Abstract
Evolutionary algorithms and computational intelligence represent a developing technology and science that provides great potential in the area of system and system-of-systems architecture generation, categorization and evaluation. Classical system engineering analysis techniques have been used to represent a system architecture in a manner that is compatible with evolutionary algorithms and computational intelligence techniques. This paper focuses on specific system relationship configurations and attributes that are required to successfully aggregate the best-fit function in a fuzzy associative memory that is used in an evolutionary algorithm to generate and evaluate system architectures.
Recommended Citation
J. J. Simpson and C. H. Dagli, "System of Systems Architecture Generation and Evaluation Using Evolutionary Algorithms," Proceedings of the 2nd Annual IEEE Systems Conference 2008, Institute of Electrical and Electronics Engineers (IEEE), Apr 2008.
The definitive version is available at https://doi.org/10.1109/SYSTEMS.2008.4518989
Meeting Name
2nd Annual IEEE Systems Conference 2008
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
Computational Intelligence; Evolutionary Algorithms; System; System of Systems
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2008 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Apr 2008
