Treatment of set order relations by means of a nonlinear scalarization functional: a full characterization

In this paper, we show how a nonlinear scalarization functional can be used in order to characterize several well-known set order relations and which thus plays a key role in set optimization. By means of this functional, we derive characterizations for minimal elements of set-valued optimization problems using a set approach. Our methods do not rely on any convexity assumptions on the considered sets. Furthermore, we develop a derivative-free descent method for set optimization problems without convexity assumptions to verify the usefulness of our results.     

Convexity with respect to a differential equation

The concepts of convexity of a set, convexity of a function and monotonicity of an operator with respect to a second-order ordinary differential equation are introduced in this paper. Several well-known properties of usual convexity are derived in this context, in particular, a characterization of convexity of function and monotonicity of an operator. A sufficient optimality condition for a optimization problem is obtained as an application. A number of examples of convex sets, convex functions and monotone operators with respect to a differential equation are presented.     

Investigation of smoothness conditions on the boundary for the strong linear convexity of a domain

We construct a counterexample for the hypothesis that the strong linear convexity of a domain follows from the linear convexity if the set of singularities does not split the boundary. Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 51, No. 12, pp. 1710–1713, December, 1999.     

A characterization of convex games by means of bargaining sets

The aim of the paper is to characterize the classical convexity notion for cooperative TU games by means of the Mas-Colell and the Davis–Maschler bargaining sets. A new set of payoff vectors is introduced and analyzed: the max-Weber set. This set is defined as the convex hull of the max-marginal worth vectors. The characterizations of convexity are reached by comparing the classical Weber set, the max-Weber set and a selected bargaining set.     

The Forcing Convexity Number of a Graph

For two vertices u and v of a connected graph G, the set I(u,v) consists of all those vertices lying on a u-v geodesic in G. For a set S of vertices of G, the union of all sets I(u,v) for u, v S is denoted by I(S). A set S is a convex set if I(S) = S. The convexity number con(G) of G is the maximum cardinality of a proper convex set of G. A convex set S in G with |S| = con(G) is called a maximum convex set. A subset T of a maximum convex set S of a connected graph G is called a forcing subset for S if S is the unique maximum convex set containing T. The forcing convexity number f(S, con) of S is the minimum cardinality among the forcing subsets for S, and the forcing convexity number f(G, con) of G is the minimum forcing convexity number among all maximum convex sets of G. The forcing convexity numbers of several classes of graphs are presented, including complete bipartite graphs, trees, and cycles. For every graph G, f(G, con) con(G). It is shown that every pair a, b of integers with 0 a b and b is realizable as the forcing convexity number and convexity number, respectively, of some connected graph. The forcing convexity number of the Cartesian product of H × K ₂ for a nontrivial connected graph H is studied.     

Strong Restricted-Orientation Convexity

Strong restricted-orientation convexity is a generalization of standard convexity. We explore the properties of strongly convex sets in multidimensional Euclidean space and identify major properties of standard convex sets that also hold for strong convexity. We characterize strongly convex flats and halfspaces, and establish the strong convexity of the affine hull of a strongly convex set. We then show that, for every point in the boundary of a strongly convex set, there is a supporting strongly convex hyperplane through it. Finally, we show that a closed set with nonempty interior is strongly convex if and only if it is the intersection of strongly convex halfspaces; we state a condition under which this result extends to sets with empty interior.     

On the convexity of integrals of multivalued mappings: Applications in control theory

Using the notion of the local convexity index, we characterize in a quantitative way the local convexity of a set in then-dimensional Euclidean space, defined by an integral of a multivalued mapping. We estimate the rate of convergence of the conditional gradient method for solving an abstract optimization problem by means of the convexity index of the constraining set at the solution point. These results are applied to the qualitative analysis of the solutions of time-optimal and Mayer problems for linear control systems, as well as for estimating the convergence rate of algorithms solving these problems.     

On multiple objective programming problems with set functions

The convexity of a subset of a σ-algebra and the convexity of a set function on a convex subset are defined. Related properties are also examined. A Farkas-Minkowski theorem for set functions is then proved. These results are used to characterize properly efficient solutions for multiple objective programming problems with set functions by associated scalar problems.     

Convexity of the Solution Set of a Pseudoconvex Inequality in Riemannian Manifolds

Some equivalent conditions for convexity of the solution set of a pseudoconvex inequality are presented. These conditions turn out to be very useful in characterizing the solution sets of optimization problems of pseudoconvex functions defined on Riemannian manifold.     

Optimal constrained selection of a measurable subset

Necessary and sufficient conditions are given for a class of optimization problems involving optimal selection of a measurable subset from a given measure space subject to set function inequality constraints. Results are developed firstly for the case where the set functions involved possess a differentiability property and secondly where a type of convexity is present. These results are then used to develop numerical methods. It is shown that in a special case the optimal set can be obtained via solution of a fixed point problem in Euclidean space.     

