Abstract
Model-Based Systems Engineering techniques used with decriptive metamodel such as NAF, SysML or UML often fails to provide quick analyses of huge problem spaces. This is generally compensated by Operations Research technique supporting the resolution of constraint-based problems. This paper shows how both perspectives can be combined in a smooth continuous bridge filling the gap between the two universes whilst hiding the operations researchs complexity for the modelers and automating the exploration of a very huge problem space for the finding of optimized solutions.
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Benoist, T., Estellon, B., Gardi, F., Megel, R., Nouioua, K.: Localsolver 1. x: a black-box local-search solver for 0-1 programming. 4OR Q. J. Oper. Res. 9(3), 299–316 (2011)
BKCASE. Sebok, guide to the systems engineering body of knowledge. http://sebokwiki.org
Czarnecki, K., Grünbacher, P., Rabiser, R., Schmid, K., Wąsowski, A.: Cool features and toughdecisions: a comparison of variability modeling approaches. In: Proceedings of the Sixth International Workshop on Variability Modeling of Software-Intensive Systems, pp. 173–182. ACM (2012)
Dumitrescu, C.: CO-OVM: a practical approach to systems engineering variability modeling. Université Panthéon-Sorbonne - Paris I, Theses (2014)
Dupin, N.: Modélisation et résolution de grands problèmes stochastiques combinatoires. Ph.D. thesis, Université Lille 1, Laboratoire Cristal (2015)
Ernadote, D.: An ontology mindset for system engineering. In: 2015 1st IEEE International Symposium on Systems Engineering (ISSE), pp. 454–460. IEEE (2015)
Ernadote, D.: Ontology reconciliation for system engineering. In: 2016 IEEE International Symposium on Systems Engineering (ISSE), pp. 1–8. IEEE (2016)
Estellon, B., Gardi, F., Nouioua, K.: Two local search approaches for solving real-life car sequencing problems. Eur. J. Oper. Res. 191(3), 928–944 (2008)
Hammami, O.: Multiobjective optimization of collaborative process for modeling and simulation-\(<\) q, r, t. In: 2015 IEEE International Symposium on Systems Engineering (ISSE), pp. 446–453. IEEE (2015)
Hammami, O., Houllier, M.: Rationalizing approaches to multi-objective optimization in systems architecture design. In: 2014 8th Annual IEEE Systems Conference (SysCon), pp. 407–410. IEEE (2014)
Haugen, Ø., Wasowski, A., Czarnecki, K.: CVL: common variability language. SPLC 2, 266–267 (2012)
INCOSE: INCOSE System Engineering Handbook, 4 edn. (2015)
InfoGrid. What are the differences between a vocabulary, a taxonomy, a thesaurus, an ontology, and a meta-model? http://infogrid.org/trac/wiki/Reference/PidcockArticle
Innovation24. Lsp reference manual. https://www.localsolver.com/documentation/lspreference/index.html
ISO: ISO/IEC 15288:2008, Systems and software engineering–System life cycle processes (2008)
Milewski, B.: Category theory for programmers (2014)
Morkevicius, A.: Integrated modeling: adopting architecture frameworks for model-based systems engineering. http://163.117.147.32/joomlaaeis/sese/slides/SESE_2014-Integrated_Modeling_Aurelijus.pdf
NATO. Naf v4 meta-model (model) (2013). http://nafdocs.org/modem/
OMG: Object Constraint Language, version 2.4, February 2014. http://www.omg.org/spec/OCL/2.4/PDF
OMG: OMG Systems Modeling Language (OMG SysML ™), version 1.4. June 2015. http://www.omg.org/spec/SysML/1.4/PDF
OMG: OMG Unified Modeling Language ™(OMG UML). Structured Classifiers, p. 181. OMG, March 2015. http://www.omg.org/spec/UML/2.5/PDF
Richters, M., Gogolla, M.: On formalizing the UML object constraint language OCL. In: International Conference on Conceptual Modeling, pp. 449–464. Springer (1998)
Van Laarhoven, P.J., Aarts, E.H.: Simulated annealing. In: Simulated Annealing: Theory and Applications, pp. 7–15. Springer (1987)
Warmer, J.B., Kleppe, A.G.: The Object Constraint Language: Precise Modeling with UML (Addison-Wesley object technology series) (1998)
Acknowledgement
I warmly thank Thierry Benoist from the LocalSolver company for his precious help regarding the constraints implementation. I also thank Erwan Beurier from IMT Atlantiques (Institut Mines-Telecom Bretagne, France) for his first implementation of the MEGA to LocalSolver converter.
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Ernadote, D. (2019). Ontology-Based Optimization for Systems Engineering. In: Bonjour, E., Krob, D., Palladino, L., Stephan, F. (eds) Complex Systems Design & Management. CSD&M 2018. Springer, Cham. https://doi.org/10.1007/978-3-030-04209-7_2
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DOI: https://doi.org/10.1007/978-3-030-04209-7_2
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