A comparative study of CHN-MNC, GA and PSO for solving constraints satisfaction problems

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.

[thumbnail of PDF]
Preview
Text (PDF)
eai.24-4-2019.2284084.pdf - Published Version

Download (536kB) | Preview

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)
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

Actions (login required)

View Item
View Item