Neural Network and Local Search to Solve Binary CSP - Adil Bouhouch; Hamid Bennis; Chakir Loqman; Abderrahim El Qadi (Institute of Advanced Engineering and Science, 2018)
Continuous Hopfield neural Network (CHN) is one of the effective approaches to solve Constrain Satisfaction Problems (CSPs). However, the main problem with CHN is that it can reach stabilisation with outputs in real values, which means an inconsistent solution or an incomplete assignment of CSP variables. In this paper, we propose a new hybrid approach combining CHN and min-conflict heuristic to mitigate these problems. The obtained results show an improvement in terms of solution quality, either our approach achieves feasible soluion with a high rate of convergence, furthermore, this approach can also enhance theperformance more than conventional CHN in some cases, particularly, when the network crashes.