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A Modeling Framework for Engineered Complex Adaptive Systems

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2 Author(s)
Moeed Haghnevis ; School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA ; Ronald G. Askin

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.

Published in:

IEEE Systems Journal  (Volume:6 ,  Issue: 3 )