Relaxed Quasimonotone Operators and Relaxed Quasiconvex Functions

Similar documents
Journal of Inequalities in Pure and Applied Mathematics

1 Introduction The study of the existence of solutions of Variational Inequalities on unbounded domains usually involves the same sufficient assumptio

Pseudomonotone Operators: A Survey of the Theory and Its Applications

Upper sign-continuity for equilibrium problems

On Optimality Conditions for Pseudoconvex Programming in Terms of Dini Subdifferentials

Existence results for quasi-equilibrium problems

arxiv: v1 [math.oc] 21 Mar 2015

On pseudomonotone variational inequalities

SCALARIZATION APPROACHES FOR GENERALIZED VECTOR VARIATIONAL INEQUALITIES

Generalized Monotonicities and Its Applications to the System of General Variational Inequalities

Transformation of Quasiconvex Functions to Eliminate. Local Minima. JOTA manuscript No. (will be inserted by the editor) Suliman Al-Homidan Nicolas

Subdifferential representation of convex functions: refinements and applications

Solution existence of variational inequalities with pseudomonotone operators in the sense of Brézis

A projection-type method for generalized variational inequalities with dual solutions

An Overview of Generalized Convexity

Applied Mathematics Letters

("-1/' .. f/ L) I LOCAL BOUNDEDNESS OF NONLINEAR, MONOTONE OPERA TORS. R. T. Rockafellar. MICHIGAN MATHEMATICAL vol. 16 (1969) pp.

Stability of efficient solutions for semi-infinite vector optimization problems

Journal of Inequalities in Pure and Applied Mathematics

AN ASYMPTOTIC MINTY S TYPE VARIATIONAL INEQUALITY WITH PSEUDOMONOTONE OPERATORS. G. Isac

ON A HYBRID PROXIMAL POINT ALGORITHM IN BANACH SPACES

Exceptional Family of Elements and Solvability of Mixed Variational Inequality Problems

The theory of monotone operators with applications

FIRST ORDER CHARACTERIZATIONS OF PSEUDOCONVEX FUNCTIONS. Vsevolod Ivanov Ivanov

ON GAP FUNCTIONS OF VARIATIONAL INEQUALITY IN A BANACH SPACE. Sangho Kum and Gue Myung Lee. 1. Introduction

CHARACTERIZATION OF (QUASI)CONVEX SET-VALUED MAPS

SOME ELEMENTARY GENERAL PRINCIPLES OF CONVEX ANALYSIS. A. Granas M. Lassonde. 1. Introduction

Remark on a Couple Coincidence Point in Cone Normed Spaces

Epiconvergence and ε-subgradients of Convex Functions

Strong Convergence Theorem by a Hybrid Extragradient-like Approximation Method for Variational Inequalities and Fixed Point Problems

Generalized vector equilibrium problems on Hadamard manifolds

Existence and Approximation of Fixed Points of. Bregman Nonexpansive Operators. Banach Spaces

WEAK CONVERGENCE OF RESOLVENTS OF MAXIMAL MONOTONE OPERATORS AND MOSCO CONVERGENCE

A double projection method for solving variational inequalities without monotonicity

Relationships between upper exhausters and the basic subdifferential in variational analysis

On the Weak Convergence of the Extragradient Method for Solving Pseudo-Monotone Variational Inequalities

Limiting Normal Operator in Quasiconvex Analysis

Journal of Inequalities in Pure and Applied Mathematics

Convergence Theorems of Approximate Proximal Point Algorithm for Zeroes of Maximal Monotone Operators in Hilbert Spaces 1

On Gap Functions for Equilibrium Problems via Fenchel Duality

The Journal of Nonlinear Science and Applications

On Weak Pareto Optimality for Pseudoconvex Nonsmooth Multiobjective Optimization Problems

Geometric Properties and Coincidence Theorems with Applications to Generalized Vector Equilibrium Problems 1

Math 421, Homework #9 Solutions

Research Article Existence and Duality of Generalized ε-vector Equilibrium Problems

