Distributionally Robust Joint Chance Constrained Problem under Moment Uncertainty | Zendy

Ke-wei Ding | Zendy

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Distributionally Robust Joint Chance Constrained Problem under Moment Uncertainty

Author(s) -

Ke-wei Ding

Publication year - 2014

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2014/487178

Subject(s) - semidefinite programming , robust optimization , mathematical optimization , mathematics , moment (physics) , convex optimization , quadratic programming , regular polygon , semidefinite embedding , quadratically constrained quadratic program , second order cone programming , cvar , quadratic equation , joint (building) , expected shortfall , architectural engineering , physics , geometry , management , classical mechanics , engineering , economics , risk management

We discuss and develop the convex approximation for robust joint chance constraints under uncertainty of first- and second-order moments. Robust chance constraints are approximated by Worst-Case CVaR constraints which can be reformulated by a semidefinite programming. Then the chance constrained problem can be presented as semidefinite programming. We also find that the approximation for robust joint chance constraints has an equivalent individual quadratic approximation form

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