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
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;
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
DOI :
10.1109/IJCNN.1991.155207