一致凸度量线性空间的自反性及其应用

为研究度量线性空间中凸集的逼近性质，Ｇ．Ｃ．Ａｈｕｊａ等引起了度量线性空间的严格凸性及一致凸性的定义。本文证明了完备的一致凸的度量线性空间是自反的。同时，作为应用，研究了最佳联合逼近元的存在性与唯一性问题。     

Necessary optimality criteria in mathematical programming in the presence of differentiability

We consider the problem of minimizing a function over a region defined by an arbitrary set, equality constraints, and constraints of the inequality type defined via a convex cone. Under some moderate convexity assumptions on the arbitrary set we develop Optimality criteria of the minimum principle type which generalize the Fritz John Optimality conditions. As a consequence of this result necessary Optimality criteria of the saddle point type drop out. Here convexity requirements on the functions are relaxed to convexity at the point under investigation. We then present the weakest possible constraint qualification which insures positivity of the lagrangian multiplier corresponding to the objective function.     

Book review of Israel Gohberg,Seymour Goldberg,Marinus A. Kaashoek,Basic Classes of Linear Operators,Birkhäuser Verlag,Basel–Boston–Berlin 2003, 423 p. ISBN 3-7643-6930-2

In projective space three notions of convexity (weak convexity, strong convexity, p-convexity) are regarded systematically. Since these notions are defined only by incidence relations, there can be introduced dual notions. We consider relations.between the introduced notions and the most essential properties of convex sets. To all assertions. can be formulated dual assertions, too. The most important theorems given by Fenchel can be generalised. The property of a point set (a set of hyperplanes) to be strongly convex or p-convex, respectively, is invariant with respect to correlations.     

DEA with efficiency classification preserving conditional convexity

We propose to relax the standard convexity property used in Data Envelopment Analysis (DEA) by imposing additional qualifications for feasibility of convex combinations. We specifically focus on a condition that preserves the Koopmans efficiency classification. This yields an efficiency classification preserving conditional convexity property, which is implied by both monotonicity and convexity, but not conversely. Substituting convexity by conditional convexity, we construct various empirical DEA approximations as the minimal sets that contain all DMUs and are consistent with the imposed production assumptions. Imposing an additional disjunctive constraint to standard convex DEA formulations can enforce conditional convexity. Computation of efficiency measures relative to conditionally convex production set can be performed through Disjunctive Programming (DP).     

Convexity of chance constrained programming problems with respect to a new generalized concavity notion

In this paper, convexity of chance constrained problems have been investigated. A new generalization of convexity concept, named h-concavity, has been introduced and it has been shown that this new concept is the generalization of the ??-concavity. Then, using the new concept, some of the previous results obtained by Shapiro et al. [in Lecture Notes on Stochastic Programming Modeling and Theory, SIAM and MPS, 2009] on properties of ??-concave functions, have been extended. Next the convexity of chance constraints with independent random variables is investigated. It will be shown how concavity properties of the mapping related to the decision vector have to be combined with suitable properties of decrease or increase for the marginal densities in order to arrive at convexity of the feasible set for large enough probability levels and then sufficient conditions for convexity of chance constrained problems which has been introduced by Henrion and Strugarek [in Convexity of chance constraints with independent random variables. Comput. Optim. Appl. 41:263?C276, 2008] has been extended in this paper for a wider class of real functions.     

The convexity of the reachable set for a bilinear controllable system

The reachable of a bilinear controllable system, in which the range of allowed control values is a convex polyhedron, is examined. Sufficient conditions of convexity of the reachable set, which enable the maximum principle to be used in the standard form are found.     

The lattice of convexities of partial monounary algebras

A class of partial monounary algebras is called a convexity if it is closed under homomorphic images, direct products and convex relative subalgebras. We prove that the collection of all convexities of partial monounary algebras forms a countable set. Further, each convexity can be generated by at most two algebras.     

自由支配集下近似平衡约束向量优化问题的稳定性研究

在自由支配集下,对一类近似平衡约束向量优化问题（AOPVF）的稳定性进行研究.首先,在较弱的凸性假设下获得了约束集映射的Berge-半连续性和约束集的闭性、凸性和紧性结果.然后,在目标函数列Gamma-收敛的假设下,分别得到了AOPVF弱有效解映射Berge 半连续和弱有效解集下Painlevé-Kuratowski收敛的充分条件,并给出例子说明结论是新颖和有意义的.     

Relations between the convexity of a set and the differentiability of its support function

It is known that, in finite dimensions, the support function of a compact convex set with nonempty interior is differentiable excepting the origin if and only if the set is strictly convex. In this paper, we realize a thorough study of the relations between the differentiability of the support function on the interior of its domain and the convexity of the set, mainly for unbounded sets. Then, we revisit some results related to the differentiability of the cost function associated to a production function.     

Essential components of the set of weakly Pareto-Nash equilibrium points

In this paper, we first give a generalization of Ky Fan's inequality to vector-valued functions. We prove that, for every vector-valued function (satisfying some continuity and convexity conditions), there exists at least one essential component of the set of its Ky Fan's points. As applications, we show that, for every multiobjective game (satisfying some continuity and convexity conditions), there exists at least one essential component of the set of its weakly Pareto-Nash equilibrium points.