On a nonlocal metric regularity of nonlinear operators
On constraint qualifications in directionally differentiable multiobjective optimization problems
We consider a multiobjective optimization problem with a feasible set defined by inequality and equality constraints such that all functions are, at least, Dini differentiable (in some cases, Hadamard differentiable and sometimes, quasiconvex). Several constraint qualifications are given in such a way that generalize both the qualifications introduced by Maeda and the classical ones, when the functions are differentiable. The relationships between them are analyzed. Finally, we give several Kuhn-Tucker...
On constraint qualifications in directionally differentiable multiobjective optimization problems
We consider a multiobjective optimization problem with a feasible set defined by inequality and equality constraints such that all functions are, at least, Dini differentiable (in some cases, Hadamard differentiable and sometimes, quasiconvex). Several constraint qualifications are given in such a way that generalize both the qualifications introduced by Maeda and the classical ones, when the functions are differentiable. The relationships between them are analyzed. Finally, we give several Kuhn-Tucker...
On dual vector optimization and shadow prices
In this paper we present the image space analysis, based on a general separation scheme, with the aim of studying lagrangian duality and shadow prices in Vector Optimization. Two particular kinds of separation are considered; in the linear case, each of them is applied to the study of sensitivity analysis, and it is proved that the derivatives of the perturbation function can be expressed in terms of vector Lagrange multipliers or shadow prices.
On dual vector optimization and shadow prices
In this paper we present the image space analysis, based on a general separation scheme, with the aim of studying Lagrangian duality and shadow prices in Vector Optimization. Two particular kinds of separation are considered; in the linear case, each of them is applied to the study of sensitivity analysis, and it is proved that the derivatives of the perturbation function can be expressed in terms of vector Lagrange multipliers or shadow prices.
On Duality for Nonsmooth Lipschitz Optimization Problems
On generalized derivatives for vector optimization problems.
On generalized monotone multifunctions with applications to optimality conditions in generalized convex programming.
On semidefinite bounds for maximization of a non-convex quadratic objective over the l1 unit ball
We consider the non-convex quadratic maximization problem subject to the l1 unit ball constraint. The nature of the l1 norm structure makes this problem extremely hard to analyze, and as a consequence, the same difficulties are encountered when trying to build suitable approximations for this problem by some tractable convex counterpart formulations. We explore some properties of this problem, derive SDP-like relaxations and raise open questions.
On the extrema of integrable functions.
Optimal control from inoculation on a continuous microalgae culture
The present work is centred on the problem of biomass productivity optimization of a culture of microalgae Spirulina maxima. The mathematical tools consisted of necessary and sufficient conditions for optimal control coming from the celebrated Pontryagin's Maximum Principle (PMP) as well as the Bellman's Principle of Optimality, respectively. It is shown that the optimal dilution rate turns to be a bang-singular-bang control. It turns out that, the experimental results are in accordance to the optimal...
Optimality and Duality for a Class of Nondifferentiable Minimax Fractional Programming Problems
Optimality and duality in nonsmooth multiobjective optimization involving V-type I invex functions.
Optimality conditions and duality in nonsmooth multiobjective programs.
Optimality conditions for a class of mathematical programs with equilibrium constraints: strongly regular case
The paper deals with mathematical programs, where parameter-dependent nonlinear complementarity problems arise as side constraints. Using the generalized differential calculus for nonsmooth and set-valued mappings due to B. Mordukhovich, we compute the so-called coderivative of the map assigning the parameter the (set of) solutions to the respective complementarity problem. This enables, in particular, to derive useful 1st-order necessary optimality conditions, provided the complementarity problem...
Optimality conditions for approximate solutions in multiobjective optimization problems.
Optimality conditions for weak efficiency to vector optimization problems with composed convex functions
We consider a convex optimization problem with a vector valued function as objective function and convex cone inequality constraints. We suppose that each entry of the objective function is the composition of some convex functions. Our aim is to provide necessary and sufficient conditions for the weakly efficient solutions of this vector problem. Moreover, a multiobjective dual treatment is given and weak and strong duality assertions are proved.
Optimality conditions in nondifferentiable -invex multiobjective programming.
Optimality criteria for deterministic discrete-time infinite horizon optimization.
Optimization analysis involving set functions.