01149nas a2200229   4500000000100000000000100001008004100002260001200043653001100055653001600066653001900082653001300101100002100114700002000135700002300155245009000178856009900268300001000367490000600377520052200383022001400905       2016                            d  c09/201610aEnergy10aProgramming10aNeural Network10aHopfield1 aMohamed Ettaouil1 aKhalid Haddouch1 aKarim Elmoutaoukil00aSolving the Weighted Constraint Satisfaction Problems Via the Neural Network Approach  uhttp://www.ijimai.org/JOURNAL/sites/default/files/files/2016/02/ijimai20164_1_11_pdf_42425.pdf  a56-600 v43 aA 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.  a1989-1660