Abstract
Ant-Q is an algorithm belonging to the class of ant colony based methods, that is, of combinatorial optimization methods in which a set of simple agents, called ants, cooperate to find good solutions to combinatorial optimization problems. The main focus of this article is on the experimental study of the sensitivity of the Ant-Q algorithm to its parameters and on the investigation of synergistic effects when using more than a single ant. We conclude comparing Ant-Q with its ancestor Ant System, and with other heuristic algorithms.
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Bersini H., C. Oury and M. Dorigo, 1995. Hybridization of genetic algorithms. Tech. Rep. No. IRIDIA/95-22, IRIDIA, Université Libre de Bruxelles, Belgium.
Colorni A., M. Dorigo and V. Maniezzo, 1991. Distributed Optimization by Ant Colonies. Proceedings of ECAL91 — European Conference on Artificial Life, Paris, France, F. Varela and P. Bourgine (Eds.), Elsevier Publishing, 134–142.
Colorni A., M. Dorigo and V. Maniezzo, 1992. An Investigation of some Properties of an Ant Algorithm. Proceedings of the Parallel Problem Solving from Nature Conference (PPSN 92), Brussels, Belgium, R. Männer and B. Manderick (Eds.), Elsevier Publishing, 509–520.
Dorigo M., 1992. Optimization, Learning and Natural Algorithms. Ph.D.Thesis, Politecnico di Milano, Italy. (In Italian).
Dorigo M., V. Maniezzo and A. Colorni, 1996. The Ant System: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics-Part B, 26, 2, 29–41.
Eilon S., C.D.T. Watson-Gandy and N. Christofides, 1969. Distribution management: mathematical modeling and practical analysis. Operational Research Quarterly, 20, 37–53.
Fischetti M. and P. Toth, 1992. An Additive Bounding Procedure for the Asymmetric Travelling Salesman Problem. Mathematical Programming, 53, 173–197.
Fischetti M. and P. Toth, 1994. A polyhedral approach for the exact solution of hard ATSP instances. Tech. Rep. OR-94, DEIS, Università di Bologna, Italy, April 1994.
Fogel D., 1993. Applying evolutionary programming to selected traveling salesman problems. Cybernetics and Systems: An International Journal, 24, 27–36.
Gambardella L. and M. Dorigo, 1995. Ant-Q: A Reinforcement Learning approach to the traveling salesman problem. Proceedings of ML-95, Twelfth International Conference on Machine Learning, Tahoe City, CA, A. Prieditis and S. Russell (Eds.), Morgan Kaufmann, 252–260.
Lin F.-T., C.-Y. Kao and C.-C. Hsu, 1993. Applying the genetic approach to simulated annealing in solving some NP-hard problems. IEEE Transactions on Systems, Man, and Cybernetics, 23, 1752–1767.
Watkins C.J.C.H., 1989. Learning with delayed rewards. Ph. D. dissertation, Psychology Department, University of Cambridge, England.
Whitley D., T. Starkweather and D. Fuquay, 1989. Scheduling Problems and Traveling Salesman: the Genetic Edge Recombination Operator. Proc. of the Third International Conference on Genetic Algorithms, Morgan Kaufmann, 133–140.
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© 1996 Springer-Verlag Berlin Heidelberg
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Dorigo, M., Gambardella, L.M. (1996). A study of some properties of Ant-Q. In: Voigt, HM., Ebeling, W., Rechenberg, I., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN IV. PPSN 1996. Lecture Notes in Computer Science, vol 1141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61723-X_1029
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DOI: https://doi.org/10.1007/3-540-61723-X_1029
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