Bouhouch, Adil and Loqman, Chakir and Bennis, Hamid and El Qadi, Abderrahim (2019) A comparative study of CHN-MNC, GA and PSO for solving constraints satisfaction problems. In: ICCWCS 2019, 24-25 April 2019, Kenitra, Morocco.
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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
Item Type: | Conference or Workshop Item (Paper) |
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Uncontrolled Keywords: | csp metaheuristics ga pso min-conflict heuristic |
Subjects: | T Technology > T Technology (General) |
Depositing User: | EAI Editor IV |
Date Deposited: | 15 Oct 2021 07:16 |
Last Modified: | 15 Oct 2021 07:16 |
URI: | https://eprints.eudl.eu/id/eprint/7647 |