Ant Colony Optimization for Multi-objective Optimization Problems
Résumé
We propose in this paper a generic algorithm based on Ant Colony
Optimization metaheuristic (ACO) to solve multi-objective
optimization problems (PMO). The proposed algorithm is
parameterized by the number of ant colonies and the number of
pheromone trails. We compare different variants of this algorithm
on the multi-objective knapsack problem. We compare also the
obtained results with other evolutionary algorithms from the
literature.
Domaines
Informatique [cs]
Origine : Fichiers produits par l'(les) auteur(s)
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