(U 2 ayxtyj < (2 ajjxjxj) (2 a^jj),

The local equicontinuity of a maximal monotone operator

Characterizations of Pseudoconvex Functions and Semistrictly Quasiconvex Ones

Brøndsted-Rockafellar property of subdifferentials of prox-bounded functions. Marc Lassonde Université des Antilles et de la Guyane

Sum of two maximal monotone operators in a general Banach space is maximal

SOME REMARKS ON SUBDIFFERENTIABILITY OF CONVEX FUNCTIONS

Continuity and Differentiability of Quasiconvex Functions

arxiv: v2 [math.oc] 17 Jul 2017

Local strong convexity and local Lipschitz continuity of the gradient of convex functions

Convergence theorems for a finite family. of nonspreading and nonexpansive. multivalued mappings and equilibrium. problems with application

An inexact subgradient algorithm for Equilibrium Problems

Constraint qualifications for convex inequality systems with applications in constrained optimization

arxiv: v1 [math.fa] 30 Oct 2018

Characterizations of the solution set for non-essentially quasiconvex programming

Iterative algorithms based on the hybrid steepest descent method for the split feasibility problem

Thai Journal of Mathematics Volume 14 (2016) Number 1 : ISSN

On nonexpansive and accretive operators in Banach spaces

Convexity in R n. The following lemma will be needed in a while. Lemma 1 Let x E, u R n. If τ I(x, u), τ 0, define. f(x + τu) f(x). τ.

SECOND-ORDER CHARACTERIZATIONS OF CONVEX AND PSEUDOCONVEX FUNCTIONS

g 2 (x) (1/3)M 1 = (1/3)(2/3)M.

Convex Optimization Notes

Continuous Sets and Non-Attaining Functionals in Reflexive Banach Spaces

Symmetric strong vector quasiequilibrium problems in Hausdorff locally convex spaces

MAXIMALITY OF SUMS OF TWO MAXIMAL MONOTONE OPERATORS

Optimization and Optimal Control in Banach Spaces

Chapter 2 Convex Analysis

Generalized convex functions and generalized differentials

On Semicontinuity of Convex-valued Multifunctions and Cesari s Property (Q)

Lower Semicontinuity of the Efficient Solution Mapping in Semi-Infinite Vector Optimization

On the split equality common fixed point problem for quasi-nonexpansive multi-valued mappings in Banach spaces

On Penalty and Gap Function Methods for Bilevel Equilibrium Problems

Math 209B Homework 2

Convergence theorems for mixed type asymptotically nonexpansive mappings in the intermediate sense

A Brøndsted-Rockafellar Theorem for Diagonal Subdifferential Operators

EXISTENCE RESULTS FOR QUASILINEAR HEMIVARIATIONAL INEQUALITIES AT RESONANCE. Leszek Gasiński

An iterative method for fixed point problems and variational inequality problems

Scalar Asymptotic Contractivity and Fixed Points for Nonexpansive Mappings on Unbounded Sets

Common fixed points of two generalized asymptotically quasi-nonexpansive mappings

Maximal Monotone Operators with a Unique Extension to the Bidual

On Total Convexity, Bregman Projections and Stability in Banach Spaces

Research Article Cyclic Iterative Method for Strictly Pseudononspreading in Hilbert Space

MOSCO STABILITY OF PROXIMAL MAPPINGS IN REFLEXIVE BANACH SPACES

Coderivatives of gap function for Minty vector variational inequality

A convergence result for an Outer Approximation Scheme

Necessary and Sufficient Conditions for the Existence of a Global Maximum for Convex Functions in Reflexive Banach Spaces

SHRINKING PROJECTION METHOD FOR A SEQUENCE OF RELATIVELY QUASI-NONEXPANSIVE MULTIVALUED MAPPINGS AND EQUILIBRIUM PROBLEM IN BANACH SPACES

