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

Adil Bouhouch; Chakir Loqman; Hamid Bennis; Abderrahim El Qadi

Proceedings of the Third International Conference on Computing and Wireless Communication Systems, ICCWCS 2019, April 24-25, 2019, Faculty of Sciences, Ibn Tofaïl University -Kénitra- Morocco

Research Article

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

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@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

Adil Bouhouch¹^,*, Chakir Loqman², Hamid Bennis³, Abderrahim El Qadi⁴

1: epartment of Computer Science, Faculty Sciences, Chouaib Doukkali University, El Jadida, Morocco
2: Department of informatics, Faculty Sciences, Dhar Mehraz, Sidi Mohammed Ben Abdellah Fez, Morocco
3: Team TIM, High School of Technology - Moulay Ismail University, Meknes, Morocco
4: High School of Technology - Mohammed V University of Rabat Morocco

*Contact email: bouhouch.adil@gmail.com

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

Keywords: csp metaheuristics ga pso min-conflict heuristic

Published: 2019-05-23
Publisher: EAI

: http://dx.doi.org/10.4108/eai.24-4-2019.2284084