Journal of Intelligent Manufacturing

, Volume 20, Issue 1, pp 91–111 | Cite as

Integration of a flat holonic form in an HLA environment

  • Fouzia Ounnar
  • Patrick Pujo
  • Lynda Mekaouche
  • Norbert Giambiasi


Managers need to create and sustain internal systems and controls to ensure that their customer focused strategies are being implemented. Companies are currently in a spiral of permanent optimization. Accordingly, many companies turn to their core activity. In this framework, one notices the development of the concept of “industrial partnership”. In this context and to control the customer–supplier relationships (CSR), we proposed a self-organized control model in which all partner entities (customers/suppliers) negotiate to guarantee good quality connections between customers and suppliers. This means meeting customer expectations as closely as possible and respecting supplier capacities. In this proposal, self-organized control is characterized more precisely by an organizational architecture of the flat holonic form type. This flat holonic form is based on the concept of autonomous control entity (ACE). The holonic architecture, the behaviour of an ACE, the interaction mechanisms between ACEs and the self-evaluation supplier process are presented, and then the modelling of ACEs using discrete event system specification (DEVS) is described. An implementation of the simulation of such a system was done via a distributed simulation environment high level architecture (HLA). A case study illustrating the proposed approach is presented.


Self-organized control Discrete EVent system Specification High level architecture Flat holonic form Autonomous control entity Analytic hierarchy process 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Afsarmanesh, H., & Camarinha-Matos, L. M. (2005). A framework for management of victual organization breeding environments. In Proceedings of PRO-VE’05—Collaborative Networks and their Breeding Environments, Springer, 26–28 September 2005, Valencia, Spain.Google Scholar
  2. Alcouffe C. and Corrégé N. (1999). L’évaluation des performances dans les organisations en réseaux de sous-traitants: l’exemple de l’Aérospatiale Matra Airbus. Revue Française de Gestion Industrielle 18(4): 27–42 Google Scholar
  3. Bongaerts L., Monostori L., McFarlane D. and Kadar B. (2000). Hierarchy in distributed shop floor control. Computer in Industry 43: 123–137 CrossRefGoogle Scholar
  4. Brandolese A., Brun A. and Portioli-Staudacher A. (2000). A Multi-agent approach for the capacity allocation problem. International Journal of Production Economics 66: 269–285 CrossRefGoogle Scholar
  5. Brito, C. M., & Roseira, C. (2003). A model for the understanding of supply chain networks. In 19th Annual Industrial Marketing and Purchasing Conference, University of Lugano, 4th–6th September, Lugano, Switzerland.Google Scholar
  6. Camarinha-Matos L.M. and Afsarmanesh H. (2004). Collaborative Networked Organizations—a research agenda for emerging business models. Springer, New York Google Scholar
  7. Camarinha-Matos L.M. and Afsarmanesh H. (2005). Collaborative networks: A new scientific discipline. Journal of Intelligent Manufacturing 16(4–5): 439–452 CrossRefGoogle Scholar
  8. Camarinha-Matos, L. M., & Afsarmanesh, H. (2006a). Towards a reference model for collaborative networked organizations. In Proceedings of BASYS’06 (Springer), 4–6 Sept 06, Niagara Falls, Canada.Google Scholar
  9. Camarinha-Matos L.M. and Afsarmanesh H. (2006). Results assessment and impact creation in collaborative research—an example from the ECOLEAD project. Technovation 27(1–2): 65–77 Google Scholar
  10. Chen, H., Amodeo, L., & Chu, F. (2001). Modelling and performance evaluation of supply chain with Batch deterministic and stochastic petri nets. In 13th European Simulation Symposium (pp. 415–419), October 2001, Marseille.Google Scholar
  11. Cousins P.D. and Spekman R. (2003). Strategic supply and the management of inter- and intra-organizational relation ships. Journal of Purchasing and Supply Management 9(1): 19–29 CrossRefGoogle Scholar
  12. Deen, S. M. (2003). Agent-Based manufacturing—advances in the holonic approach. Springer-Verlag Ed, ISBN 3-540-44069-0.Google Scholar
  13. Despontin E., Briand C. and Esquirol P. (2005). Aide à la décision pour une coopération inter-entreprises: une approche par contraintes. Journal Européen des Systèmes Automatisés 39(7): 799–818 CrossRefGoogle Scholar
  14. Dong, J., Zhang, D., & Nagurney, A. (2002). Supply chain networks with multicriteria decision-makers. Transportation and Traffic Theory in the 21st Century, M.A.P, 179–196.Google Scholar
  15. Faems D., Van Looy B. and Debackere K. (2005). Interorganizational collaboration and innovation: Towards a portfolio approach. Journal of Product Innovation Management 22(3): 238–250 CrossRefGoogle Scholar
  16. Harker, P. T. (1989). The art and science of decision making: The analytic hierarchy process: Applications and studies. Springer-Verlag Ed.Google Scholar
  17. Harri, I. K. (2002). Accounting in customer–supplier relationships: Developing cost management in customer–supplier relationships: Three case studies. In Proceedings of the 3rd Conference on New Directions in Management Accounting: Innovations in Practice and Research (Vol. 2, pp. 699–716), December 2002, Brussels, Belgium.Google Scholar