Integral Jensen inequality

REMARKS ON SOME VARIATIONAL INEQUALITIES

The Fitzpatrick Function and Nonreflexive Spaces

Chapter 2 Hilbert Spaces

FROM VARIATIONAL TO HEMIVARIATIONAL INEQUALITIES

Well-posedness for generalized mixed vector variational-like inequality problems in Banach space

ON THE RANGE OF THE SUM OF MONOTONE OPERATORS IN GENERAL BANACH SPACES

NEW MAXIMUM THEOREMS WITH STRICT QUASI-CONCAVITY. Won Kyu Kim and Ju Han Yoon. 1. Introduction

Global Maximum of a Convex Function: Necessary and Sufficient Conditions

Transcription:

J Optim Theory Appl (2008) 138: 329 339 DOI 10.1007/s10957-008-9382-6 Relaxed Quasimonotone Operators and Relaxed Quasiconvex Functions M.R. Bai N. Hadjisavvas Published online: 12 April 2008 Springer Science+Business Media, LLC 2008 Abstract In this paper, we introduce the class of multivalued relaxed μ quasimonotone operators and establish the existence of solutions of variational inequalities for such operators. This result is compared with a recent result of Bai et al. on densely relaxed pseudomonotone operators. A similar comparison regarding an existence result of Luc on densely pseudomonotone operators is provided. Also, we introduce a broad class of functions, called relaxed quasiconvex functions, and show that they are characterized by the relaxed μ quasimonotonicity of their subdifferentials. The results strengthen a variety of other results in the literature. Keywords Variational inequalities Relaxed μ quasimonotone operators Relaxed quasiconvex functions Subdifferentials Dag subdifferential 1 Introduction Let X be a normed space with norm and dual space X.LetK be a nonempty convex subset of X and let T : K 2 X \{ } be a multivalued operator. The Stampacchia variational inequality problem for T is to find x K such that y K, x T(x):x,y x 0. (1) Communicated by S. Schaible. This work is supported by NNSF of China (10571046) and by the GSRT of Greece (06FR-062). M.R. Bai College of Mathematics and Econometrics, Hunan University, Changsha, Hunan 410082, China N. Hadjisavvas ( ) Department of Product and Systems Design Engineering, University of the Aegean, Hermoupolis, Syros 84100, Greece e-mail: nhad@aegean.gr

330 J Optim Theory Appl (2008) 138: 329 339 The usual assumptions for proving the existence of solutions for (1) involve some kind of upper semicontinuity, and some kind of generalized monotonicity for the operator T. Various generalized monotonicity assumptions were used, such as: T is pseudomonotone [1, 2]; T is quasimonotone, single valued, and K has inner points [3]; T is properly quasimonotone [4]; T is single-valued and densely pseudomonotone [5]; T is quasimonotone (without any assumption on the existence of inner points) [6]. A different kind of generalization, namely relaxed monotonicity (or else weak monotonicity, or global hypomonotonicity) was considered by various authors in relation with algorithms for finding a solution of variational inequalities or equilibrium problems; see, e.g., [7, 8]. However, in these papers existence of a solution of the variational inequality was assumed rather than shown. Recently, those different generalizations were combined and existence of solutions of (1) was shown for the case of single valued, densely relaxed μ pseudomonotone operators [9, 10]. In the present paper we will introduce the broader class of multivalued relaxed μ quasimonotone operators and establish the existence of solutions of (1) for such operators. This is done in Sect. 2, where we also compare our main result with a recently obtained result for densely relaxed pseudomonotone operators [10]. With an analogous method, we investigate the relation of densely pseudomonotone operators introduced by Luc [5] to properly quasimonotone operators. In Sect. 3 we introduce a broad class of functions, called relaxed μ quasiconvex functions, and show that they are characterized by the relaxed μ quasimonotonicity of their subdifferentials. We fix the notation and introduce some definitions. Given x,y X, we denote by [x,y] the line segment {x + t(y x) : t [0, 1]}. A multivalued operator T : K 2 X \{ } is called upper hemicontinuous if its restriction to line segments of K is upper semicontinuous with respect to the weak topology of X.IfT is single valued, it is called hemicontinuous if its restriction to line segments of K is continuous with respect to the weak topology of X.We denote by S(T,K) the set of solutions of the variational inequality (1): x S(T,K) x K and y K, x T(x):x,y x 0. Also, we denote by LM(T, K) the set of local solutions [6] of the Minty variational inequality x LM(T, K) x K and U : y K U, y T(y), y,y x 0 where U is a neighborhood of x. The following definition generalizes Definition 2.1(ii) of [10] to the multivalued case. Let μ>0 be given. Definition 1.1 A multivalued operator T : K 2 X \{ } is called relaxed μ quasimonotone if, for all x,y K and x T(x), y T(y), the following implication holds: x,y x > 0 y,y x μ y x 2.

