Approximation schemes for functional optimization problems

DOI10.1007/S10957-008-9471-6zbMath1176.90658OpenAlexW2051872019MaRDI QIDQ1024253

Marcello Sanguineti, Saverio Giulini

Publication date: 16 June 2009

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10957-008-9471-6

zbMATH Keywords

Ritz methodcurse of dimensionalityextended Ritz methodcomplexity of admissible solutionsupper bounds on accuracy

Mathematics Subject Classification ID

Newton-type methods (49M15) Approximation methods and heuristics in mathematical programming (90C59) Programming in abstract spaces (90C48)

Related Items (10)

On the curse of dimensionality in the Ritz method ⋮ Suboptimal solutions to dynamic optimization problems via approximations of the policy functions ⋮ A comparison between fixed-basis and variable-basis schemes for function approximation and functional optimization ⋮ Can dictionary-based computational models outperform the best linear ones? ⋮ Approximate dynamic programming for stochastic \(N\)-stage optimization with application to optimal consumption under uncertainty ⋮ New insights into Witsenhausen's counterexample ⋮ Estimates of variation with respect to a set and applications to optimization problems ⋮ Some comparisons of complexity in dictionary-based and linear computational models ⋮ Management of water resource systems in the presence of uncertainties by nonlinear approximation techniques and deterministic sampling ⋮ Suboptimal Policies for Stochastic $$N$$-Stage Optimization: Accuracy Analysis and a Case Study from Optimal Consumption

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