A New Approach for Dynamic Parametrization of Ant System Algorithms

This paper proposes a learning approach for dynamic parameterization of ant colony optimization algorithms. In fact, the specific optimal configuration for each optimization problem using these algorithms, whether at the level of preferences, the level of evaporation of the pheromone, or the number...

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Veröffentlicht in:	International journal of intelligent systems and applications 2018-06, Vol.10 (6), p.1-12
Hauptverfasser:	MASROUR, Tawfik, RHAZZAF, Mohamed
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Ant colony optimization Configurations Machine learning Parameterization Termites
Online-Zugang:	Volltext
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