Gradients and Subgradients of Buffered Failure Probability
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Abstract (arXiv)
Gradients and subgradients are central to optimization and sensitivity analysis of buffered failure probabilities. We furnish a characterization of subgradients based on subdifferential calculus in the case of finite probability distributions and, under additional assumptions, also a gradient expression for general distributions. Several examples illustrate the application of the results, especially in the context of optimality conditions.
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References · 4
- 2019Solving Chance-Constrained Problems via a Smooth Sample-Based Nonlinear Approximationcited by 6
- 2021Certifiable Risk-Based Engineering Design Optimizationcited by 4
- 2017Subdifferential characterization of probability functions under Gaussian distributioncited by 2
- 2021Data-driven optimization of reliability using buffered failure probabilitycited by 1
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