J Optim Theory Appl (2008) 138: 329 339 331 We also introduce the relaxed Minty variational inequality y K, y T(y), y,y x μ y x 2 (2) and denote by RM(T,K) the set of x K that satisfy (2). We recall that a set-valued mapping G : K 2 X is said to be a KKM mapping if for any {x 1,...,x n } K, co{x 1,...,x n } n i=1 G(x i ), where co{x 1,...,x n } denotes the convex hull of x 1,...,x n. For the convenience of the reader we reproduce the fundamental lemma of Ky Fan on KKM mappings [11]. Lemma 1.1 Assume that K is a nonempty compact convex subset of a Hausdorff topological vector space X. Let K 0 K be nonempty and let G : K 0 2 K be a KKM mapping. If G(x) is closed in X for each x in K 0, then x K 0 G(x). 2 Existence Result We introduce the following definition. Let μ>0 be given. Definition 2.1 An operator T : K 2 X \{ } is said to be properly relaxed μ quasimonotone if, for all x 1,...,x n K, and all x co{x 1,...,x n }, there exists i {1,...,n} such that x T(x i ), x,x i x μ x i x 2. Proposition 2.1 If T is properly relaxed μ quasimonotone, then it is relaxed μ quasimonotone. Proof Let x,y K and x 0 T(x)be such that x 0,y x > 0. Set x t = x +t(y x), t (0, 1). Since T is μ properly relaxed quasimonotone, for all t (0, 1) we have either x,x x t μ x xt 2, x T(x), (3) or y,y x t μ y xt 2, y T(y). (4) However, (3) implies that x 0,y x μt y x 2, which for sufficiently small t (0, 1) clearly contradicts x0,y x > 0. Thus, for small t (0, 1), (4) holds. Taking the limit in (4) ast 0, we deduce that y,y x μ y x 2, y T(y), i.e., T is relaxed μ quasimonotone.

332 J Optim Theory Appl (2008) 138: 329 339 Lemma 2.1 Let K be a nonempty convex subset of a normed space X. If T : K 2 X \{ } is upper hemicontinuous with weakly compact values, then RM(T,K) S(T,K). Proof Assume to the contrary that there exists x RM(T,K) such that x/ S(T,K). Then there exists y K such that x,y x < 0 for all x T(x). Since T(x) is weakly compact, there exists ε>0 such that x,y x < ε for all x T(x). If we set V ={x X :x,y x < ε}, then V is an weak open set such that T(x) V. Set x t = ty + (1 t)x, t (0, 1]. By upper hemicontinuity, there exists δ>0 such that T(x t ) V for all t (0,δ), i.e., x,y x < ε, t (0,δ), x T(x t ). (5) On the other hand, since x RM(T,K), there exists a constant μ such that, for all t (0,δ)and all x T(x t ),wehave x,x t x = t x,y x μ x t x 2 = μt 2 y x 2, i.e., x,y x μt y x 2. (6) It is clear that, for t small enough, (5) contradicts (6). Therefore, RM(T,K) S(T,K). We deduce that the following alternative holds for every relaxed μ quasimonotone operator. Proposition 2.2 Let K be a nonempty, convex subset of a normed space X and let T : K 2 X \{ } be relaxed μ quasimonotone. Then, one of the following assertions holds: (i) T is properly relaxed μ quasimonotone; (ii) LM(T, K). Proof Suppose that T is not properly relaxed μ quasimonotone. Then, there exist x i K, x i T(x i ), i = 1,...,n, and x co{x 1,x 2,...,x n } such that x i,x i x < μ x x i 2, i = 1,...,n. Since the functions x i,x i +μ x i 2 are continuous, there exists a neighborhood U of x such that, for every z K U, x i,x i z < μ z x i 2. (7)

