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KR25 System of Systems Architecture Evaluation Using Evolutionary Computation
Author(s) -
Simpson Joseph J,
Dagli Cihan H.
Publication year - 2008
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2008.tb00911.x
Subject(s) - computer science , evolutionary algorithm , evolutionary computation , context (archaeology) , evolutionary programming , theoretical computer science , artificial intelligence , interactive evolutionary computation , paleontology , biology
Evolutionary computation and evolutionary algorithms represent a developing science and technology that can be effectively applied to the generation and evaluation of system of systems architectures. A general technique used by systems engineering professionals is a binary matrix representation of a system or system of systems. The specific meaning and semantics of the binary relationship depends of the type of representation used. Typical representations are, “N squared”, design structure matrix, dependency structure matrix, and implication matrix. A key feature of these typical representations is their direct relationship to the structure required in an evolutionary computational approach. Evolutionary algorithms can be applied to the evaluation and optimization of these matrix structures. A new evolutionary algorithm has been developed that applies specifically to the generation and evaluation of systems and system of systems. This new evolutionary algorithm incorporates a fuzzy inference system in the calculation of the best fit evaluation. The current industrial and social environment is populated with a vast array of existing and developing systems. Any new system must take this context into account. Evolutionary computation is applied to assist the system architect and engineer in the evaluation of these complex configurations and interface sets. The new evolutionary computing techniques are applied to system of systems architecting tasks using a well defined set of measures of effectiveness (MOE). The systems architecting task is divided into three general areas organized around the roles and responsibilities associated with the system architect, the system customer and the system engineer. The system architect is responsible for the complete system operation and MOE balance, focused on life‐cycle cost and risk. The customer is responsible for the mission profile and mission functions. Operational effectiveness and operational suitability areas are the responsibility of the systems engineers. Affordability, risk, operational effectiveness and operational suitability are the four MOE used to evaluate the candidate system of systems architectures.