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P. Krokhmal, R. Murphey, P. Pardalos, S. Uryasev and G. Zrazhevsky, “Robust Decision Making: Addressing Uncertainties in Distributions,” In: S. Butenko, et al., Eds., Cooperative Control: Models, Applications and Algorithms, Kluwer Academic Publishers, Dordrecht, 2003, pp. 165-185.

has been cited by the following article:

• TITLE: Optimization of Critical Systems for Robustness in a Multistate World

  AUTHORS: Edouard Kujawski

  KEYWORDS: Critical System; Robustness; Risk; Multistate World; Diversification; Hybrid Solution; Portfolio Allocation; Stochastic Optimization; Expected Utility Theory; Minimax Regret; Disappointment Theory

  JOURNAL NAME: American Journal of Operations Research, Vol.3 No.1A, January 30, 2013

  ABSTRACT: Critical systems are typically complex systems that are required to perform reliably over a wide range of scenarios, or multistate world. Seldom does a single system exist that performs best for all plausible scenarios. A robust solution, one that performs relatively well over a wide range of scenarios, is often the preferred choice for reduced risk at an acceptable cost. The alternative with the maximum expected utility may possess vulnerabilities that could be exploited. The best strategy is likely to be a hybrid solution. The von Neumann-Morgenstern Expected Utility Theory (EUT) would never select such a solution because, given its linear functional form, the expected utility of a hybrid solution cannot be greater than that of every constituent alternative. The continuity axiom and the independence axiom are assessed to be unrealistic for the problem of interest. Several well-known decision models are analyzed and demonstrated to be potentially misleading. The linear disappointment model modifies EUT by adding a term proportional to downside risk; however, it does not provide a mathematical basis for determining preferred hybrid solutions. The paper proposes a portfolio allocation model with stochastic optimization as a flexible and transparent method for defining choice problems and determining hybrid solutions for critical systems with desirable properties such as diversification and robustness.