Optimization on directionally convex sets

Directional convexity generalizes the concept of classical convexity. We investigate OC-convexity generated by the intersections of C-semispaces that efficiently approximates directional convexity. We consider the following optimization problem in case of the direction set of OC-convexity being infinite. Given a compact OC-convex set A, maximize a linear form L subject to A. We prove that there exists an OC-extreme solution of the problem. We introduce the notion of OC-quasiconvex function. Ii is shown that if O is finite then the constrained maximum of an OC-quasiconvex function on the set A is attained at an OC-extreme point of A. We show that the OC-convex hull of a finite point set represents the union of a finite set of polytopes in case of the direction set being finite.     

Canonical and monophonic convexities in hypergraphs

Known properties of “canonical connections” from database theory and of “closed sets” from statistics implicitly define a hypergraph convexity, here called canonical convexity (c-convexity), and provide an efficient algorithm to compute c-convex hulls. We characterize the class of hypergraphs in which c-convexity enjoys the Minkowski-Krein-Milman property. Moreover, we compare c-convexity with the natural extension to hypergraphs of monophonic convexity (or m-convexity), and prove that: (1) m-convexity is coarser than c-convexity, (2) m-convexity and c-convexity are equivalent in conformal hypergraphs, and (3) m-convex hulls can be computed in the same efficient way as c-convex hulls.     

New integral representations of nth order convex functions

In this paper we give an integral representation of an n-convex function f in general case without additional assumptions on function f. We prove that any n-convex function can be represented as a sum of two (n+1)-times monotone functions and a polynomial of degree at most n. We obtain a decomposition of n-Wright-convex functions which generalizes and complements results of Maksa and Páles (2009) [13]. We define and study relative n-convexity of n-convex functions. We introduce a measure of n-convexity of f. We give a characterization of relative n-convexity in terms of this measure, as well as in terms of nth order distributional derivatives and Radon-Nikodym derivatives. We define, study and give a characterization of strong n-convexity of an n-convex function f in terms of its derivative f(n+1)(x) (which exists a.e.) without additional assumptions on differentiability of f. We prove that for any two n-convex functions f and g, such that f is n-convex with respect to g, the function g is the support for the function f in the sense introduced by W?sowicz (2007) [29], up to polynomial of degree at most n.     

2-Coherent and 2-convex conditional lower previsions

In this paper we explore relaxations of (Williams) coherent and convex conditional previsions that form the families of n-coherent and n-convex conditional previsions, at the varying of n. We investigate which such previsions are the most general one may reasonably consider, suggesting (centered) 2-convex or, if positive homogeneity and conjugacy is needed, 2-coherent lower previsions. Basic properties of these previsions are studied. In particular, we prove that they satisfy the Generalised Bayes Rule and always have a 2-convex or, respectively, 2-coherent natural extension. The role of these extensions is analogous to that of the natural extension for coherent lower previsions. On the contrary, n-convex and n-coherent previsions with $n\ge 3$ either are convex or coherent themselves or have no extension of the same type on large enough sets. Among the uncertainty concepts that can be modelled by 2-convexity, we discuss generalisations of capacities and niveloids to a conditional framework and show that the well-known risk measure Value-at-Risk only guarantees to be centered 2-convex. In the final part, we determine the rationality requirements of 2-convexity and 2-coherence from a desirability perspective, emphasising how they weaken those of (Williams) coherence.     

On the space of B-convex compacta

We investigate topology of the space of B-convex compacta of finite-dimensional Banach space (the notion of B-convexity space was introduced by M. Lassak). An answer to the question of M. van de Vel about a characterization of continuity of the closed B-convex hull is given. We prove that the space of B-convex compacta is a Q-manifold iff the map of the closed B-convex hull is continuous.     

Convex Partitions of Graphs

A set of vertices S of a graph G is convex if all vertices of every geodesic between two of its vertices are in S. We say that G is k-convex if V(G) can be partitioned into k convex sets. The convex partition number of G is the least k ⩾ 2 for which G is k-convex. In this paper we examine k-convexity of graphs. We show that it is NP-complete to decide if G is k-convex, for any fixed k ⩾ 2. We describe a characterization for k-convex cographs, leading to a polynomial time algorithm to recognize if a cograph is k-convex. Finally, we discuss k-convexity for disconnected graphs.     

