Skip to main content

MBSE, PLM, MIP and Robust Optimization for System of Systems Management, Application to SCCOA French Air Defense Program

  • Conference paper
  • First Online:
Book cover Complex Systems Design & Management (CSDM 2016)

Abstract

To examine the Project Management aspects of the French Air Defense Program SCCOA, a Model-Based System Engineering approach using the NATO Architecture Framework (NAF) is appropriate to ensure the System of Systems consistency. Two limitations of the NAF are addressed: incorporating temporality and incorporating decision support tools. The first issue is resolved by coupling NAF with an Access calendar database. The second is solved using Prolog, a Constraint Programming tool, and Cplex, a Mathematical Programming tool. The resulting tool stack allows to schedule deployment integrating Robust Optimization techniques.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Estefan, J.A., et al.: Survey of model-based systems engineering (MBSE) methodologies. Incose MBSE Focus Group 25(8) (2007)

    Google Scholar 

  2. SCCOA: http://www.defense.gouv.fr/dga/equipement/information-communication-espace/le-systeme-de-commandement-et-de-conduite-des-operations-aerospatiales-sccoa

  3. Luzeaux, D.: SoS and Large-Scale Complex Systems Architecting. In: Complex Systems Design and Management, pp. 39–49. Springer International Publishing (2014)

    Google Scholar 

  4. Maier, M.W.: Architecting principles for systems-of-systems. In: INCOSE International Symposium, vol. 6, pp. 565–573. Wiley Online Library (1996)

    Google Scholar 

  5. Charette, R.N.: Why software fails [software failure]. IEEE Spectr. 42(9), 42–49 (2005)

    Article  Google Scholar 

  6. Luzeaux, D., Ruault, J.R., Wippler, J.L.: Complex Systems and Systems of Systems Engineering. Wiley (2013)

    Google Scholar 

  7. Simo, F.K., Lenne, D., Ernadote, D.: Mastering SoS complexity through a methodical tailoring of modeling: benefits and new issues. In: Systems Conference (SysCon), 2015 9th Annual IEEE International, pp. 516–520. IEEE (2015)

    Google Scholar 

  8. Ernadote, D.: An automated objective-driven approach to drive the usage of the naf framework. In: NATO Science and Technology Organization (STO) Symposium (2013)

    Google Scholar 

  9. Ernadote, D.: An ontology mindset for system engineering. In: 2015 IEEE International Symposium on Systems Engineering (ISSE), pp. 454–460. IEEE (2015)

    Google Scholar 

  10. Moones, E., et al.: Towards an Extended Interoperability Systemic Approach for Dynamic Manufacturing Networks: Role and Assessment of PLM Standards. In: CSD and M (2015)

    Google Scholar 

  11. Doufene, A., Chalé-Góngora, H.G., Krob, D.: Complex systems architecture framework: Extension to multi-objective optimization. In: CSD and M 2013, pp. 105–123. Springer (2013)

    Google Scholar 

  12. Helle, P., Masin, M., Greenberg, L.: Approximate reliability algebra for architecture optimization. In: Computer Safety, Reliability, and Security, pp. 279–290. Springer (2012)

    Google Scholar 

  13. Kim, I.Y., De Weck, O.: Adaptive weighted-sum method for bi-objective optimization: Pareto front generation. Struct. Multidisc. Optim. 29(2), 149–158 (2005)

    Article  Google Scholar 

  14. Smaling, R., Weck, O.D.: Assessing risks and opportunities of technology infusion in system design. Syst. Eng. 10(1), 1–25 (2007)

    Article  Google Scholar 

  15. Chen, M., Hammami, O.: A system engineering conception of multi-objective optimization for multi-physics system. In: Multiphysics Modelling and Simulation for Systems Design and Monitoring, pp. 299–306. Springer (2015)

    Google Scholar 

  16. Fleming, P.J., Purshouse, R.C., Lygoe, R.J.: Many-objective optimization: an engineering design perspective. In: Evolutionary Multi-criterion Optimization, pp. 14–32. Springer (2005)

