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Four-Quadrant Division with HNN for Euclidean TSP

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7390))

Abstract

The Traveling Salesman Problem (TSP) is a renowned combinatorial optimization problem and has caught great attention of scientists from all over the world. In this study, an algorithm of Four-quadrant Division (FQD), which in each time divides a part of the map into four equivalent quadrants until the number of cities at each part of map is suitable for HNN to create tours, is applied to TSP. Also, a path relinking method is proposed to relink each part of a map to compose a global tour.

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References

  1. Aiyer, S.V.B., Niranjan, M., Fallside, F.: A theoretical Investigation into The Performance of The Hopfield Model. IEEE Transactions on Neural Network I(2), 204–215 (1990)

    Article  Google Scholar 

  2. Punnen, A.P.: The Traveling Salesman Problem: Application, Formulations and Variations. In: Gutin, G., Punnen, A.P. (eds.) The Traveling Salesman Problem and Its Variations, pp. 1–28. Kluwer, Norwell (2002)

    Google Scholar 

  3. Yang, H.Q., Yang, H.H.: An Self-organizing Neural Network with Convex-hull Expanding Property for TSP. IEEE (2005)

    Google Scholar 

  4. http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/

  5. Li, M.L., Zhang, Y., Zhu, M.: Solving TSP by using Lotka-Volterra Neural Networks. Neurocomputing, 0925–2312/$ - see front matter © 2009 Elsevier B.V

    Google Scholar 

  6. Pedro, M., Talavan, J.Y.: Parameter Setting of The Hopfield Network Applied to TSP. Neural Network 15, 363–373 (2002)

    Article  Google Scholar 

  7. Li, Y., Tang, Z., Xia, G.P., Wang, R.L., Xu, X.S.: A Fast and Reliable Approach to TSP using Positively Self-feedbacked Hopfield Networks. Hokkaido Institute of Tecnology, Japan (2004)

    Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Yu, KF., Zeng, KH. (2012). Four-Quadrant Division with HNN for Euclidean TSP. In: Huang, DS., Ma, J., Jo, KH., Gromiha, M.M. (eds) Intelligent Computing Theories and Applications. ICIC 2012. Lecture Notes in Computer Science(), vol 7390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31576-3_7

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  • DOI: https://doi.org/10.1007/978-3-642-31576-3_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31575-6

  • Online ISBN: 978-3-642-31576-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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