A Connectionist Approach for Solving Large ConstraintSatisfaction Problems

  • Authors:
  • A. Likas;G. Papageorgiou;A. Stafylopatis

  • Affiliations:
  • Department of Electrical and Computer Engineering, National Technical University of Athens, 157 73 Zografou, Greece. E-mail: arly@cs.ece.ntua.gr, gpap@cs.ece.ntua.gr, andreas&commat ...;Department of Electrical and Computer Engineering, National Technical University of Athens, 157 73 Zografou, Greece. E-mail: arly@cs.ece.ntua.gr, gpap@cs.ece.ntua.gr, andreas&commat ...;Department of Electrical and Computer Engineering, National Technical University of Athens, 157 73 Zografou, Greece. E-mail: arly@cs.ece.ntua.gr, gpap@cs.ece.ntua.gr, andreas&commat ...

  • Venue:
  • Applied Intelligence
  • Year:
  • 1997

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Abstract

An efficient neural network technique is presented for the solutionof binary constraint satisfaction problems. The method is based onthe application of a double-update technique to the operation of thediscrete Hopfield-type neural network that can be constructed for thesolution of such problems. This operation scheme ensures that thenetwork moves only between consistent states, such that each problemvariable is assigned exactly one value, and leads to a fast andefficient search of the problem state space. Extensions of theproposed method are considered in order to include severaloptimisation criteria in the search. Experimental results concerningmany real-size instances of the Radio Links Frequency AssignmentProblem demonstrate very good performance.