Now showing items 1-10 of 764
Free time and mixed constrained optimal control problems
We consider free time optimal control problems with pointwise set control constraints u(t) ∈ U(t). Here we derive necessary conditions of optimality for those problem where the set U(t) is defined by equality and inequality ...
ON THE RESOLUTION OF LINEARLY CONSTRAINED CONVEX MINIMIZATION PROBLEMS
(Siam PublicationsPhiladelphia, 1994)
A maximum principle for constrained infinite horizon dynamic control systems
This article presents and discusses a maximum principle for infinite horizon constrained optimal control problems with a cost functional depending on the state at the final time. The main feature of these optimality ...
Necessary optimality conditions for interval optimization problems with inequality constraints using constrained interval arithmetic
This article is devoted to obtaining necessary optimality conditions for optimization problems with interval-valued objective and interval inequality constraints. These objective and constraint functions are obtained from ...
Optimal reactive power dispatch using stochastic chance-constrained programming
Deterministic Optimal Reactive Power Dispatch problem has been extensively studied, such that the demand power and the availability of shunt reactive power compensators are known and fixed. Give this background, a two-stage ...
Partial spectral projected gradient method with active-set strategy for linearly constrained optimization
A method for linearly constrained optimization which modifies and generalizes recent box-constraint optimization algorithms is introduced. The new algorithm is based on a relaxed form of Spectral Projected Gradient iterations. ...
Bound constrained smooth optimization for solving variational inequalities and related problems
Variational inequalities and related problems may be solved via smooth bound constrained optimization. A comprehensive discussion of the important features involved with this strategy is presented. Complementarity problems ...
From convex feasibility to convex constrained optimization using block action projection methods and underrelaxation