Research Article
A comparative study of CHN-MNC, GA and PSO for solving constraints satisfaction problems
@INPROCEEDINGS{10.4108/eai.24-4-2019.2284084, author={Adil Bouhouch and Chakir Loqman and Hamid Bennis and Abderrahim El Qadi}, title={A comparative study of CHN-MNC, GA and PSO for solving constraints satisfaction problems}, proceedings={Proceedings of the Third International Conference on Computing and Wireless Communication Systems, ICCWCS 2019, April 24-25, 2019, Faculty of Sciences, Ibn Tofa\~{n}l University -K\^{e}nitra- Morocco}, publisher={EAI}, proceedings_a={ICCWCS}, year={2019}, month={5}, keywords={csp metaheuristics ga pso min-conflict heuristic}, doi={10.4108/eai.24-4-2019.2284084} }
- Adil Bouhouch
Chakir Loqman
Hamid Bennis
Abderrahim El Qadi
Year: 2019
A comparative study of CHN-MNC, GA and PSO for solving constraints satisfaction problems
ICCWCS
EAI
DOI: 10.4108/eai.24-4-2019.2284084
Abstract
Our approach CHN-MNC, based Continuous Hopfield neural network and Min-Conflict heuristic), have proved that is more efficient than using CHN alone to solve Constraints Satisfaction Problem (CSP). In This paper we study the performance of CHN-MNC by comparing it robustness with two evolutionary algorithms. We choose a Genetic Algorithm and Swarm optimisation to performers this study. Some numerical experiments are done over a variety of problems to verify the efficiency and fast convergence of our approach. abstract needs to summarize the content of the paper
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