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
Link To Document :
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