An Information-Theoretic Metric of System Complexity with Application to Engineering System Design Conference Paper uri icon


  • System complexity is considered a key driver of the inability of current system design practices to at times not recognize performance, cost, and schedule risks as they emerge. We present here a definition of system complexity and a quantitative metric for measuring that complexity based on information theory. We also derive sensitivity indices that indicate the fraction of complexity that can be reduced if more about certain factors of a system can become known. This information can be used as part of a resource allocation procedure aimed at reducing system complexity. Our methods incorporate Gaussian process emulators of expensive computer simulation models and account for both model inadequacy and code uncertainty. We demonstrate our methodology on a candidate design of an infantry fighting vehicle. 2012 by the Authors.

name of conference

  • 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
    20th AIAA/ASME/AHS Adaptive Structures Conference
    14th AIAA

published proceedings

  • 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference>BR<20th AIAA/ASME/AHS Adaptive Structures Conference>BR<14th AIAA

author list (cited authors)

  • Allaire, D., He, Q., & Willcox, K.

citation count

  • 0

complete list of authors

  • Allaire, Douglas||He, Qinxian||Willcox, Karen

publication date

  • January 2012