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
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