Distributionally robust optimization with polynomial densities: theory, models and algorithms
نویسندگان
چکیده
منابع مشابه
Data-driven Distributionally Robust Polynomial Optimization
We consider robust optimization for polynomial optimization problems where the uncertainty set is a set of candidate probability density functions. This set is a ball around a density function estimated from data samples, i.e., it is data-driven and random. Polynomial optimization problems are inherently hard due to nonconvex objectives and constraints. However, we show that by employing polyno...
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ژورنال
عنوان ژورنال: Mathematical Programming
سال: 2019
ISSN: 0025-5610,1436-4646
DOI: 10.1007/s10107-019-01429-5