Outlining a Model of an Intelligent Decision Support System Based on Multi Agents

Authors

  • N. Benmoussa Signals, Distributed Systems and Artificial Intelligence Laboratory, ENSET Mohammedia, University of Hassan II, Mohammedia, Morocco
  • M. Fakhouri Amr Signals, Distributed Systems and Artificial Intelligence Laboratory (SSDIA), ENSET, University Hassan II, Mohammedia, Morocco
  • S. Ahriz Signals, Distributed Systems and Artificial Intelligence Laboratory, ENSET Mohammedia, University of Hassan II, Mohammedia, Morocco
  • K. Mansouri Signals, Distributed Systems and Artificial Intelligence Laboratory, ENSET Mohammedia, University of Hassan II, Mohammedia, Morocco
  • E. Illoussamen Signals, Distributed Systems and Artificial Intelligence Laboratory, ENSET Mohammedia, University of Hassan II, Mohammedia, Morocco

Abstract

Performance optimization has become a necessity for the survival of enterprises as emerging technologies continue to impact them. To achieve this goal, decision making, a complex process which depends on big data and human issues, must be effective. As enterprises are being subjected to a multi-faceted pressure, they must ensure the optimization of their performance. This article investigates an intelligent decision support system (IDSS) based on multi agent systems (MAS). Our contribution consists in developing an intelligent model with an IDSS MAS approach that can detect and evaluate changes in both the external environment and the enterprise itself. This model is an adequate management tool for optimal and sustainable performance and offers real-time analytical, prospecting and optimization methods.

Keywords:

decision making, performance, value creation, MAS, IDSS

Downloads

Download data is not yet available.

References

H. Mintzberg, D. Raisinghani, A. Theoret, “The structure of “Unstructured” decision processes”, Administrative Science Quarterly,Vol. 21, No. 2, pp. 246-275, 1976 DOI: https://doi.org/10.2307/2392045

H. I. Anssof, Corporate Strategy, McGraw Hill, New York, 1965

B. Roy, D. Bouyssou, “Aide multicritère à la décision- Méthodes et cas”, Economica, Paris, 1993 (in French)

T. Quach, K. Oanh, “Une perspective de recherche sur la performance dans l'organisation”, 23e Colloque annuel du Conseil Canadien des PME et de l'entrepreneuriat, Trois-Rivières, 2006 (in Frenc)

I. Missaoui, “Valeur et performance des systèmes d'information”, Cahier de charge N°5, CIGREF - Université Paris-Sud 11, Paris, 2009 (in French)

M. Bouamama, “Nouveaux défis du système de mesure de la performance : cas des tableaux de bord”, Gestion et management. Université de Bordeaux, 2015 (in French)

F. Nwamen, “Impact des technologies de l’information et de la communication sur la performance commerciale des entreprises”, Revue des sciences de gestion, No. 218, pp. 111-126, 2006(in French) DOI: https://doi.org/10.3917/rsg.218.0111

P. Amans, S. Rascol-Boutard, “La performance entre construit social et indicateur simplifié”, Finance Contrôle et Stratégie, Vol. 11, No. 3, pp. 45-63, 2008 (in French)

M. Gervais, Contrôle de gestion, Economica, 2005 (in French)

A. Bourguignon, “Peut-on définir la performance?”, Revue Française de Comptabilité, No. 269, pp. 61-66, 1995 (in French)

M. S. Scott-Morton, Management Decision System, 1971

P. G. W. Keen, M. Scott-Morton, “Decision Support Systems : an oragnizational perspective”, AddisonWesley Publighing, 1978

R. H. Spargue , E Carlson, Building Effective Support Systems, Prentice-Hall, Inc, Englewood Cliffs, 1982

P. N. Finlay, Introducing Decision Support Systems, NCC Blackwell, 19889

A. R. Probst, “Les Systèmes d’Aide à la Décision : rôle, structure et évolution”, Gestion-Revue In ternationale de Gestion, Vol. 9, No. 4, pp. 13-19, 1984

E. Turban, Decision Support and Expert Systems: Managerial perspectives, Macmillan Library Reference, 1990

S. Shamshirband, N. Badrul Anuar, M. L. Mat Kiah, A. Patel, “An appraisal and design of a multi-agent system based cooperative wireless intrusion detection computational intelligence technique”, Engineering Applications of Artificial Intelligence, Vol. 26, No. 9, pp. 2105-2127, 2013 DOI: https://doi.org/10.1016/j.engappai.2013.04.010

S. Shamshirband, A. Patel, N. Badrul Anuar, M. L. Mat Kiah, A. Abraham, “Cooperative game theoretic approach using fuzzy Q-learning for detecting and preventing intrusions in wireless sensor networks”, Engineering Applications of Artificial Intelligence, Vol. 32. pages 228-241, 2014 DOI: https://doi.org/10.1016/j.engappai.2014.02.001

A. Jahangirzadeh, S. Shamshirband, S. Aghabozorgi, S. Akib, H. Basser, N. Badrul Anuar, M. L. Mat Kiah, “A cooperative expert based support vector regression (Co-ESVR) system to determine collar dimensions around bridge pier”, Neurocomputing, Vol. 140, pp. 172-184, 2014 DOI: https://doi.org/10.1016/j.neucom.2014.03.024

S. Shamshirband, S. Kalantari, Z. Bakhshandeh, “Designing a smart multi-agent system based on fuzzy logic to improve the gas consumption pattern”, Scientific Research and Essays, Vol. 5, No. 6, pp. 592-605, 2010

J. Ferber, Les Systèmes Multi Agents vers une Intelligence Collective, InterEditions, Paris, 1995 (in French)

B. Nachet, A. Adla, “An agent-based distributed collaborative decision support system”, Intelligent Decision Technologies - Various forms of intelligence, Vol. 8, No. 1, pp. 15-34, 2014 DOI: https://doi.org/10.3233/IDT-130174

N. Bakhta, Modèle multi-agents pour la conception d’un SIAD collective, PhD Thesis, Université d’Oran, 2014, (in French)

G. Weiss, Multiagent Systems, MIT Press, 2013

S. H. Chan, Q. Song, S. Sarker, R. David Plumleed, “Decision support system (DSS) use and decision performance: DSS motivation and its antecedents”, Information & Management, Vol. 54, No. 7, pp. 934-947, 2017 DOI: https://doi.org/10.1016/j.im.2017.01.006

Downloads

How to Cite

[1]
Benmoussa, N., Fakhouri Amr, M., Ahriz, S., Mansouri, K. and Illoussamen, E. 2018. Outlining a Model of an Intelligent Decision Support System Based on Multi Agents. Engineering, Technology & Applied Science Research. 8, 3 (Jun. 2018), 2937–2942. DOI:https://doi.org/10.48084/etasr.1936.

Metrics

Abstract Views: 857
PDF Downloads: 513

Metrics Information

Most read articles by the same author(s)