Ant Colony Optimization for Multi-Objective Optimization Problems

We propose in this paper a generic algorithm based on ant colony optimization to solve multi-objective optimization problems. 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.

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