Special Issue: Artificial Intelligence and Pattern Recognition

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Competition Based Neural Networks for Assignment Problems

Li Tao;   

  1. Department of Computer Science Monash University; Clayton; VIC 3168; Australia;
  • Online:1991-07-10 Published:1991-07-10

Competition based neural networks have been used to solve the generalized assignment problem and the quadratic assignment problem.Both problems are very difficult and are ε approximation complete.The neural network approach has yielded highly competitive performance and good performance for the quadratic assignment problem.These neural networks are guaranteed to produce feasible solutions.

Key words: architecture transformation,graph rewriting,weakest precondition,constraint checking;



[1] S.Abe, Theories on the Hopfield Neural Networks. Int. Joint Conf. Neural Networks, Vol.1(June 1989) Washington D. C., 557-564.

[2] P.Bourret, S.Goodall and M.Samuelides, Optimal Scheduling by Competitive Activation: Application to the Satellite Antennae Scheduling Problem. Int,Joint Conf.Neural Networks, Vol. 1 (June 1989) Washington D.C., 565-572.

[3] M.Cohen and S.Grossberg, Absolute stability of global pattern formation and parallel memory storage by competitive neural networks. IEEE Trans. Systems, Man and Cybernetics., SMC-13 (Sep./Oct.1983), 815-826.

[4] L.Y.Fang, Design of Computational Neural Networks. Ph.D thesis submitted to the Flinders University of South Australia, March 1990.

[5] J.J.Hopfield, Neural networks and physical systems with emergent collective computational abilities. Proc. Natl. Acad. Sci. USA, Vol.79 (April 1982), 2553-2558. ……….
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ISSN 1000-9000(Print)

         1860-4749(Online)
CN 11-2296/TP

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