A hierarchical approach to state space constrained optimization problems

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Abstract
A class of hierarchical prediction-type methods for solving state space constrained optimization problems is studied. The approach is a generalization of the balance-type methods suggested by the authors in earlier papers, where the state space constrained optimization problem was converted into a two-level problem with control constrained first-level problems by using the multiplier method of Hestenes. The use of a prediction-type approach allows simpler first-level optimization problems via decomposition and/or simplification of the constraints.