System of Systems Architecture Generation and Evaluation Using Evolutionary Algorithms
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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.
