RECURRENT NEURAL NETWORK WITH SOFT 'WINNER TAKES ALL' PRINCIPLE FOR THE TSP

Paulo Henrique Siqueira, Maria Teresinha Arns Steiner, Sérgio Scheer

2010

Abstract

This paper shows the application of Wang’s Recurrent Neural Network with the 'Winner Takes All' (WTA) principle in a soft version to solve the Traveling Salesman Problem. In soft WTA principle the winner neuron is updated at each iteration with part of the value of each competing neuron and some comparisons with the hard WTA are made in this work with instances of the TSPLIB (Traveling Salesman Problem Library). The results show that the soft WTA guarantees equal or better results than the hard WTA in most of the problems tested.

References

  1. Cochrane, E. M., Beasley, J. E. (2003). The Co-Adaptive Neural Network Approach to the Euclidean Travelling Salesman Problem. Neural Networks, 16 (10), 1499- 1525.
  2. Créput, J. C., Koukam, A., (2009). A memetic neural network for the Euclidean travelling salesman problem. Neurocomputing, 72 (4-6), 1250-1264.
  3. Glover, F., Gutin, G., Yeo, A., Zverovich, A., (2001). Construction heuristics for the asymmetric TSP. European Journal of Operational Research, 129 (3), 555-568.
  4. Hung, D. L., Wang, J. (2003). Digital Hardware realization of a Recurrent Neural Network for solving the Assignment Problem. Neurocomputing, 51, 447- 461.
  5. Jin, H. D., Leung, K. S., Wong, M. L., Xu, Z. B., (2003). An Efficient Self-Organizing Map Designed by Genetic Algorithms for the Traveling Salesman Problem. IEEE Transactions On Systems, Man, And Cybernetics - Part B: Cybernetics, 33 (6), 877-887.
  6. Leung, K. S., Jin, H. D., Xu, Z. B., (2004). An expanding self-organizing neural network for the traveling salesman problem. Neurocomputing, 62, 267-292.
  7. Li, M., Yi, Z., Zhu, M., (2009). Solving TSP by using Lotka-Volterra neural networks, Neurocomputing, 72 (16-18), 3873-3880.
  8. Masutti, T. A. S., Castro, L. N., (2009). A self-organizing neural network using ideas from the immune system to solve the traveling salesman problem. Information Sciences, 179 (10), 1454-1468.
  9. Misevicius, A., Smolinskas, J., Tomkevicius A., (2005). Iterated Tabu Search for the Traveling Salesman Problem: new results. Information Technology And Control, 34 (4), 327-337.
  10. Reinelt, G. (1991). TSPLIB - A traveling salesman problem library. ORSA Journal on Computing, 3 (4), 376-384.
  11. Siqueira, P. H., Steiner, M. T. A., Scheer, S., (2007). A new approach to solve the Traveling Salesman Problem. Neurocomputing, 70 (4-6), 1013-1021.
  12. Siqueira, P. H., Scheer, S., Steiner, M. T. A., (2008). A Recurrent Neural Network to Traveling Salesman Problem. In Greco, F. (Ed.), Travelling Salesman Problem (pp. 135-156). In-teh: Croatia.
  13. Wang, J. (1992). Analog Neural Network for Solving the Assignment Problem. Electronic Letters, 28 (11), 1047-1050.
  14. Wang, J. (1997). Primal and Dual Assignment Networks. IEEE Transactions on Neural Networks, 8 (3), 784- 790.
  15. Wang, Y., Feng, X. Y., Huang, Y. X., Pu, D. B., Liang, C.Y., Zhou, W.G., (2007). A novel quantum swarm evolutionary algorithm and its applications, Neurocomputing, 70 (4-6), 633-640.
  16. Yi, J., Yang, G., Zhang, Z., Tang, Z., (2009). An improved elastic net method for travelling salesman problem, Neurocomputing, 72 (4-6), 1329-1335.
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Paper Citation


in Harvard Style

Siqueira P., Arns Steiner M. and Scheer S. (2010). RECURRENT NEURAL NETWORK WITH SOFT 'WINNER TAKES ALL' PRINCIPLE FOR THE TSP . In Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010) ISBN 978-989-8425-32-4, pages 265-270. DOI: 10.5220/0003059102650270


in Bibtex Style

@conference{icnc10,
author={Paulo Henrique Siqueira and Maria Teresinha Arns Steiner and Sérgio Scheer},
title={RECURRENT NEURAL NETWORK WITH SOFT 'WINNER TAKES ALL' PRINCIPLE FOR THE TSP},
booktitle={Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)},
year={2010},
pages={265-270},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003059102650270},
isbn={978-989-8425-32-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)
TI - RECURRENT NEURAL NETWORK WITH SOFT 'WINNER TAKES ALL' PRINCIPLE FOR THE TSP
SN - 978-989-8425-32-4
AU - Siqueira P.
AU - Arns Steiner M.
AU - Scheer S.
PY - 2010
SP - 265
EP - 270
DO - 10.5220/0003059102650270