Abstract
Ant Colony Optimization (ACO) is a metaheuristic inspired by the foraging behavior of ant colonies that has empirically shown its effectiveness in the resolution of hard combinatorial optimization problems like the Traveling Salesman Problem (TSP). Still, very little theory is available to explain the reasons underlying ACO’s success. An ACO alternative called Omicron ACO (OA), first designed as an analytical tool, is presented. This OA is used to explain the reasons of elitist ACO’s success in the TSP, given a globally convex structure of its solution space.
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Gómez, O., Barán, B. (2004). Reasons of ACO’s Success in TSP. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2004. Lecture Notes in Computer Science, vol 3172. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28646-2_20
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DOI: https://doi.org/10.1007/978-3-540-28646-2_20
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