Metaheuristics for Combinatorial Optimization and Modelling Complex Systems

Hybrid Artificial Intelligent Systems (HAIS) have been engaged in recent years to obtain better models and address complex problems by means of the combination and association of several different techniques from artificial intelligence such as neuro-fuzzy systems, genetic fuzzy systems, fuzzy experts systems, swarm intelligence techniques, evolutionary models, multi-agent systems, etc. Complexity, emergence and self-organization represent essential aspects of today’s world real systems. The study and in-depth analysis of these elements needs computational perspectives able to significantly impact the study of complexity and the solving process of dynamic complex problems. Furthermore, real-world complex problems usually involve imprecision, uncertainty and vagueness in their data and measurements. Because of their inherent complexity and uncertainty they usually can not be modeled with only one technique, and multiple/hybrid methods are needed. This session is concerned with the new metaheuristics in HAIS, particularly those applied to combinatorial optimization and modeling complex systems.

More info about this Special Session:

  • Co-Chairs
  1. Camelia Chira, Computer Science Department, University of Babes-Bolyai, Romania
  2. Enrique de la Cal, Computer Science Department, University of Oviedo, Spain
  3. Petrica Pop, Department of Mathematics and Informatics, North University, Romania.
  4. José Ramón Villar, Computer Science Department, University of Oviedo, Spain

  • Contact information
  • José Ramón Villar
  • Computer Science Department, University of Oviedo
    Affiliation. Computer Science Department, University of Oviedo
  • Postal address. 33204
  • Telephone number. +34 985182597
  • Fax Number. +34 985181986

Important Dates


Paper submission


These papers go through the same reviewing and selection process like those submitted regularly