Abstract
A computational intelligence approach to system-of-systems architecting is developed using multi-objective optimization. Such an approach yields a set of optimal solutions (the Pareto set) which has both advantages and disadvantages. The primary benefit is that a set of solutions provides a picture of the optimal solution space that a single solution cannot. The primary difficulty is making use of a potentially infinite set of solutions. Therefore, a significant part of this approach is the development of a method to model the solution set with a finite number of points allowing the architect to intelligently choose a subset of optimal solutions based on criteria outside of the given objectives. The approach developed incorporates a meta-architecture, multi-objective genetic algorithm, and a corner search to identify points useful for modeling the solution space. This approach is then applied to a network centric warfare problem seeking the optimum selection of twenty systems. Finally, using the same problem, it is compared to a hybrid approach using single-objective optimization with a fuzzy logic assessor to demonstrate the advantage of multi-objective optimization.
Recommended Citation
D. M. Curry and C. H. Dagli, "A Computational Intelligence Approach to System-of-Systems Architecting Incorporating Multi-Objective Optimization," Procedia Computer Science, vol. 44, no. C, pp. 86 - 94, Elsevier, Mar 2015.
The definitive version is available at https://doi.org/10.1016/j.procs.2015.03.036
Meeting Name
2015 Conference on Systems Engineering Research (2015: Mar. 17-19, Hoboken, New Jersey)
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
Algorithms; Artificial intelligence; Computation theory; Evolutionary algorithms; Fuzzy logic; Gallium; Genetic algorithms; Military applications; Network architecture; Optimal systems; Optimization; System of systems; Systems engineering; Engineering research; Architecting; MOEA; MOP; Multi objective evolutionary algorithms; Multi-objective optimization problem; SoS; Multiobjective optimization; GA; Meta-Architecture; Multi-Objective Evolutionary Algorithm; 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
© 2015 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 Mar 2015
