10.2514/6.2021-3095
https://zenodo.org/records/5735114
oai:zenodo.org:5735114
Bussemaker, J.H.
J.H.
Bussemaker
DLR (German Aerospace Center), Institute of System Architectures in Aeronautics, Hamburg, Germany
Bartoli, N.
N.
Bartoli
ONERA
Lefebvre, T.
T.
Lefebvre
ONERA
Ciampa, P.D.
P.D.
Ciampa
DLR (German Aerospace Center), Institute of System Architectures in Aeronautics, Hamburg, Germany
Nagel, N.
N.
Nagel
DLR (German Aerospace Center), Institute of System Architectures in Aeronautics, Hamburg, Germany
Effectiveness of Surrogate-Based Optimization Algorithms for System Architecture Optimization
Zenodo
2021
Surrogate Modeling
Optimization
2021-07-28
https://zenodo.org/communities/agile4
https://zenodo.org/communities/eu
Creative Commons Attribution 4.0 International
The design of complex system architectures brings with it a number of challenging issues,
among others large combinatorial design spaces. Optimization can be applied to explore the
design space, however gradient-based optimization algorithms cannot be applied due to the
mixed-discrete nature of the design variables. It is investigated how effective surrogate-based
optimization algorithms are for solving the black-box, hierarchical, mixed-discrete, multi-
objective system architecture optimization problems. Performance is compared to the NSGA-
II multi-objective evolutionary algorithm. An analytical benchmark problem that exhibits
most important characteristics of architecture optimization is defined. First, an investigation
into algorithm effectiveness is performed by measuring how accurately a known Pareto-front
can be approximated for a fixed number of function evaluations. Then, algorithm efficiency
is investigated by applying various multi-objective convergence criteria to the algorithms and
establishing the possible trade-off between result quality and function evaluations needed.
Finally, the impact of hidden constraints on algorithm performance is investigated. The code
used for this paper has been published.
European Commission
10.13039/501100000780
815122
AGILE 4.0: Towards cyber-physical collaborative aircraft development