Ant Colony Optimization for Multi-objective Optimization Problems

Abstract

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.