DocumentCode
276597
Title
A maximum neural network for the max cut problem
Author
Lee, Kuo Chun ; Takefuji, Yoshiyasu ; Funabiki, Nobuo
Author_Institution
Dept. of Electr. Eng. & Appl. Phys., Case Western Reserve Univ., Cleveland, OH, USA
Volume
i
fYear
1991
fDate
8-14 Jul 1991
Firstpage
379
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 (1983) within one hundred iteration steps, regardless of the problem size
Keywords
computational complexity; graph theory; neural nets; optimisation; parallel algorithms; NP-complete problems; artificial neural network; iteration steps; max cut problem; maximum neural network; parallel algorithm; vertex problems; Constraint optimization; Integrated circuit interconnections; NP-complete problem; Neural networks; Parallel algorithms; Physics; Polynomials; Routing; Testing; Wire;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-0164-1
Type
conf
DOI
10.1109/IJCNN.1991.155207
Filename
155207
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