Conference article

Towards Design Optimization with OpenModelica Emphasizing Parameter Optimization with Genetic Algorithms

Hubert Thieriot
Center For Energy and Processes, MINES ParisTech, Palaiseau, France

Maroun Nemura
Center For Energy and Processes, MINES ParisTech, Palaiseau, France

Mohsen Torabzadeh-Tari
PELAB Programming Environment Lab, Dept. Computer Science, Linkoping University Sweden

Peter Fritzson
PELAB Programming Environment Lab, Dept. Computer Science, Linkoping University Sweden

Rajiv Singh
Evonik Energy Services, Pvt. Ltd., India

John John Kocherry
Evonik Energy Services, Pvt. Ltd., India

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Published in: Proceedings of the 8th International Modelica Conference; March 20th-22nd; Technical Univeristy; Dresden; Germany

Linköping Electronic Conference Proceedings 63:84, p. 756-762

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Published: 2011-06-30

ISBN: 978-91-7393-096-3

ISSN: 1650-3686 (print), 1650-3740 (online)


One of the main goals when modeling a physical system is to optimize its design or configuration. Currently existing platforms are often dependent on commercial software or are based on in-house and special-purpose development tools. These two alternatives present disadvantages that limit sharing and reusability. The same assessment has partly motivated the origin of the Modelica language itself. In this paper; a new optimization platform called OMOptim is presented. Intrinsically linked with OpenModelica; this platform is mainly aimed at facilitating optimization algorithm development; as well as application use together with models. A first version is already available and three test cases of which one using respectively Dymola and two using OpenModelica are presented. Future developments and design considerations of OMOptim but also of related OpenModelica computation functions are also discussed.


Optimization; model-based; parameter; genetic algorithm; Modelica; modeling; simulation


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