2018
DOI: 10.5815/ijisa.2018.06.01
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A New Approach for Dynamic Parametrization of Ant System Algorithms

Abstract: Abstract-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 of ants, makes the dynamic approach an interested one. The new idea suggests the addition of a knowledge center shared by the colony members, combining the optimal evaluation of the configuration parameters… Show more

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