    Google Scholar 

  17. Talbi, E.G.: Metaheuristics: From Design to Implementation, vol. 74. Wiley (2009)

    Google Scholar 

  18. Benoist, T., Estellon, B., Gardi, F., Megel, R., Nouioua, K.: Localsolver 1. x: a black-box local-search solver for 0-1 programming. 4OR 9(3), 299–316 (2011)

    Google Scholar 

  19. Condat, H., Strobel, C., Hein, A.: Model-based automatic generation and selection of safe architectures. INCOSE (2012)

    Google Scholar 

  20. Sagaspe, L.: Allocation sûre dans les systmes aéronautiques: Modélisation, vérification et génération. Ph.D. thesis, Université Bordeaux 1 (2008)

    Google Scholar 

  21. Vielma, J.P.: Mixed integer linear programming formulation techniques. SIAM Rev. 57(1), 3–57 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  22. Marinelli, F., De Weck, O., Krob, D., Liberti, L., Mucherino, A.: A general framework for combined module-and scale-based product platform design. In: Second Internal Symposium on Engineering Systems MIT. Cambridge, Mass (2009)

    Google Scholar 

  23. Dupin, N.: Modélisation et résolution de grands problèmes stochastiques combinatoires: application à la gestion de production d’électricité. Ph.D. thesis, Lille 1 (2015)

    Google Scholar 

  24. Dupin, N., Talbi, E.G.: Dual matheuristic and new dual bounds for the EURO/ROADEF 2010 Challenge. IRIDIA Technical Report series (ISSN 1781-3794) (2016)

    Google Scholar 

  25. Dupin, N., Talbi, E.G.: Matheuristic for the discrete unit commitment problem with min-stop ramping constraints. IRIDIA Technical Report series (ISSN 1781-3794) (2016)

    Google Scholar 

  26. Bertsimas, D., Sim, M.: The price of robustness. Oper. Res. 52(1), 35–53 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  27. Wielemaker, J.: SWI-Prolog 2.7-Reference Manual (1996)

    Google Scholar 

  28. ILOG, I.: Cplex optimizer 12.6. 0 (2014)

    Google Scholar 

  29. Schulz, J.: Hybrid solving techniques for project scheduling problems. Ph.D. Thesis (2013)

    Google Scholar 

  30. Dupin, N.: Tighter MIP formulations for the discretized unit commitment problem with min-stop ramping constraints. To appear in EURO Journal of Computational Optimization

    Google Scholar 

  31. Herroelen, W., Leus, R.: Robust and reactive project scheduling: a review and classification of procedures. Int. J. Prod. Res. 42(8), 1599–1620 (2004)

    Article  Google Scholar 

  32. Remli, N.: Robustesse en programmation linéaire. Ph.D. thesis (2011)

    Google Scholar 

  33. Minoux, M.: Duality, Robustness, and 2-stage robust LP decision models. Application to Robust PERT Scheduling (2007)

    Google Scholar 

  34. Fischetti, M., et al.: Light robustness. Lect. Notes Comput. Sci. 5868, 61–84 (2009)

    Article  MATH  Google Scholar 

  35. OSLC: core specification version 2.0. Open Services for Lifecycle Collaboration (2010)

    Google Scholar 

  36. Soyster, A.: Convex programming with set-inclusive constraints and applications to inexact linear programming. Oper. Res. 21, 1154–1157 (1973)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

This paper was written thanks to a team work, the authors are grateful to the stakeholders of System Engineering for SCCOA. Special thanks to Jean Reix and Jérôme Lemaire (SCCOA program directors), Lionel Roz (MOSS, director of the System Engineering service), Jean-François Dumas and Sara Sellos (SCCOA system architects). We also thank Lucas Hassan for his participation to code MIP models.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Thomas Peugeot or Nicolas Dupin .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Peugeot, T., Dupin, N., Sembely, MJ., Dubecq, C. (2017). MBSE, PLM, MIP and Robust Optimization for System of Systems Management, Application to SCCOA French Air Defense Program. In: Fanmuy, G., Goubault, E., Krob, D., Stephan, F. (eds) Complex Systems Design & Management. CSDM 2016. Springer, Cham. https://doi.org/10.1007/978-3-319-49103-5_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-49103-5_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49102-8

  • Online ISBN: 978-3-319-49103-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics