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Decision making under uncertainty for design of resilient engineered systems

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  • MacKenzie, Cameron A.
  • Hu, Chao

Abstract

Designing resilient engineered systems that can sense and withstand adverse events and recover from the effects of the adverse events is increasingly seen as an important goal of engineering design. This paper proposes a value-driven design for resilience (VD2R) framework in order to enable the assessment of system resilience and the optimization of decision variables (or design characteristics) that maximize the value of the system for a firm. The VD2R framework possesses three unique features that allow system resilience and value to be addressed in a theoretically founded and explicit way. First, it assesses the time-dependent resilience of an engineered system by explicitly modeling the redundancy, robustness, and restoration of the system. This assessment captures the stochastic behavior of degradation and restoration and their impact on system resilience. Second, it encompasses a value model that links time-dependent system resilience to a design firm's future profit. Third, the VD2R framework offers an efficient optimization method to solve high-dimension, mixed-integer decision-making models. The proposed framework is demonstrated with a case study, where the resilience of a series-parallel system is modeled and its design characteristics optimized.

Suggested Citation

  • MacKenzie, Cameron A. & Hu, Chao, 2019. "Decision making under uncertainty for design of resilient engineered systems," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    • Handle: RePEc:eee:reensy:v:192:y:2019:i:c:s0951832016307165
    DOI: 10.1016/j.ress.2018.05.020
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    4. Liu, Jin & Zhai, Changhai & Yu, Peng, 2022. "A Probabilistic Framework to Evaluate Seismic Resilience of Hospital Buildings Using Bayesian Networks," Reliability Engineering and System Safety, Elsevier, vol. 226(C).

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