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Published in: Structural and Multidisciplinary Optimization 4/2014

01-10-2014 | INDUSTRIAL APPLICATION

Bilevel multiobjective packaging optimization for automotive design

Authors: Brian Dandurand, Paolo Guarneri, Georges M. Fadel, Margaret M. Wiecek

Published in: Structural and Multidisciplinary Optimization | Issue 4/2014

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Abstract

The successful application of multiobjective optimization to engineering problems has motivated studies of more complex systems involving multiple subsystems and design disciplines, each with multiple design criteria. Complex system design requires participation of different teams that are highly specialized within each discipline and subsystem. Such a high differentiation results in limited sharing of information among the design teams. The mathematical modeling and the solution algorithm proposed in this paper address the issue of coordinating multiple design problems that negotiate according to conflicting criteria. The design of the layout of hybrid vehicles is formulated as a bilevel decomposed problem including a vehicle level and a battery level in concert with the specialization of the respective design teams required at each level. An iterative algorithm, the Multiobjective Decomposition Algorithm (MODA) is proposed, whose generated sequences are shown to converge to efficient designs for the overall design problem under certain conditions examined in the context of the block coordinate descent method and the method of multipliers. MODA applied to the hybrid electric design problem captures the bilevel tradeoffs originating by the conflicting objectives at the vehicle and battery levels.

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Metadata
Title
Bilevel multiobjective packaging optimization for automotive design
Authors
Brian Dandurand
Paolo Guarneri
Georges M. Fadel
Margaret M. Wiecek
Publication date
01-10-2014
Publisher
Springer Berlin Heidelberg
Published in
Structural and Multidisciplinary Optimization / Issue 4/2014
Print ISSN: 1615-147X
Electronic ISSN: 1615-1488
DOI
https://doi.org/10.1007/s00158-014-1120-0

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