Optimization of large-scale heterogeneous system-of-systems models.

Parekh, Ojas ; Watson, Jean-Paul ; Phillips, Cynthia Ann ; Siirola, John ; Swiler, Laura Painton ; Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA) ; Lee, Herbert K. H. (University of California, Santa Cruz, Santa Cruz, CA) ; Hart, William Eugene ; Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA) ; Woodruff, David L. (University of California, Davis, Davis, CA)

Sandia National Laboratories

关键词: Economics;    Decision Making;    Optimization;    Simulation;    99 General And Miscellaneous//Mathematics, Computing, And Information Science;   

DOI  :  10.2172/1034869
RP-ID  :  SAND2012-0529
RP-ID  :  AC04-94AL85000
RP-ID  :  1034869

美国|英语

来源: UNT Digital Library

【 摘 要 】

Decision makers increasingly rely on large-scale computational models to simulate and analyze complex man-made systems. For example, computational models of national infrastructures are being used to inform government policy, assess economic and national security risks, evaluate infrastructure interdependencies, and plan for the growth and evolution of infrastructure capabilities. A major challenge for decision makers is the analysis of national-scale models that are composed of interacting systems: effective integration of system models is difficult, there are many parameters to analyze in these systems, and fundamental modeling uncertainties complicate analysis. This project is developing optimization methods to effectively represent and analyze large-scale heterogeneous system of systems (HSoS) models, which have emerged as a promising approach for describing such complex man-made systems. These optimization methods enable decision makers to predict future system behavior, manage system risk, assess tradeoffs between system criteria, and identify critical modeling uncertainties.