Abstract
A System of Systems (SoS) architecting problem requires creating a selection of systems in order to provide a set of capabilities. SoS architecting finds many applications in military/defense projects. In this paper, we study a multi-objective SoS architecting problem, where the cost of the architecture is minimized while its performance is maximized. The cost of the architecture is the summation of the costs of the systems to be included in the SoS. Similarly, the performance of the architecture is defined as the sum of the performance of the capabilities, where the performance of a capability is the sum of the selected systems' contributions towards its performance. Here, nevertheless, the performance of a system in providing a capability is not known with certainty. To model this uncertainty, we assume that the performance of a system for providing a capability has lower and upper bounds and subject to complete uncertainty, i.e., no information is available about the probability distribution of the performance values. To solve the resulting multi-objective SoS architecting problem with uncertainty, we propose and compare three robust approaches: max-min, max-max, and max-mid. We apply these methods on a military example and numerically compare the results of the different approaches.
Recommended Citation
H. Farhangi et al., "Combining Max-Min and Max-Max Approaches for Robust SoS Architecting," Procedia Computer Science, vol. 95, pp. 103 - 110, Elsevier, Nov 2016.
The definitive version is available at https://doi.org/10.1016/j.procs.2016.09.299
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; Costs; Military applications; Probability distributions; Systems engineering; Evolutionary method; Lower and upper bounds; Max-min; Multi objective; Performance value; Robust approaches; System Performance; 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.