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

Paulo Henrique Siqueira, Maria Teresinha Arns Steiner, Sérgio Scheer

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

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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