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Effectiveness of Surrogate-Based Optimization Algorithms for System Architecture Optimization

Bussemaker, Jasper and Bartoli, Nathalie and Lefebvre, Thierry and Ciampa, Pier Davide and Nagel, Björn (2021) Effectiveness of Surrogate-Based Optimization Algorithms for System Architecture Optimization. AIAA AVIATION 2021 Forum, 2-6 August 2021, Virtual Event. doi: 10.2514/6.2021-3095.

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Official URL: http://dx.doi.org/10.2514/6.2021-3095


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.

Item URL in elib:https://elib.dlr.de/143456/
Document Type:Conference or Workshop Item (Lecture)
Title:Effectiveness of Surrogate-Based Optimization Algorithms for System Architecture Optimization
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Bussemaker, JasperJasper.Bussemaker (at) dlr.dehttps://orcid.org/0000-0002-5421-6419
Bartoli, Nathalienathalie.bartoli (at) onera.frUNSPECIFIED
Lefebvre, Thierrythierry.lefebvre (at) onera.frUNSPECIFIED
Ciampa, Pier DavidePier.Ciampa (at) dlr.dehttps://orcid.org/0000-0003-1652-4899
Nagel, BjörnBjoern.Nagel (at) dlr.deUNSPECIFIED
Date:28 July 2021
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
DOI :10.2514/6.2021-3095
Keywords:mdo, optimization, surrogate-based optimization, kriging, rbf, system architecting
Event Title:AIAA AVIATION 2021 Forum
Event Location:Virtual Event
Event Type:international Conference
Event Dates:2-6 August 2021
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Efficient Vehicle
DLR - Research area:Aeronautics
DLR - Program:L EV - Efficient Vehicle
DLR - Research theme (Project):L - Digital Technologies
Location: Hamburg
Institutes and Institutions:Institute of System Architectures in Aeronautics > Aircraft Design and System Integration
Deposited By: Bussemaker, Jasper
Deposited On:10 Aug 2021 07:13
Last Modified:10 Aug 2021 07:13

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