A maximum neural network for the max cut problem

Kuo Chun Lee, Yoshiyasu Takefuji, Nobuo Funabiki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

The max cut problem, one of the NP-complete problems, was chosen to test the capability of an artificial neural network. The algorithm based on the maximum neural network was tested by 1000 randomly generated examples, including up to 300 vertex problems. The simulation result shows that the proposed parallel algorithm using the maximum neural network generates better solutions than Hsu's algorithm within one hundred iteration steps, regardless of the problem size.

Original languageEnglish
Title of host publicationProceedings. IJCNN-91-Seattle
Subtitle of host publicationInternational Joint Conference on Neural Networks
Editors Anon
PublisherPubl by IEEE
Pages379-384
Number of pages6
ISBN (Print)0780301641
Publication statusPublished - Dec 1 1991
EventInternational Joint Conference on Neural Networks - IJCNN-91-Seattle - Seattle, WA, USA
Duration: Jul 8 1991Jul 12 1991

Publication series

NameProceedings. IJCNN-91-Seattle: International Joint Conference on Neural Networks

Other

OtherInternational Joint Conference on Neural Networks - IJCNN-91-Seattle
CitySeattle, WA, USA
Period7/8/917/12/91

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Lee, K. C., Takefuji, Y., & Funabiki, N. (1991). A maximum neural network for the max cut problem. In Anon (Ed.), Proceedings. IJCNN-91-Seattle: International Joint Conference on Neural Networks (pp. 379-384). (Proceedings. IJCNN-91-Seattle: International Joint Conference on Neural Networks). Publ by IEEE.