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International Conference on Neural Information Processing

ICONIP 2011: Neural Information Processing pp 389–394Cite as

Method of Solving Combinatorial Optimization Problems with Stochastic Effects

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7064))

Abstract

The higher order connections network is useful to solve the combinatorial optimization problems, however, the network topology is complicated so that implementation on hardware is not easy. To implement the higher order connections more simply, we introduce the stochastic logic architecture to the discrete hysteresis network with the higher order connections. The proposed network can solve a Traveling Salesman Problems as the conventional network.

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References

  1. Hayakawa, Y., Nakajima, K.: Design of the inverse function delayed neural network for solving combinatorial optimization problems. IEEE Trans. Neural Netw. 21(2), 224–237 (2010)

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  2. Sota, T., Hayakawa, Y., Sato, S., Nakajima, K.: An application of higher order connection to inverse function delayed network. Nonlinear Theory and Its Applications, IEICE 2(2), 180–197 (2011)

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  3. Kondo, Y., Sawada, Y.: Functional abilities of a stochastic logic nerual network. IEEE Trans. Neural Netw. 3(3), 434–443 (1992)

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  4. Sota, T., Hayakawa, Y., Sato, S., Nakajima, K.: Discrete higher order inverse function delayed network. In: Proc. NOLTA 2010, pp. 615–618 (2010)

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Author information

Authors and Affiliations

  1. The Laboratory for Brainware/Laboratory for Nanoelectronics and Spintronics, Research Institute of Electrical Communication, Tohoku University, 2-1-1 Katahira, Aoba-Ku, Sendai, 980-8577, Japan

    Takahiro Sota, Shigeo Sato & Koji Nakajima

  2. Department of Information Systems, Sendai National College of Technology, 4-16-1 Ayashi-Chuoh, Aoba-Ku, Sendai, 989-3128, Japan

    Yoshihiro Hayakawa

Authors
  1. Takahiro Sota
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  2. Yoshihiro Hayakawa
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  3. Shigeo Sato
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  4. Koji Nakajima
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800, Dongchuan Road, 200240, Shanghai, China

    Bao-Liang Lu  & Liqing Zhang  & 

  2. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China

    James Kwok

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© 2011 Springer-Verlag Berlin Heidelberg

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Sota, T., Hayakawa, Y., Sato, S., Nakajima, K. (2011). Method of Solving Combinatorial Optimization Problems with Stochastic Effects. In: Lu, BL., Zhang, L., Kwok, J. (eds) Neural Information Processing. ICONIP 2011. Lecture Notes in Computer Science, vol 7064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24965-5_44

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  • DOI: https://doi.org/10.1007/978-3-642-24965-5_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24964-8

  • Online ISBN: 978-3-642-24965-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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