TY - JOUR
T1 - Many objective visual analytics
T2 - Rethinking the design of complex engineered systems
AU - Woodruff, Matthew J.
AU - Reed, Patrick M.
AU - Simpson, Timothy W.
N1 - Funding Information:
The second author of this work was partially supported by the US National Science Foundation under Grant CBET-0640443. The computational resources for this work were provided in part through instrumentation funded by the National Science Foundation through Grant OCI-0821527. Any opinions,findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the US National Science Foundation.
PY - 2013/7
Y1 - 2013/7
N2 - Many cognitive and computational challenges accompany the design of complex engineered systems. This study proposes the many-objective visual analytics (MOVA) framework as a new approach to the design of complex engineered systems. MOVA emphasizes learning through problem reformulation, enabled by visual analytics and many-objective search. This study demonstrates insights gained by evolving the formulation of a General Aviation Aircraft (GAA) product family design problem. This problem's considerable complexity and difficulty, along with a history encompassing several formulations, make it well-suited to demonstrate the MOVA framework. The MOVA framework results compare a single objective, a two objective, and a ten objective formulation for optimizing the GAA product family. Highly interactive visual analytics are exploited to demonstrate how decision biases can arise for lower dimensional, highly aggregated problem formulations.
AB - Many cognitive and computational challenges accompany the design of complex engineered systems. This study proposes the many-objective visual analytics (MOVA) framework as a new approach to the design of complex engineered systems. MOVA emphasizes learning through problem reformulation, enabled by visual analytics and many-objective search. This study demonstrates insights gained by evolving the formulation of a General Aviation Aircraft (GAA) product family design problem. This problem's considerable complexity and difficulty, along with a history encompassing several formulations, make it well-suited to demonstrate the MOVA framework. The MOVA framework results compare a single objective, a two objective, and a ten objective formulation for optimizing the GAA product family. Highly interactive visual analytics are exploited to demonstrate how decision biases can arise for lower dimensional, highly aggregated problem formulations.
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U2 - 10.1007/s00158-013-0891-z
DO - 10.1007/s00158-013-0891-z
M3 - Article
AN - SCOPUS:84879695508
SN - 1615-147X
VL - 48
SP - 201
EP - 219
JO - Structural and Multidisciplinary Optimization
JF - Structural and Multidisciplinary Optimization
IS - 1
ER -