Sequences of Discrete Hopfield’s Networks for the Maximum Clique Problem

  • G. Grossi
Conference paper

DOI: 10.1007/978-1-4471-1520-5_8

Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)
Cite this paper as:
Grossi G. (1998) Sequences of Discrete Hopfield’s Networks for the Maximum Clique Problem. In: Marinaro M., Tagliaferri R. (eds) Neural Nets WIRN VIETRI-97. Perspectives in Neural Computing. Springer, London

Abstract

We propose here a neural approximation technique for the Maximum Clique problem. The core of the method consists of a sequence of Hopfield’s networks that, in polynomial time, converge to a state representing a clique for a given graph. Some experiments made on the DIMACS benchmark show that the approximated solutions found are promising. Finally, the possibility to extend this technique to other NP-hard problems and to implement it onto neural hardware are discussed.

Keywords

Maximum Clique problem constrained optimization Hopfield’s networks 

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Copyright information

© Springer-Verlag London Limited 1998

Authors and Affiliations

  • G. Grossi
    • 1
  1. 1.Dipartimento di Scienze dell’InformazioneUniversità degli Studi di MilanoMilanoItaly

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