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

  • Authors:

  • Matthew J. Woodruff;Patrick M. Reed;Timothy W. Simpson

  • Affiliations:

  • Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, USA 16802;Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park, USA 16802;Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, USA 16802

  • Venue:
  • Structural and Multidisciplinary Optimization
  • Year:
  • 2013

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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.