On generalized cyclically monotone operators and proper quasimonotonictty

In this paper we consider an abstract subdifferential that fulfills a prioria weak type of a mean value property. We survey and extend some recent results connecting the gener-alized convexity of nonsmooth functions with the generalized cyclic monotonidty of their subdifferentials. It is shown that, for a large class of subdifferentials, a Isc function is quasiconvex if and only if its subdifferential is a cyclically quasimonotone operator. An analogous property holds for pseudoconvexity. It is also shown that the subdiffer-ential of a quasiconvex function is properly quasimonotone. This property is slightly stronger than quasimonotonicity, and is more useful in applications connected with variational inequalities     

Approximate convexity and submonotonicity

It is shown that a locally Lipschitz function is approximately convex if, and only if, its Clarke subdifferential is a submonotone operator. Consequently, in finite dimensions, the class of locally Lipschitz approximately convex functions coincides with the class of lower-C¹ functions. Directional approximate convexity is introduced and shown to be a natural extension of the class of lower-C¹ functions in infinite dimensions. The following characterization is established: a multivalued operator is maximal cyclically submonotone if, and only if, it coincides with the Clarke subdifferential of a locally Lipschitz directionally approximately convex function, which is unique up to a constant. Furthermore, it is shown that in Asplund spaces, every regular function is generically approximately convex.     

Generalized gradients of monotone type

We examine the properties of the subdifferential in the sense of Clarke of certain locally Lipschitz, quasi-convex functions. We prove that, even if they may not possess a pseudomonotone-type subdifferential, if we consider the operator A+∂f, where A is an operator of type (S)₊, then the sum is pseudomonotone. A new type of subdifferential for Lipschitz functions is also presented. We prove some calculus rules and we establish that in the context of reflexive Banach spaces is an operator of type (M).     

Controllability and strong controllability of differential inclusions

In this paper, we prove sufficient conditions for controllability and strong controllability in terms of the Mordukhovich subdifferential for two classes of differential inclusions. The first one is the class of sub-Lipschitz multivalued functions introduced by Loewen-Rockafellar (1994) [10]. The second one, introduced recently by Clarke (2005) [18], is the class of multivalued functions which are pseudo-Lipschitz and satisfy the so-called tempered growth condition. To do this, we establish an error bound result in terms of the Mordukhovich subdifferential outside Asplund spaces.     

Prox-Regularity of Functions and Sets in Banach Spaces

In this paper, we define the prox-regularity for functions on Banach spaces by adapting the original definition in R ⁿ . In this context, we establish a subdifferential characterization and show that qualified convexly C ^1,+-composite functions and primal lower nice functions belong to this class, as already known in the setting of Hilbert spaces. We also study, in a geometrical point of view, the epigraphs of prox-regular functions. The subdifferential characterization allows us to show that some Moreau-envelope-like regularizations of such functions are of class C ¹ in the context of certain uniformly convex spaces.     

Abstract convexity of extended real-valued ICR functions

The theory of non-negative increasing and co-radiant (ICR) functions defined on ordered topological vector spaces has been well developed. In this article, we present the theory of extended real-valued ICR functions defined on an ordered topological vector space X. We first give a characterization for non-positive ICR functions and examine abstract convexity of this class of functions. We also investigate polar function and subdifferential of these functions. Finally, we characterize abstract convexity, support set and subdifferential of extended real-valued ICR functions.     

New Formulas for the Fenchel Subdifferential of the Conjugate Function

Following (López and Volle, J Convex Anal 17, 2010) we provide new formulas for the Fenchel subdifferential of the conjugate of functions defined on locally convex spaces. In particular, this allows deriving expressions for the minimizers set of the lower semicontinuous convex hull of such functions. These formulas are written by means of primal objects related to the subdifferential of the initial function, namely a new enlargement of the Fenchel subdifferential operator.     

Almost everywhere convex functions on R n and weak derivatives

The classical subdifferential calculus is a useful tool in order to establish characterizations of convex functions and optimality conditions; but it becomes useless when one thinks to study almost everywhere convex functions. In this paper by using Sobolev space theory we give some characterizations of this class of functions.     

A new representation of a proximal subdifferential by employing a directional derivative

In this paper, a new representation of the proximal subdifferential of a nonsmooth function is presented by using a directional derivative. The upper-semicontinuity property of the proximal subdifferential is proved via the new representation. The existence and necessary conditions of an optimal solution for a class of inf-convolution functions are obtained by using the proximal subdifferential. Finally, a relationship between the proximal subdifferential and the quasidifferential is established. Based on the relation, the proximal subdifferential can be computed easily when the quasidifferential is a polytope.     

Subdifferential estimate of the directional derivative,optimality criterion and separation principles

We provide an inequality relating the radial directional derivative and the subdifferential of proper lower semicontinuous functions, which extends the known formula for convex functions. We show that this property is equivalent to other subdifferential properties of Banach spaces, such as controlled dense subdifferentiability, optimality criterion, mean value inequality and separation principles. As an application, we obtain a first-order sufficient condition for optimality, which extends the known condition for differentiable functions in finite-dimensional spaces and which amounts to the maximal monotonicity of the subdifferential for convex lower semicontinuous functions. Finally, we establish a formula describing the subdifferential of the sum of a convex lower semicontinuous function with a convex inf-compact function in terms of the sum of their approximate ?-subdifferentials. Such a formula directly leads to the known formula relating the directional derivative of a convex lower semicontinuous function to its approximate ?-subdifferential.     

