Abstract
A System of Systems architecting problem aims to determine a selection of systems, which are capable of providing a set of desired capabilities. A SoS architect usually has multiple objectives in generating efficient architectures such as minimization of the total cost and maximization the overall performance of the SoS. This study formulates a biobjective SoS architecting problem with these two objectives. Here, we consider that, by allocating funds to the systems, the SoS architect can improve the performance of the capabilities the systems can provide. The resulting architecting problem is a biobjective mixed-integer linear programming model. Specifically, the system selection decisions are binary while the fund allocation decisions are continuous. We first discuss the application of the adaptive epsilon-constraint method as an exact method for solving this model. Then, we propose an evolutionary method and compare its performance with the exact method. Finally, a numerical study demonstrates the benefits of fund allocation in the SoS architecting process.
Recommended Citation
H. Farhangi et al., "Multiobjective System of Systems Architecting with Performance Improvement Funds," Procedia Computer Science, vol. 95, pp. 119 - 125, Elsevier, Nov 2016.
The definitive version is available at https://doi.org/10.1016/j.procs.2016.09.301
Meeting Name
Complex Adaptive Systems (2016: Nov. 2-4, Los Angeles, CA)
Department(s)
Engineering Management and Systems Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Adaptive systems; Architecture; Integer programming; Multiobjective optimization; Systems engineering; Efficient architecture; Epsilon-constraint method; Evolutionary method; Mixed integer linear programming model; Multi objective; Multiple-objectives; Performance Improvement; System selection; System of systems
International Standard Serial Number (ISSN)
1877-0509
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2016 The Authors, 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 Nov 2016
Comments
This work is partially supported by the US Department of Defense through the Systems Engineering Research Center (SERC) under Contract HQ0034-13-D-0004. SERC is a federally funded University Affiliated Research Center managed by Stevens Institute of Technology.