The infinite dimensional Lagrange multiplier rule for convex optimization problems

AbstractIn this paper an infinite dimensional generalized Lagrange multipliers rule for convex optimization problems is presented and necessary and sufficient optimality conditions are given in order to guarantee the strong duality. Furthermore, an application is presented, in particular the existence of Lagrange multipliers associated to the bi-obstacle problem is obtained

Structural optimization of large structural systems by optimality criteria methods

The fundamental concepts of the optimality criteria method of structural optimization are presented. The effect of the separability properties of the objective and constraint functions on the optimality criteria expressions is emphasized. The single constraint case is treated first, followed by the multiple constraint case with a more complex evaluation of the Lagrange multipliers. Examples illustrate the efficiency of the method

Optimal bilinear control problem related to a chemo-repulsion system in 2D domains

In this paper we study a bilinear optimal control problem associated to a chemo-repulsion model with linear production term. We analyze the existence, uniqueness and regularity of pointwise strong solutions in a bidimensional domain. We prove the existence of an optimal solution and, using a Lagrange multipliers theorem, we derive first-order optimality conditions

An extension of Yuan's Lemma and its applications in optimization

We prove an extension of Yuan's Lemma to more than two matrices, as long as the set of matrices has rank at most 2. This is used to generalize the main result of [A. Baccari and A. Trad. On the classical necessary second-order optimality conditions in the presence of equality and inequality constraints. SIAM J. Opt., 15(2):394--408, 2005], where the classical necessary second-order optimality condition is proved under the assumption that the set of Lagrange multipliers is a bounded line segment. We prove the result under the more general assumption that the hessian of the Lagrangian evaluated at the vertices of the Lagrange multiplier set is a matrix set with at most rank 2. We apply the results to prove the classical second-order optimality condition to problems with quadratic constraints and without constant rank of the jacobian matrix

Optimal control of obstacle problems : existence of Lagrange multipliers

We study first order optimality systems for the control of a system governed by a variational inequality and deal with Lagrange multipliers : is it possible to associate to each pointwise constraint a multiplier to get a ``good'' optimality system ? We give positive and negative answers for the finite and infinite dimensional cases. These results are compared with the previous ones got by penalization or differentiation