Method of solving combinatorial optimization problems with stochastic effects

Takahiro Sota; Yoshihiro Hayakawa; Shigeo Sato; Koji Nakajima

doi:10.1007/978-3-642-24965-5_44

Method of solving combinatorial optimization problems with stochastic effects

Takahiro Sota, Yoshihiro Hayakawa, Shigeo Sato, Koji Nakajima

RIEC - Computing System Platforms Division

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings
Pages	389-394
Number of pages	6
Edition	PART 3
DOIs	https://doi.org/10.1007/978-3-642-24965-5_44
Publication status	Published - 2011
Event	18th International Conference on Neural Information Processing, ICONIP 2011 - Shanghai, China Duration: 2011 Nov 13 → 2011 Nov 17

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 3
Volume	7064 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Conference on Neural Information Processing, ICONIP 2011
Country/Territory	China
City	Shanghai
Period	11/11/13 → 11/11/17

Keywords

Energy function
Higher order connections
Hysteresis neural network
Quartic form
Traveling Salesman Problems

Access to Document

10.1007/978-3-642-24965-5_44

Cite this

Sota, T., Hayakawa, Y., Sato, S., & Nakajima, K. (2011). Method of solving combinatorial optimization problems with stochastic effects. In Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings (PART 3 ed., pp. 389-394). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7064 LNCS, No. PART 3). https://doi.org/10.1007/978-3-642-24965-5_44

Sota, Takahiro ; Hayakawa, Yoshihiro ; Sato, Shigeo et al. / Method of solving combinatorial optimization problems with stochastic effects. Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings. PART 3. ed. 2011. pp. 389-394 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).

@inproceedings{034f2370f8eb4804af2a50833e0a10ac,

title = "Method of solving combinatorial optimization problems with stochastic effects",

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.",

keywords = "Energy function, Higher order connections, Hysteresis neural network, Quartic form, Traveling Salesman Problems",

author = "Takahiro Sota and Yoshihiro Hayakawa and Shigeo Sato and Koji Nakajima",

year = "2011",

doi = "10.1007/978-3-642-24965-5_44",

language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 3",

pages = "389--394",

booktitle = "Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings",

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note = "18th International Conference on Neural Information Processing, ICONIP 2011 ; Conference date: 13-11-2011 Through 17-11-2011",

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Sota, T, Hayakawa, Y, Sato, S & Nakajima, K 2011, Method of solving combinatorial optimization problems with stochastic effects. in Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings. PART 3 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 7064 LNCS, pp. 389-394, 18th International Conference on Neural Information Processing, ICONIP 2011, Shanghai, China, 11/11/13. https://doi.org/10.1007/978-3-642-24965-5_44

Method of solving combinatorial optimization problems with stochastic effects. / Sota, Takahiro; Hayakawa, Yoshihiro; Sato, Shigeo et al.
Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings. PART 3. ed. 2011. p. 389-394 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7064 LNCS, No. PART 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Sota, Takahiro

AU - Hayakawa, Yoshihiro

AU - Sato, Shigeo

AU - Nakajima, Koji

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

KW - Energy function

KW - Higher order connections

KW - Hysteresis neural network

KW - Quartic form

KW - Traveling Salesman Problems

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Sota T, Hayakawa Y, Sato S, Nakajima K. Method of solving combinatorial optimization problems with stochastic effects. In Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings. PART 3 ed. 2011. p. 389-394. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). doi: 10.1007/978-3-642-24965-5_44

Method of solving combinatorial optimization problems with stochastic effects

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