Solving the Weighted Constraint Satisfaction Problems Via the Neural Network Approach

Author
Keywords
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.
Year of Publication
2016
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
4
Issue
Special Issue on Artificial Intelligence Underpinning
Number
1
Number of Pages
56-60
Date Published
09/2016
ISSN Number
1989-1660
Citation Key
URL
http://www.ijimai.org/JOURNAL/sites/default/files/files/2016/02/ijimai20164_1_11_pdf_42425.pdf
DOI
10.9781/ijimai.2016.4111
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