Mean-Value Theorem with Small Subdifferentials

We prove a mean-value theorem for lower semicontinuous functions on a large class of Banach spaces which contains the class of Asplund spaces, in particular reflexive Banach spaces and Banach spaces with a separable dual. It involves the lower subdifferential (or contingent subdifferential) and the Fréchet subdifferentials, which are among the smallest subdifferentials known to date. It follows that the estimates which it provides require weak assumptions and are accurate. When the function is locally Lipschitzian, we get a simple statement which refines the Lebourg mean-value theorem.     

Variational Subdifferential for Quasiconvex Functions

It is shown that a convenient subdifferential for the class of quasiconvex functions is variational. This property combines a variational principle with a kind of weak fuzzy sum rule. It entails a number of useful properties. The subdifferential considered here is the lower subdifferential at the origin (in the sense of Plastria) of the incident derivative or inner epiderivative of the function.     

Lagrange multiplier rules for non-differentiable DC generalized semi-infinite programming problems

This paper aims to study a broad class of generalized semi-infinite programming problems with (upper and lower level) objectives given as the difference of two convex functions, and (lower level) constraints described by a finite number of convex inequalities and a set constraints. First, we are interested in some various lower level constraint qualifications for the problem. Then, the results are used to establish efficient upper estimate of certain subdifferential of value functions. Finally, we apply the obtained subdifferential estimates to derive necessary optimality conditions for the problem.     

Radiant Separation Theorems and Minimum-Type Subdifferentials of Calm Functions

Applying minimum-type functions and plus-cogauges, we construct a closed, convex cone in order to separate a boundary point of a radiant set from its interior. Abstract convexity of positively homogeneous functions is studied as well. Since a locally Lipschitz function is degree-one calm, the class of degree-one calm functions is large. We study degree-one calm functions and investigate how these functions can be generated by a class of min-type functions. Then, we derive a method to find an element of the subdifferential of a non-negative, lower semicontinuous and degree-one calm function with respect to the class of min-type functions.     

Abstract convexity of topical functions

In this paper, we examine properties of topical (increasing and plus-homogeneous) functions defined on a normed linear space ${X}$ . We also study many results of abstract convexity such as support set, polarity and subdifferential set of these functions. Finally, we give a characterization for topical functions with respect to closed downward sets.     

Calculus rules for global approximate minima and applications to approximate subdifferential calculus

We provide calculus rules for global approximate minima concerning usual operations on functions. The formulas we obtain are then applied to approximate subdifferential calculus. In this way, new results are presented, for example on the approximate subdifferential of a deconvolution, or on the subdifferential of an upper envelope of convex functions.     

A Fritz John optimality condition using the approximate subdifferential

A Fritz John type first-order optimality condition is derived for infinite-dimensional programming problems involving the approximate subdifferential. A discussion of the important properties of the approximate subdifferential for locally Lipschitz functions is included. In addition, an upper semicontinuity condition is obtained for an approximate subdifferential multifunction related to the class of locally compactly Lipschitzian mappings.The authors would like to thank two anonymous referees for their detailed comments which have significantly improved the presentation of this paper. In particular, they thank the first referee for pointing out a number of important references on the approximate subdifferential and the second referee for various corrections and for bringing an important recent reference (Ref. 17) to their attention.     

Nonsmooth Analysis of Singular Values. Part I: Theory

The singular values of a rectangular matrix are nonsmooth functions of its entries. In this work we study the nonsmooth analysis of functions of singular values. In particular we give simple formulae for the regular subdifferential, the limiting subdifferential, and the horizon subdifferential, of such functions. Along the way to the main result we give several applications and in particular derive von Neumann’s trace inequality for singular values. Mathematics Subject Classifications (2000) Primary 90C31, 15A18; secondary 49K40, 26B05.Research supported by NSERC.     

Subdifferential of the supremum function: moving back and forth between continuous and non-continuous settings

In this paper we establish general formulas for the subdifferential of the pointwise supremum of convex functions, which cover and unify both the compact continuous and the non-compact non-continuous settings. From the non-continuous to the continuous setting, we proceed by a compactification-based approach which leads us to problems having compact index sets and upper semi-continuously indexed mappings, giving rise to new characterizations of the subdifferential of the supremum by means of upper semicontinuous regularized functions and an enlarged compact index set. In the opposite sense, we rewrite the subdifferential of these new regularized functions by using the original data, also leading us to new results on the subdifferential of the supremum. We give two applications in the last section, the first one concerning the nonconvex Fenchel duality, and the second one establishing Fritz-John and KKT conditions in convex semi-infinite programming.

     

Subdifferential set of the supremum of lower semi-continuous convex functions and the conical hull intersection property

In this paper we give some characterizations for the subdifferential set of the supremum of an arbitrary (possibly infinite) family of proper lower semi-continuous convex functions. This is achieved by means of formulae depending exclusively on the (exact) subdifferential sets and the normal cones to the domains of the involved functions. Our approach makes use of the concept of conical hull intersection property (CHIP, for short). It allows us to establish sufficient conditions guarantying explicit representations for this subdifferential set at any point of the effective domain of the supremum function. Research supported by grant SB2003-0344 of SEUI (MEC), Spain.