Considering a vector optimization problem to which properly efficient solutions are defined by using convex cone-monotone scalarization functions, we attach to it, by means of perturbation theory, new vector duals. When the primal problem, the scalarization function and the perturbation function are particularized, different dual vector problems are obtained, some of them already known in the l...

The authors provide a model for dynamical scalarization, beyond the adiabatic approximation, using effective field theory techniques, demonstrating that inclusion of post-adiabatic corrections is crucial. agnostic, i.e., independent specific gravity and can therefore be used even alternative theories.

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A numerical method is proposed for constructing an approximation of the Pareto front of nonconvex multi-objective optimal control problems. First, a suitable scalarization technique is employed for the multi-objective optimal control problem. Then by using a grid of scalarization parameter values, i.e., a grid of weights, a sequence of single-objective optimal control problems are solved to obt...

In the current work, we have formulated the optimal bit-allocation problem for a scalable codec of images or videos as a constrained vector-valued optimization problem and demonstrated that there can be many optimal solutions, called Pareto optimal points. In practice, the Pareto points are derived via the weighted sum scalarization approach. An important question which arises is whether all th...

In this paper we consider a vector optimization problem; we present some scalarization techniques for finding all the vector optimal points of this problem and we discuss the relationships between these methods. Moreover, in the linear case, the study of dual variables is carried on by means of sensitivity analysis and also by a parametric approach. We also give an interpretation of the dual va...

In this paper we extend naturally the scalarization proximal point method to solve multiobjective unconstrained minimization problems, proposed by Apolinario et al.[1], from Euclidean spaces to Hadamard manifolds for locally Lipschitz and quasiconvex vector objective functions. Moreover, we present a convergence analysis, under some mild assumptions on the multiobjective function, for two inexa...

Marcelo Salgado, Daniel Sudarsky Instituto de Ciencias Nucleares Universidad Nacional Autónoma de México Apdo. Postal 70-543 México 04510 D.F, México and Ulises Nucamendi Departamento de F́ısica Centro de Investigación y de Estudios Avanzados del I.P.N. A. P. 14-741, México, D. F. 07000, México. Abstract We study in the physical frame the phenomenon of spontaneous scalarization that occurs in sc...

This is an overview of a few possibilities that are open by model theory in applied mathematics. The most attention is paid to the present state and frontiers of the Cauchy method of majorants, approximation of operator equations with finite-dimensional analogs, and the Lagrange multiplier principle in multiobjective decision making. DOI: 10.1134/S1990478909010116 The union of functional analys...

Abstarct: The conventional equilibria problem found in many economics and network models is based on a scalar cost, or a single objective. Recently, equilibria problems based on a vector cost, or multicriteria, have received considerable attention. In this paper, we study a scalarization method for analyzing network equilibria problems with vector-valued cost function. The method is based on th...