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Ontology-Based Optimization for Systems Engineering

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Complex Systems Design & Management (CSD&M 2018)

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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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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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Authors and Affiliations

  1. Airbus Defence and Space, Elancourt, France

    Dominique Ernadote

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  1. Dominique Ernadote
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Correspondence to Dominique Ernadote .

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Editors and Affiliations

  1. Université de Lorraine, Laxou, France

    Eric Bonjour

  2. CESAMES, Paris, France

    Daniel Krob

  3. Safran, Magny Les Hameaux, France

    Luca Palladino

  4. Be-Bound, Marnes La Coquette, France

    François Stephan

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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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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04208-0

  • Online ISBN: 978-3-030-04209-7

  • eBook Packages: EngineeringEngineering (R0)

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