genéticos en Fortran. 
  • Metodología de la investigación
  • Bibliometría: Evaluación de la ciencia

Bibliografía complementaria

  • Swarm Intelligence
    • S. Garnier, J. Gautrais, G. Theraulaz. The biologicalprinciples of swarm intelligence. Swarm Intelligence 1(2007) 3-31.
    • S. Alonso, O. Cordón, I. Fernández de Viana y F. Herrera. La Metaheurística de Optimización Basada en Colonias de Hormigas: Modelos y Nuevos Enfoques. In: G. Joya, M.A. Atencia, A. Ochoa, S. Allende (Eds.), Optimizacion Inteligente: Técnicas de Inteligencia Computacional para Optimización, 2004, Servicio de Publicaciones de la Universidad de Málaga, 261-313.
    • O. Cordón, F. Herrera and T. Stützle. A Review on the Ant Colony Optimization Metaheuristic: Basis, Models and New Trends. Mathware and Soft Computing 9:2-3, 2002, pp. 141-175. 
    • M. Dorigo, T. Stützle. Chapter 9: The ant colony optimization metaheuristic: Algorithms, applications and advances. In: F. Glover, G.A. Kochenberber, (Eds.). Handbook of Metaheuristics. Kluwer Academics (2003) 251-285.
    • R. Poli, J. Kennedy, T. Blackwell. Particle swarm optimization: An overview. Swarm Intelligence 1 (2007) 33-57.
  • Algoritmos Genéticos
    • Tutorial: Darrell Whitley, A Genetic AlgorithmTutorial, Statistics and Computing, 4, (1994), 65-85.
    • C.Reeves. Chapter 3: Genetic Algorithms. In: F. Glover, G.A.Kochenberber, (Eds.). Handbook of Metaheuristics. Kluwer Academics.(2003) 55-82. 
    • D.E. Goldberg, Genetic Algorithms in Search, Optimization andMachine Learning. Addison Wesley, 1989.
    • Z. Michalewicz, Genetic Algorithms + Data Structures = EvolutionPrograms. Springer Verlag, 1996.
    • D.B. Fogel (Ed.) Evolutionary Computation. The Fossil Record.(Selected Readings on the History of Evolutionary Computation). IEEEPress, 1998.
    • A.E. Eiben, J.E. Smith. Introduction to Evolutionary Computation.Springer Verlag 2003. (Natural Computing Series)
    • F.Herrera, M. Lozano, J.L. Verdegay, Tackling Real-Coded GeneticAlgorithms: Operators and tools for the Behaviour Analysis. ArtificialIntelligence Review 12 (1998) 265-319. 
    • S.Ventura, C. Romero, A. Zafra, J.A. Delgado, C. Hervás-Martínez. JCLEC:A Java Framework for Evolutionary Computing. Soft Computing 12:4 (2008) 381-392. 
  • Algoritmos Genéticos Multiobjetivo
    • C.A. Coello, D.A. Van Veldhuizen, G.B. Lamont, Evolutionary Algorithms for Solving Multi-Objective Problems. Kluwer Academic Publishers, Second Edition, 2007.
    • K. Deb, Multi-Objective Optimization using Evolutionary Algorithms. John Wiley & Sons, 2001
    • E. Zitzler, L. Thiele. Multiobjective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approach. IEEE Transactions on Evolutionary Computation 3:4 (1999) 257-217.
    • E. Zitzler, K. Deb, L. Thiele. Comparison of Multiobjetive Evolutionary Algorithms: Empirical Results. Evolutionary Computation 8:2 (2000) 173-195.
    • Eckart Zitzler, Marco Laumanns, Lothar Thiele: SPEA2: Improving the Strength Pareto Evolutionary Algorithm. Zürich, TIK Report Nr. 103, Computer Engineering and Networks Lab (TIK), Swiss Federal Institute of Technology (ETH) Zurich, May, 2001.
    • K. Deb, A. Pratap, S. Agarwal and T. Meyarivan. A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6:2 (2002) 182-197. 
    • C.A. Coello. Evolutionary Multiobjective Optimization: Current and Future Challenges. In J. Benitez, O. Cordon, F. Hoffmann, and R. Roy (Eds.), Advances in Soft Computing---Engineering, Design and Manufacturing. Springer-Verlag, September, 2003, pp. 243 - 256.
    • E. Zitzler, L. Thiele, M. Laumanns, C.M. Fonseca, and V. Grunert da Fonseca. Performance Assessment of Multiobjective Optimizers: An Analysis and Review. IEEE Transactions on Evolutionary Computation 7:2, April, 2003, pp. 117 - 132.
    • M. Laumanns, L. Thiele, K. Deb, and E. Zitzler. Combining Convergence and Diversity in Evolutionary Multi-objective Optimization. Evolutionary Computation 10:3, Fall, 2002, pp. 263 - 282. 
    • K. Deb, L. Thiele, M. Laumanns, and E. Zitzler. Scalable Test Problems for Evolutionary Multiobjective Optimization. In A. Abraham, L. Jain, and R. Goldberg (Eds.), Evolutionary Multiobjective Optimization. Theoretical Advances and Applications. Springer, USA, 2005, pp. 105 - 145.