Browsing by Author "Herrera Triguero, Francisco"

Now showing items 1-8 of 8

    • A multicriteria genetic tuning for fuzzy logic controllers 

      Alcalá Fernández, Rafael; Casillas Barranquero, Jorge; Castro Peña, Juan Luis; González Muñoz, Antonio; Herrera Triguero, Francisco (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 2001)
      Article
      Open Access
      This paper presents the use of genetic algorithms to develop smartly tuned fuzzy logic controllers in multicriteria complex problems. This tuning approach has some specific restrictions that make it very particular and ...

    • A review on the ant colony optimization metaheuristic: basis, models and new trends 

      Cordón García, Oscar; Herrera Triguero, Francisco; Stützle, Thomas (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 2002)
      Article
      Open Access
      Ant Colony Optimization (ACO) is a recent metaheuristic method that is inspired by the behavior of real ant colonies. In this paper, we review the underlying ideas of this approach that lead from the biological inspiration ...

    • Analysis of the best-worst ant system and its variants on the TSP 

      Cordón García, Oscar; Fernández de Viana, Iñaki; Herrera Triguero, Francisco (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 2002)
      Article
      Open Access
      In this contribution, we will study the influence of the three main components of Best-Worst Ant System: the best-worst pheromone trail update rule, the pheromone trail mutation and the restart. Both the importance of ...

    • Analyzing the reasoning mechanisms in fuzzy rule based classification systems 

      Cordón García, Oscar; Jesús Díaz, Ma José del; Herrera Triguero, Francisco (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 1998)
      Article
      Open Access
      Fuzzy Rule-Based Systems have been succesfully applied to pattern classification problems. In this type of classification systems, the classical Fuzzy Reasoning Method classifies a new example with the consequent of the ...

    • Ant colony optimization: models and applications [Guest editorial] 

      Cordón García, Oscar; Herrera Triguero, Francisco; Stützle, Thomas (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 2002)
      Review
      Open Access
      Ant Colony Optimization (ACO) is a metaheuristic that is inspired by the shortest path searching behavior of various ant species [1,2]. The initial work of Dorigo, Maniezzo and Colorni [3,4] who proposed the first ACO ...

    • Improvement to the cooperative rules methodology by using the ant colony system algorithm 

      Alcalá Fernández, Rafael; Casillas Barranquero, Jorge; Cordón García, Oscar; Herrera Triguero, Francisco (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 2001)
      Article
      Open Access
      The cooperative rules (COR) methodology [2] is based on a combinatorial search of cooperative rules performed over a set of previously generated candidate rule consequents. It obtains accurate models preserving the highest ...

    • Multi-stage genetic fuzzy systems based on the iterative rule learning approach 

      González Muñoz, Antonio; Herrera Triguero, Francisco (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 1997)
      Article
      Open Access
      Genetic algorithms (GAs) represent a class of adaptive search techniques inspired by natural evolution mechanisms. The search properties of GAs make them suitable to be used in machine learning processes and for developing ...

    • The use of fuzzy connectives to design real-coded genetic algorithms 

      Herrera Triguero, Francisco; Lozano, M.; Verdegay, José Luis (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 1994)
      Article
      Open Access
      Genetic algorithms are adaptive methods that use principles inspired by natural population genetics to evolve solutions to search and optimization problems. Genetic algorithms process a population of search space solutions ...