Combinatorial optimization using cooperative agent colonies and reinforced learning
DOI:
https://doi.org/10.31908/19098367.818Keywords:
Ant Colony, Optimization, Pheromone, TSPAbstract
They exist a set of problems, that by their size and complexity cannot to find solutions of good quality; The way as the nature solves this problems, has inspired to many investigators to develop algorithms that simulate these qualities, the present paper shows the advantages of the method "Ant Colony", their properties and applications. To measure the impact of the algorithm, the benchmark problem chosen was the "Traveling Salesman Problem" (TSP), since one is of more widely spread in specialized Literature.
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DORIGO M., Gambardella L. Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Transactions on Evolutionary Computation. 1(1):53-56. 1997.
DORIGO M., Maniezzo V., Colorni A.; Ant System: Optimization by a Colony of Cooperating Agents. IEEE Transactions on Systems, Man and Cybernetics 26 (1), pp 29- 41,1996.
DORIGO M., Stützle T. The Ant Colony Optimization Metaheuristic: Algorithms, Aplications, and Advances. Université Libre de Bruxelle, IRIDIA.
PARPINELLI R., Lopes H., Freitas A. Data Mining with Ant Colony Optimization Algorithm. IEEE Transactions on Evolutionary Computation. Vol. 6, No. 4. August 2000.
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