Abstract
In this paper, an approach for adaptive reconfiguration of architecture of a complex system using computational intelligence techniques is proposed. This paper establishes that the simulated change in the relative importance of rules reflecting the significance of customer's key performance attributes could be used to affect architectural evolution. the proposed approach was demonstrated on a sample system. It was also extended to a general system. the evolving system architecture gave the system an adaptive feature in the sense that it accepted alternative components based on the simulated changes in the environment. Architecture alternatives were generated through genetic algorithms (GA), while fuzzy logic was used to determine the fittest architectures based on the ambiguous multi-dimensional performance attributes provided by the customer modeled in quality function deployment (QFD). the weights of fuzzy associative memory (FAM) rules were randomly changed to simulate results of environmental effects and demonstrate how the system would self-adapt. © 2011 Published by Elsevier Ltd.
Recommended Citation
K. Haris and C. H. Dagli, "Adaptive Reconfiguration of Complex System Architecture," Procedia Computer Science, vol. 6, pp. 147 - 152, Elsevier, Jan 2011.
The definitive version is available at https://doi.org/10.1016/j.procs.2011.08.029
Department(s)
Engineering Management and Systems Engineering
Publication Status
Open Access
Keywords and Phrases
Adaptive; Architectural evolution; Computational intelligence; Environmental effects; Fuzzy logic; Genetic algorithms; QFD; Quality function deployment
International Standard Serial Number (ISSN)
1877-0509
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2024 Elsevier, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Publication Date
01 Jan 2011
