This paper covers a multi-objective Ant Colony Optimization, which is applied to the N P-complete multi-objective shortest path problem in order to approximate Pareto-fronts. The efficient single-objective solvability of the problem is used to improve the results of the ant algorithm significantly. A dynamic program is developed which generates local heuristic values on the edges of the problem graph. These heuristic values are used by the artificial ants.
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