This paper studies necessary conditions of weak efficiency of a constrained vector minimization problem with equality and inequality constraints in real linear spaces. These results are obtained under generalized convexity conditions through new alternative theorems and given in linear operator rules form. We present a relaxed subconvexlikeness and generalized subconvexlikeness, and likewise, d...

We introduce generalized definitions of Peano and Riemann directional derivatives in order to obtain second-order optimality conditions for vector optimization problems involving C 1,1 data. We show that these conditions are stronger than those in literature obtained by means of second-order Clarke subdifferential.

Two approximation algorithms for solving convex vector optimization problems (CVOPs) are provided. Both algorithms solve the CVOP and its geometric dual problem simultaneously. The first algorithm is an extension of Benson’s outer approximation algorithm, and the second one is a dual variant of it. Both algorithms provide an inner as well as an outer approximation of the (upper and lower) image...

Algorithms for the proportional rounding of a nonnegative vector, and for the biproportional rounding of a nonnegative matrix are discussed. Here we view vector and matrix rounding as special instances of a generic optimization problem that employs an additive version of the objective function of Gaffke and Pukelsheim (2007). The generic problem turns out to be a separable convex integer optimi...

The concept of d−invexity for functions defined on Riemannian manifolds is introduced. Then, this notion is used to obtain optimality conditions for vector optimization problems on Riemannian manifolds. M.S.C. 2010: 58E17, 90C26.

In this paper, a parametric simplex algorithm for solving linear vector optimization problems (LVOPs) is presented. This algorithm can be seen as a variant of the multi-objective simplex (Evans-Steuer) algorithm [12]. Different from it, the proposed algorithm works in the parameter space and does not aim to find the set of all efficient solutions. Instead, it finds a solution in the sense of Lö...

Using the additive weight method of vector optimization problems and the method of essential solutions, we study some continuity properties of the mapping which associates the set of efficient solutions S(f ) to the objective function f . To understand such properties, the key point is to consider the stability of additive weight solutions and the relationship between efficient solutions and ad...

This paper is concerned with generalized second-order contingent epiderivatives of frontier and solution maps in parametric vector optimization problems. Under some mild conditions, we obtain some formulas for computing generalized second-order contingent epiderivatives of frontier and solution maps, respectively. We also give some examples to illustrate the corresponding results.

A sequential optimality condition characterizing the efficient solution without any constraint qualification for an abstract convex vector optimization problem is given in sequential forms using subdifferentials and 2-subdifferentials. Another sequential condition involving only the subdifferentials, but at nearby points to the efficient solution for constraints, is also derived. Moreover, we p...

This paper analyzes the influence of different parameters of Support Vector Machine (SVM) on text categorization performance. The research is carried out on different text collections and different subject headings (up to 1168 items). We show that parameter optimization can essentially increase text categorization performance. An estimation of range for searching optimal parameter is given. We ...