Numerical minimization methods for convex functionals dependent on probability measures with applications to optimal pollution monitoring

DOI10.1007/BF01070369zbMath0754.65060MaRDI QIDQ4007328

A. A. Gajvoronskij

Publication date: 27 September 1992

Published in: Cybernetics (Search for Journal in Brave)

zbMATH Keywords

stochastic programmingconvex programminggradient projection methodconvex functionalsoptimal experiment designoptimal parameter estimationair pollution monitoring

Mathematics Subject Classification ID

Optimal statistical designs (62K05) Numerical mathematical programming methods (65K05) Convex programming (90C25) Stochastic programming (90C15) Classical flows, reactions, etc. in chemistry (92E20)

Cites Work

• Sensors and controllers location in distributed systems - A survey
• Stochastic approximation methods for constrained and unconstrained systems
• Optimum Designs in Regression Problems
• The Gradient Projection Method for Nonlinear Programming. Part I. Linear Constraints
• Linearization methods for optimization of functionals which depend on probability measures
• Sufficient conditions for extremum, penalty functions and regularity
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