• DocumentCode
    1498791
  • Title

    A Modeling Framework for Engineered Complex Adaptive Systems

  • Author

    Haghnevis, Moeed ; Askin, Ronald G.

  • Author_Institution
    Sch. of Comput., Inf., & Decision Syst. Eng., Arizona State Univ., Tempe, AZ, USA
  • Volume
    6
  • Issue
    3
  • fYear
    2012
  • Firstpage
    520
  • Lastpage
    530
  • Abstract
    The objective of this paper is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in a certain engineered complex adaptive system. A conceptual framework is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The proposed modeling approach allows examining complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. Electrical power demand is used to illustrate the applicability of the modeling approach. We describe and use the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build our framework. The framework allows focus on the critical factors of an engineered system, but also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems without complex modeling. This paper adopts concepts of complex systems science to management science and system-of-systems engineering.
  • Keywords
    adaptive systems; large-scale systems; mathematical analysis; modelling; adaptive pattern prediction; artificial CAS; components behavior; conceptual framework; electrical power demand; engineered complex adaptive system; management science; mathematical models; modeling framework; natural CAS; natural complex adaptive systems; structure complexity; system-of-systems engineering; Adaptation models; Adaptive systems; Complexity theory; Electricity; Entropy; Logistics; Mathematical model; Complex adaptive systems (CASs); decentralization; emergence; engineered complexity; evolution; system of systems;
  • fLanguage
    English
  • Journal_Title
    Systems Journal, IEEE
  • Publisher
    ieee
  • ISSN
    1932-8184
  • Type

    jour

  • DOI
    10.1109/JSYST.2012.2190696
  • Filename
    6186758