• Media type: E-Book; Report; Text
  • Title: Optimality conditions and Moreau--Yosida regularization for almost sure state constraints
  • Contributor: Geiersbach, Caroline [Author]; Hintermüller, Michael [Author]
  • imprint: Weierstrass Institute for Applied Analysis and Stochastics publication server, 2021
  • Language: English
  • DOI: https://doi.org/10.20347/WIAS.PREPRINT.2862
  • Keywords: 49J20 ; 49K45 ; PDE-constrained optimization under uncertainty -- optimization in Banach spaces -- optimality conditions -- regularization -- convex stochastic optimization in Banach spaces -- two-stages stochastic optimization -- duality ; 49K20 ; 90C15 ; 49N15 ; article
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  • Description: We analyze a potentially risk-averse convex stochastic optimization problem, where the control is deterministic and the state is a Banach-valued essentially bounded random variable. We obtain strong forms of necessary and sufficient optimality conditions for problems subject to equality and conical constraints. We propose a Moreau--Yosida regularization for the conical constraint and show consistency of the optimality conditions for the regularized problem as the regularization parameter is taken to infinity.