Conference abstracts

Session C3 - Continuous Optimization

July 17, 19:00 ~ 19:30 - Room 111

Solving chance-constrained problems using a kernel VaR estimator

Andreas Waechter

Northwestern University, United States   -   andreasw.waechter@northwestern.edu

We present a reformulation of nonlinear optimization problems with chance constraints that replaces a probabilistic constraint by a nonparametric value-at-risk estimator. The estimator smooths the historical VaR via a kernel, resulting in a better approximation of the quantile and reducing the nonconvexity of the feasible region. An optimization algorithm is proposed that permits the efficient treatment of joint chance constraints. Theoretical convergence properties and numerical experiments are presented.

Joint work with Alejandra Pena-Ordieres (Northwestern University, USA).

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