  18. Holmlund-Rytkönen M. and Strandvik T. (2005). Stress in business relationships. The Journal of Business and Industrial Marketing 20(1): 12–22 CrossRefGoogle Scholar
  19. IEEE P1516. Draft standard for modeling and simulation (M&S) high level architecture (HLA)—framework and rules.Google Scholar
  20. IEEE P1516.1. Draft standard for modeling and simulation (M&S) high level architecture (HLA)—federate interface specification.Google Scholar
  21. IEEE P1516.2. Draft standard for modeling and simulation (M&S) high level architecture (HLA)—object model template (OMT) specification.Google Scholar
  22. Lauras M., Parrod N. and Telle O. (2003). Proposition de référentiel pour la notion d’entente industrielle: trois approches dans le domaine de la gestion des chaînes logistiques. Revue Française de Gestion Industrielle 22(4): 5–30 Google Scholar
  23. Mekaouche, L., Ounnar, F., Pujo, P., & Giambiasi, N. (2005a). Customers–suppliers relationship self organized control modeling using DEVS formalism. In IMACS’05—the 17th IMACS World Congress on Scientific Computation, Applied Mathematics and Simulation, Paris, France.Google Scholar
  24. Mekaouche, L., Ounnar, F., Pujo, P., & Giambiasi, N. (2005b). Self evaluation of company’s performance in partnership network. In IEEE International Engineering Management Conference (IEEE–IEMC), St. John’s, Newfoundland, Canada.Google Scholar
  25. Nesheim T. (2001). Externalization of the core: Antecedents of collaborative relationships with suppliers. European Journal of Purchasing & Supply Management 7: 217–225 CrossRefGoogle Scholar
  26. Nishi T., Konishi M. and Hasebe S. (2005). An autonomous decentralized supply chain planning dor multi-stage production processes. Journal of Intelligent Manufacturing 16(3): 259–275 CrossRefGoogle Scholar
  27. Ounnar F. and Ladet P. (2004). Consideration of machine breakdown in the control of flexible production systems. International Journal of Computer Integrated Manufacturing System 17(1): 69–82 CrossRefGoogle Scholar
  28. Ounnar F. and Pujo P. (2001). Décentralisation des mécanismes de pilotage de la relation donneurs d’ordres/fournisseurs. Actes du 4e congrès International de Génie Industriel 2: 1175–1185, FranceGoogle Scholar
  29. Ounnar F. and Pujo P. (2005). Supplier evaluation process within a self-organized logistical network. International Journal of Logistics Management 16(1): 159–172 CrossRefGoogle Scholar
  30. Ounnar, F., Pujo, P., Mekaouche, L., & Giambiasi, N. (2004). Decentralized self organized control of a partnership network in an intelligent supply chain. In IMS International Forum 2004: Global Challenges in Manufacturing, Italy.Google Scholar
  31. Ounnar F., Pujo P., Mekaouche L. and Giambiasi N. (2007). Customer–supplier relation-ship management in an intelligent supply chain network. Production Planning & Control 18(5): 377–387 CrossRefGoogle Scholar
  32. Pradosh N., Sandhya G.D. and Mrinalini N. (2005). Supply chain as knowledge management. International Journal of Logistic Systems and Management 1(2/3): 267–278 CrossRefGoogle Scholar
  33. Saaty T. (1996). Multicriteria decision making: The analytic hierarchy process. RWS Publications, Pittsburgh Google Scholar
  34. Smart A. and Harrison A. (2003). Online reverse auctions and their role in buyer–supplier relationships. Journal of Purchasing & Supply Management 9: 257–268 CrossRefGoogle Scholar
  35. Smith R. (1980). The contract net protocol. High-level communication and control in a distributed problem solver. IEEE Transactions on Computers 29(12): 1104–1113 CrossRefGoogle Scholar
  36. Telle O., Thierry C. and Bel G. (2004). Aide à la coopération au sein d’une relation Donneur d’Ordres/Fournisseur dans le secteur aéronautique: Un outil de simulation. Journal Européen des Systèmes Automatisés 38(1–2): 7–36 CrossRefGoogle Scholar
  37. Toole T. and Donaldson B. (2002). Relationship performance dimensions of buyer–supplier exchanges. European Journal of Purchasing & Supply Management 8: 197–207 CrossRefGoogle Scholar
  38. Van Brussel H., Wyns J., Valckenears P., Bongaerts L. and Peeters P. (1998). Reference architecture for holonic manufacturing systems: PROSA. Computers in Industry 37(3): 255–276 CrossRefGoogle Scholar
  39. Vargas L.G. (1990). An overview of the analytic hierarchy process and its applications. European Journal of Operational Research 48(1): 2–8 CrossRefGoogle Scholar
  40. Villa A. (1998). Organizing a ‘network of entreprises’: An object-oriented design methodology. Computer Integrated Manufacturing Systems 11(4): 331–336 CrossRefGoogle Scholar
  41. Wedley W.C. (1990). Combining qualitative and quantitative factors—an analytic hierarchy approach. Socio Economic Planning Sciences 24(1): 57–64 CrossRefGoogle Scholar
  42. Zeigler B. (1976). Theory of modelling and simulation. Wiley, New York Google Scholar
  43. Zeigler B., Praehofer H. and Kim T. (2000). Theory of modeling and simulation (2nd ed.). Academic Press, New York Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Fouzia Ounnar
    • 1
  • Patrick Pujo
    • 1
  • Lynda Mekaouche
    • 1
  • Norbert Giambiasi
    • 1
  1. 1.Laboratoire des Sciences de l’Information et des Systèmes (LSIS), UMR – CNRS 6168Université Paul CézanneMarseille Cedex 20France

Personalised recommendations