TY - GEN
T1 - Constraint management of reduced representation variables in decomposition-based design optimization
AU - Alexander, Michael J.
AU - Allison, James T.
AU - Papalambros, Panos Y.
AU - Gorsich, David J.
PY - 2010
Y1 - 2010
N2 - In decomposition-based design optimization strategies, such as Analytical Target Cascading (ATC), it is sometimes necessary to use reduced dimensionality representations to approximate functions of large dimensionality whose values need to be exchanged among subproblems. The reduced representation variables may not be physically meaningful, and it can become challenging to constrain them properly and define the model validity region. For example, in coordination strategies like ATC, representing vector-valued coupling variables with improperly constrained reduced representation variables can lead to poor performance or convergence failure. This paper examines two approaches for constraining effectively the model validity region of reduced representation variables based on proper orthogonal decomposition: a penalty value-based heuristic and a support vector domain description. An ATC application on electric vehicle design helps to illustrate the concepts discussed.
AB - In decomposition-based design optimization strategies, such as Analytical Target Cascading (ATC), it is sometimes necessary to use reduced dimensionality representations to approximate functions of large dimensionality whose values need to be exchanged among subproblems. The reduced representation variables may not be physically meaningful, and it can become challenging to constrain them properly and define the model validity region. For example, in coordination strategies like ATC, representing vector-valued coupling variables with improperly constrained reduced representation variables can lead to poor performance or convergence failure. This paper examines two approaches for constraining effectively the model validity region of reduced representation variables based on proper orthogonal decomposition: a penalty value-based heuristic and a support vector domain description. An ATC application on electric vehicle design helps to illustrate the concepts discussed.
KW - Analytical target cascading
KW - Decomposition
KW - Design optimization
KW - Proper orthogonal decomposition
KW - Reduced representation
KW - Support vector machines
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U2 - 10.1115/DETC2010-28788
DO - 10.1115/DETC2010-28788
M3 - Conference contribution
AN - SCOPUS:80055000225
SN - 9780791844090
T3 - Proceedings of the ASME Design Engineering Technical Conference
SP - 755
EP - 764
BT - ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2010
T2 - ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2010
Y2 - 15 August 2010 through 18 August 2010
ER -