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A Robust Portfolio Optimization Approach Using Parametric Piecewise Linear Models of System Dependencies

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Abstract

“System of Systems” architecture problems can be very challenging due to the large number of systems involved and complex interdependencies that exist between and among them. The high number of decision variables and interactions presents the need for an appropriate collection of methods, processes, and tools that can help practitioners deal with such complexities and answer key questions that typically arise when evolving an architecture. In this chapter, we build on prior work toward developing a System-of-Systems Analytic Workbench and propose a combined use of two of the workbench tools, namely, the Robust Portfolio Optimization and Systems Operational Dependency Analysis tools. The purpose of the combination is to more explicitly introduce the dependency modeling capabilities of one with the computationally efficient decision-support capabilities of the other. We demonstrate application of the proposed combined approach on a conceptual Naval Warfare Scenario problem.

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Acknowledgments

This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Systems Engineering Research Center (SERC) under Contract HQ0034-13-D-005 RT #155. SERC is a federally funded University Affiliated Research Center managed by Stevens Institute of Technology.

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Correspondence to Navindran Davendralingam .

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Davendralingam, N., Guariniello, C., Delaurentis, D. (2018). A Robust Portfolio Optimization Approach Using Parametric Piecewise Linear Models of System Dependencies. In: Madni, A., Boehm, B., Ghanem, R., Erwin, D., Wheaton, M. (eds) Disciplinary Convergence in Systems Engineering Research. Springer, Cham. https://doi.org/10.1007/978-3-319-62217-0_7

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  • DOI: https://doi.org/10.1007/978-3-319-62217-0_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62216-3

  • Online ISBN: 978-3-319-62217-0

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