NordDesign 2024
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Knowledge Base Repository
In addition to research papers, the Design Society is developing several valuable resources for those interested in the study of design. These include a repository of PhD theses, a library of case studies and transcripts of design activities, and an archive of our newsletters. Please note that these resources are accessible exclusively to Design Society members.
Constrained Multi-Objective Design Optimization in Systems Engineering Using Active Learning
Bleisinger, Oliver; Keil, Mareike; Eigner, Martin
Type:
Year:
2024
Editor:
Malmqvist, J.; Candi, M.; Saemundsson, R. J.; Bystrom, F. and Isaksson, O.
Author:
Series:
NordDESIGN
Institution:
University of Kaiserslautern-Landau, Germany; University of Mannheim, Germany; EIGNER engineering consult, Germany
Page(s):
352-361
DOI number:
ISBN:
978-1-912254-21-7
Abstract:
Design of complex systems demands exploration of high-dimensional design spaces due to competing design goals and numerous design parameters. Manual tradeoff studies in hyperspaces are laborious and hence, Artificial Intelligence offers a solution. This paper introduces a Constrained Multi-Objective Design Optimization approach in Systems Engineering using Artificial Intelligence and evaluates this method through an automotive case study. Therefore, an Active Learning algorithm is presented to automate identifying pareto fronts by inferring simulation models as substitution for learning data.
Keywords:
