Blanchet, J., Zhang, F., & Zwart, B. (2020). Efficient Scenario Generation for Heavy-tailed Chance Constrained Optimization. ArXiv. /abs/2002.02149

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Abstract

We consider a generic class of chance-constrained optimization problems with heavy-tailed (ie, power-law type) risk factors. In this setting, we use the scenario approach to obtain a constant approximation to the optimal solution with a computational complexity that is uniform in the risk tolerance parameter. We additionally illustrate the efficiency of our algorithm in the context of solvency in insurance networks.

Authors
JOSE Blanchet, F Zhang, BERT Zwart
Publication date
2020/2
Journal
arXiv preprint arXiv:2002.02149