Solving the Weighted Constraint Satisfaction Problems Via the Neural Network Approach

dc.contributor.author	Ettaouil, Mohamed
dc.contributor.author	Haddouch, Khalid
dc.contributor.author	Elmoutaoukil, Karim
dc.date	2016-09
dc.date.accessioned	2021-07-14T11:34:23Z
dc.date.available	2021-07-14T11:34:23Z
dc.identifier.issn	1989-1660
dc.identifier.uri	https://reunir.unir.net/handle/123456789/11611
dc.description.abstract	A wide variety of real world optimization problems can be modelled as Weighted Constraint Satisfaction Problems (WCSPs). In this paper, we model this problem in terms of in original 0-1 quadratic programming subject to leaner constraints. View it performance, we use the continuous Hopfield network to solve the obtained model basing on original energy function. To validate our model, we solve several instance of benchmarking WCSP. In this regard, our approach recognizes the optimal solution of the said instances.	es_ES
dc.language.iso	eng	es_ES
dc.publisher	International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)	es_ES
dc.relation.ispartofseries	;vol. 4, nº 1
dc.relation.uri	https://ijimai.org/journal/bibcite/reference/2529	es_ES
dc.rights	openAccess	es_ES
dc.subject	energy	es_ES
dc.subject	programming	es_ES
dc.subject	neural network	es_ES
dc.subject	hopfield	es_ES
dc.subject	IJIMAI	es_ES
dc.title	Solving the Weighted Constraint Satisfaction Problems Via the Neural Network Approach	es_ES
dc.type	article	es_ES
reunir.tag	~IJIMAI	es_ES
dc.identifier.doi	http://doi.org/10.9781/ijimai.2016.4111

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