Keywords and Phrases
Architecture; Clustering; Evolutionary algorithm; Fuzzy logic; Neural networks; System-of-systems
The dynamic planning for a system-of-systems (SoS) is a challenging endeavor. Large scale organizations and operations constantly face challenges to incorporate new systems and upgrade existing systems over a period of time under threats, constrained budget and uncertainty. It is therefore necessary for the program managers to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. Managers and engineers are always looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This research helps in analyzing sequential decisions in an evolving SoS architecture based on the wave model through three key features namely; meta-architecture generation, architecture assessment and architecture implementation. Meta-architectures are generated using evolutionary algorithms and assessed using type II fuzzy nets. The approach can accommodate diverse stakeholder views and convert them to key performance parameters (KPP) and use them for architecture assessment. On the other hand, it is not possible to implement such architecture without persuading the systems to participate into the meta-architecture. To address this issue a negotiation model is proposed which helps the SoS manger to adapt his strategy based on system owners behavior. This work helps in capturing the varied differences in the resources required by systems to prepare for participation. The viewpoints of multiple stakeholders are aggregated to assess the overall mission effectiveness of the overarching objective. An SAR SoS example problem illustrates application of the method. Also a dynamic programing approach can be used for generating meta-architectures based on the wave model. "--Abstract, page iii.
Dagli, Cihan H., 1949-
Enke, David Lee, 1965-
Engineering Management and Systems Engineering
Ph. D. in Systems Engineering
United States. Department of Defense
Missouri University of Science and Technology
xii, 173 pages
© 2015 Siddharth Agarwal, All rights reserved.
Dissertation - Open Access
Library of Congress Subject Headings
Systems engineering -- Data processing
Evolutionary programming (Computer science)
Neural networks (Computer science)
Electronic OCLC #
Agarwal, Siddharth, "Computational intelligence based complex adaptive system-of-systems architecture evolution strategy" (2015). Doctoral Dissertations. 2401.