A Connectionist Approach for Solving Large Constraint Satisfaction Problems

Likas, A; Papageorgiou, G; Stafylopatis, A

dc.contributor.author	Likas, A	en
dc.contributor.author	Papageorgiou, G	en
dc.contributor.author	Stafylopatis, A	en
dc.date.accessioned	2014-03-01T01:12:32Z
dc.date.available	2014-03-01T01:12:32Z
dc.date.issued	1997	en
dc.identifier.issn	0924-669X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/12120
dc.subject	Boltzmann machine	en
dc.subject	Constraint satisfaction	en
dc.subject	Frequency assignment problem	en
dc.subject	Hopfield network	en
dc.subject	Neural network architectures	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.other	Constraint theory	en
dc.subject.other	Optimization	en
dc.subject.other	Problem solving	en
dc.subject.other	State space methods	en
dc.subject.other	Boltzmann machine	en
dc.subject.other	Hopfield type neural network	en
dc.subject.other	Radio links frequency assignment problems	en
dc.subject.other	Neural networks	en
dc.title	A Connectionist Approach for Solving Large Constraint Satisfaction Problems	en
heal.type	journalArticle	en
heal.identifier.primary	10.1023/A:1008272531960	en
heal.identifier.secondary	http://dx.doi.org/10.1023/A:1008272531960	en
heal.language	English	en
heal.publicationDate	1997	en
heal.abstract	An efficient neural network technique is presented for the solution of binary constraint satisfaction problems. The method is based on the application of a double-update technique to the operation of the discrete Hopfield-type neural network that can be constructed for the solution of such problems. This operation scheme ensures that the network moves only between consistent states, such that each problem variable is assigned exactly one value, and leads to a fast and efficient search of the problem state space. Extensions of the proposed method are considered in order to include several optimisation criteria in the search. Experimental results concerning many real-size instances of the Radio Links Frequency Assignment Problem demonstrate very good performance.	en
heal.publisher	KLUWER ACADEMIC PUBL	en
heal.journalName	Applied Intelligence	en
dc.identifier.doi	10.1023/A:1008272531960	en
dc.identifier.isi	ISI:A1997XK44200003	en
dc.identifier.volume	7	en
dc.identifier.issue	3	en
dc.identifier.spage	215	en
dc.identifier.epage	225	en