Complex convexity and monotonicity in quasi-Banach lattices

In this paper we study the monotonicity and convexity properties in quasi-Banach lattices. We establish relationship between uniform monotonicity, uniform ?-convexity, H-and PL-convexity. We show that if the quasi-Banach lattice E has α-convexity constant one for some 0 < α < ∞, then the following are equivalent: (i) E is uniformly PL-convex; (ii) E is uniformly monotone; and (iii) E is uniformly ?-convex. In particular, it is shown that if E has α-convexity constant one for some 0 < α < ∞ and if E is uniformly ?-convex of power type then it is uniformly H-convex of power type. The relations between concavity, convexity and monotonicity are also shown so that the Maurey-Pisier type theorem in a quasi-Banach lattice is proved.Finally we study the lifting property of uniform PL-convexity: if E is a quasi-Köthe function space with α-convexity constant one and X is a continuously quasi-normed space, then it is shown that the quasi-normed Köthe-Bochner function space E(X) is uniformly PL-convex if and only if both E and X are uniformly PL-convex.     

q-subharmonicity and q-convex domains in ℂ n

In this paper we study q-subharmonic and q-plurisubharmonic functions in ? ⁿ . Next as an application, we give the notion of q-convex domains in ? ⁿ which is an extension of weakly q-convex domains introduced and investigated in [10]. In the end of the paper we show that the q-convexity is the local property and give some examples about q-convex domains.     

Cesàro matrix and (1, 1; r)-convex sequences

Positivity - This paper deals with (1,&nbsp;1;&nbsp;r)-convexity of sequences. First, we prove several results on the sets of (1,&nbsp;1;&nbsp;r)-convex sequences for various values...     

Regularizations in abelian complete ordered groups

Notions about Φ-convexity are extended to abelian complete partially ordered group-valued mappings in an attempt to unify in a general theory notions of Φ-convex sets and Φ-convex mappings. We obtain some group specific results and particularly a characterization of support functions.     

Algorithmic and structural aspects of the P 3-Radon number

The generalization of classical results about convex sets in ? ⁿ to abstract convexity spaces, defined by sets of paths in graphs, leads to many challenging structural and algorithmic problems. Here we study the Radon number for the P ₃-convexity on graphs. P ₃-convexity has been proposed in connection with rumour and disease spreading processes in networks and the Radon number allows generalizations of Radon’s classical convexity result. We establish hardness results and describe efficient algorithms for trees.     

Characterization of vector strict global minimizers of order 2 in differentiable vector optimization problems under a new approximation method

In this paper, a new approximation method is introduced to characterize a so-called vector strict global minimizer of order 2 for a class of nonlinear differentiable multiobjective programming problems with (F,ρ)-convex functions of order 2. In this method, an equivalent vector optimization problem is constructed by a modification of both the objectives and the constraint functions in the original multiobjective programming problem at the given feasible point. In order to prove the equivalence between the original multiobjective programming problem and its associated F-approximated vector optimization problem, the suitable (F,ρ)-convexity of order 2 assumption is imposed on the functions constituting the considered vector optimization problem.     

Saddle points and Lagrangian-type duality for discrete minmax fractional subset programming problems with generalized convex functions

In this paper we present four sets of saddle-point-type optimality conditions, construct two Lagrangian-type dual problems, and prove weak and strong duality theorems for a discrete minmax fractional subset programming problem. We establish these optimality and duality results under appropriate (b,?,ρ,θ)-convexity hypotheses.     

Sweeping by a continuous prox-regular set

The evolution problem known as sweeping process is considered for a class of nonconvex sets called prox-regular (or ?-convex). Assuming, essentially, that such sets contain in the interior a suitable subset and move continuously (w.r.t. the Hausdorff distance), we prove local and global existence as well as uniqueness of solutions, which are continuous functions with bounded variation. Some examples are presented.     

Convexity conditions and normal structure of Banach spaces

We prove that F-convexity, the property dual to P-convexity of Kottman, implies uniform normal structure. Moreover, in the presence of the WORTH property, normal structure follows from a weaker convexity condition than F-convexity. The latter result improves the known fact that every uniformly nonsquare space with the WORTH property has normal structure.     

On second-order duality for a class of nondifferentiable minimax fractional programming problem with (C,α,ρ,d)-convexity

In this paper, we derive appropriate duality theorems for three second-order dual models of a nondifferentiable minimax fractional programming problem under second-order (C,α,ρ,d)-convexity assumptions. A nontrivial example has also been exemplified to show the existence of second-order (C,α,ρ,d)-convex functions. Several known results including many recent works are obtained as special cases.     

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.     

On the James constant and B-convexity of Cesàro and Cesàro-Orlicz sequence spaces

The classical James constant and the nth James constants, which are measure of B-convexity for the Cesàro sequence spaces cesp and the Cesàro-Orlicz sequence spaces cesM, are calculated. These investigations show that cesp,cesM are not uniformly non-square and even they are not B-convex. Therefore the classical Cesàro sequence spaces cesp are natural examples of reflexive spaces which are not B-convex. Moreover, the James constant for the two-dimensional Cesàro space is calculated.