Title
Coupling between a multi-physics workflow engine and an optimization framework.
Abstract
A generic coupling method between a multi-physics workflow engine and an optimization framework is presented in this paper. The coupling architecture has been developed in order to preserve the integrity of the two frameworks. The objective is to provide the possibility to replace a framework, a workflow or an optimizer by another one without changing the whole coupling procedure or modifying the main content in each framework. The coupling is achieved by using a socket-based communication library for exchanging data between the two frameworks. Among a number of algorithms provided by optimization frameworks, Genetic Algorithms (GAs) have demonstrated their efficiency on single and multiple criteria optimization. Additionally to their robustness, GAs can handle non-valid data which may appear during the optimization. Consequently GAs work on most general cases. A parallelized framework has been developed to reduce the time spent for optimizations and evaluation of large samples. A test has shown a good scaling efficiency of this parallelized framework. This coupling method has been applied to the case of SYCOMORE (SYstem COde for MOdeling tokamak REactor) which is a system code developed in form of a modular workflow for designing magnetic fusion reactors. The coupling of SYCOMORE with the optimization platform URANIE enables design optimization along various figures of merit and constraints.
Year
DOI
Venue
2016
10.1016/j.cpc.2015.11.002
Computer Physics Communications
Keywords
Field
DocType
Multi-physics workflow engine,Optimization framework,Code coupling,DEMO fusion reactor design
Mathematical optimization,Coupling,Real-time computing,Robustness (computer science),Figure of merit,Modular design,Workflow engine,Scaling,Workflow,Genetic algorithm,Mathematics,Distributed computing
Journal
Volume
ISSN
Citations 
200
0010-4655
0
PageRank 
References 
Authors
0.34
8
17
Name
Order
Citations
PageRank
L. Di Gallo100.34
C. Reux230.76
Frederic Imbeaux3183.53
J.-F. Artaud400.34
Michał Owsiak5256.07
B. Saoutic600.34
giovanni aiello700.34
P. Bernardi800.34
G. Ciraolo900.34
J. Bucalossi1000.34
J.-L. Duchateau1100.34
clement fausser1200.34
D. Galassi1300.34
P. Hertout1400.34
J.-C. Jaboulay1500.34
A. Li-Puma1600.34
L. Zani1700.34