2 research outputs found
Solving the Weighted Constraint Satisfaction Problems Via the Neural Network Approach
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