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

Autores: Óscar Cordón García , Francisco Herrera Triguero , Thomas Stützle
Localización: Mathware & soft computing: The Magazine of the European Society for Fuzzy Logic and Technology, ISSN-e 1134-5632, Vol. 9, Nº. 3, 2002, págs. 141-175
Idioma: inglés
Títulos paralelos:
- Una revisión de la metaheurística de optimización basada en colonias de hormigas: fundamentos, modelos y nuevas tendencias
Enlaces
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Resumen
- 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 to the ACO metaheuristic, which gives a set of rules of how to apply ACO algorithms to challenging combinatorial problems. We present some of the algorithms that were developed under this framework, give an overview of current applications, and analyze the relationship between ACO and some of the best known metaheuristics. In addition, we describe recent theoretical developments in the field and we conclude by showing several new trends and new research directions in this field.