Distributionally robust polynomial chance-constraints under mixture ambiguity sets

DOI10.1007/s10107-019-01434-8zbMath1469.41005arXiv1803.11500OpenAlexW2973367427WikidataQ127252618 ScholiaQ127252618MaRDI QIDQ2220666

Tillmann Weisser, Jean-Bernard Lasserre

Publication date: 25 January 2021

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1803.11500

zbMATH Keywords

probability distributionsemidefinite programchance-constraintasymptotic guarantee

Mathematics Subject Classification ID

Semidefinite programming (90C22) Numerical methods involving duality (49M29) Approximation methods and heuristics in mathematical programming (90C59) Reasoning under uncertainty in the context of artificial intelligence (68T37) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Approximation with constraints (41A29)

Related Items

Frameworks and results in distributionally robust optimization, Chance-constrained optimization under limited distributional information: a review of reformulations based on sampling and distributional robustness, Distributionally robust optimization with moment ambiguity sets

Uses Software

• GloptiPoly
• Mosek
• GitHub

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