Structural and Multidisciplinary Optimization

, Volume 48, Issue 1, pp 201–219

Many objective visual analytics: rethinking the design of complex engineered systems

  • Matthew J. Woodruff
  • Patrick M. Reed
  • Timothy W. Simpson
Research Paper
First Online:
Received:
Revised:
Accepted:

Abstract

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.

Keywords

Multi-objective optimization Multidimensional data visualization Product family design 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Matthew J. Woodruff
    • 1
  • Patrick M. Reed
    • 2
  • Timothy W. Simpson
    • 1
  1. 1.Department of Industrial and Manufacturing EngineeringThe Pennsylvania State UniversityUniversity ParkUSA
  2. 2.Department of Civil and Environmental EngineeringThe Pennsylvania State UniversityUniversity ParkUSA

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