Abstract
In this paper, the approach of incorporating Hopfield neural networks (HNN) into ant colony systems (ACS) is proposed and studied. In the proposed approach (HNNACS), HNN is used to find a plausibly good solution, which is then used in ACS as the currently best tour for the offline pheromone trail update. The idea is to deposit additional pheromone to ACS to enhance the search efficiency. From simulation results, the search efficiency of HNNACS is better than other existing algorithms.
This research was partly supported by the National Science Council, Taiwan, R.O.C. under grant NSC 97-2221-E-211 -017.
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References
Dorigo, M., Caro, G.D.: Ant colony optimization: A new meta-heuristic. In: Proceedings of the 1999 Congress on Evolutionary Computation, vol. 2, pp. 1470–1477 (1999)
Gambardella, L.M., Dorigo, M.: Solving Symmetric and Asymmetric TSPs by Ant Colonies. In: Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ECEC 1996), pp. 622–627. IEEE Press, Los Alamitos (1996)
http://www.iwr.uni-heidelberg.de/groups/comopt/software/TSPLIB95/
Stűtzle, T., Dorigo, M.: Ant Colony Optimization. MIT Press, Cambridge (2004)
Wilson, G.V., Pawley, G.S.: On the stability of the traveling salesman problems algorithm of Hopfield and Tank. Biological Cybernetics 58, 63–70 (1988)
Hopfield, J.J., Tank, D.W.: Neural computation of decisions in optimization problem. Biological Cybernetics 52, 141–152 (1985)
Talavan, P.M., Yanez, J.: Parameter setting of the Hopfield network applied to TSP. Neural Networks 15, 363–373 (2002)
Matsuda, S.: Optimal Hopfield network for combinatorial optimization with linear cost function. In: IEEE Int. Symp. Circuits Systems, pp. 2181–2184 (May 1989)
Wang, L., Smith, K.: On chaotic simulated annealing. IEEE Trans. Neural Networks 9(4), 716–718 (1998)
Aarts, E.H.L., Lenstra, J.K.: Local Search in Combinatorial Optimization. Wiley, New York (1997)
Kolen, A., Pesch, E.: Genetic local search in combinatorial optimization. Discrete Applied mathematics and Combinatorial Operations Research and Computer Science 48, 273–284 (1994)
Lee, Z.-J., Su, S.-F., Lee, C.-Y.: Efficiently Solving General Weapon-Target Assignment Problem by Genetic algorithms with Greedy Eugenics. IEEE Trans. Systems, Man and Cybernetics, Part B, 113–121 (2003)
Goldberg, D., Lingle, R., Alleles: Loci and traveling salesman problem. In: Proceedings of the Second International Conference on Genetic Algorithms. Lawerence Eribaum Associated, Mahwah (1985)
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Weng, YL., Lee, CY., Lee, ZJ. (2009). Incorporating Hopfield Neural Networks into Ant Colony System for Traveling Salesman Problem. In: Nakamatsu, K., Phillips-Wren, G., Jain, L.C., Howlett, R.J. (eds) New Advances in Intelligent Decision Technologies. Studies in Computational Intelligence, vol 199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00909-9_28
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DOI: https://doi.org/10.1007/978-3-642-00909-9_28
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