J Optim Theory Appl (2008) 138: 329 339 333 Since T is relaxed μ quasimonotone, it follows that, for every i = 1,...,nand every z T(z), z,z x i 0. Using x co{x 1,x 2,...,x n }, we deduce that z K U, z T(z), z,z x 0. This means that x LM(T, K) thus LM(T, K). The above alternative entails our main existence result. Proposition 2.3 Let K be a nonempty, compact, convex subset of a normed space X and let T : K 2 X \{ } be relaxed μ quasimonotone and upper hemicontinuous with weakly compact values. Then, S(T,K). Proof According to the preceding proposition, we have either LM(T, K) or that T is properly relaxed μ quasimonotone. If LM(T, K) then we know that S(T,K) [6]. On the other hand, if T is properly relaxed μ quasimonotone, define the multivalued mapping G : K 2 X \{ } by G(x) ={y K :x,x y μ x y 2, x T(x)}. For every x 1,...,x n K and y co{x 1,x 2,...,x n }, proper relaxed quasimonotonicity implies that y n i=1 G(x i ). In addition, for each x K, G(x) is closed; thus, if K is compact, then for each x K, G(x) is also compact. By Lemma 1.1, one has x K G(x), which implies that RM(T,K). Finally, by Lemma 2.1, we obtain again S(T,K). Below, we derive a useful consequence for problem (1) over unbounded sets. We will make use of the following coercivity condition for an operator T : K 2 X \{ }: (C) ρ > 0 such that x K\B(0,ρ); y K such that y < x and x,x y 0, x T(x). Theorem 2.1 Let K be a convex unbounded subset of a normed space X and let T : K 2 X \{ } be upper hemicontinuous and relaxed μ quasimonotone on K with weakly compact values, satisfying the coercivity condition (C) Suppose that there exists ρ >ρsuch that K B(0,ρ ) is nonempty and compact. Then, S(T,K). Proof Set K ρ = K B(0,ρ ). By Proposition 2.3, thesets(t,k ρ ) is nonempty. Choose x 0 S(T,K ρ ). According to the coercivity condition (C) there exists y 0 B(0,ρ ) K such that x,x 0 y 0 0, x T(x 0 ). (8)

334 J Optim Theory Appl (2008) 138: 329 339 (If x 0 <ρ, we can take y 0 = x 0.) Now, for every y K, choose t (0, 1) such that (1 t)y + ty 0 K ρ. Since x 0 S(T,K ρ ), there exists x T(x 0 ) such that Multiplying (8) byt and adding to (9) yields x,(1 t)y + ty 0 x 0 0. (9) x,y x 0 0, which means that x 0 S(T,K). Note that, in Theorem 2.1, the condition of compactness of K B(0,ρ ) is satisfied automatically if K is locally compact. In order to compare our results with those existing in the literature, we recall some definitions. Given a convex subset K of X, asetk 0 K is called segment-dense in K if for every x K there exists x 0 K 0 such that x is a cluster point of the set [x,x 0 ] K 0.Givenμ>0, a single-valued operator T : K X is called relaxed μ pseudomonotone at x K if, for every y K, the following implication holds: T(x),y x 0 T(y),y x μ x y 2. (10) The operator T is called densely relaxed μ pseudomonotone if there exists a segment-dense set K 0 K such that T is relaxed μ pseudomonotone at every x K 0.In[10], it was shown that if K is compact and T is single valued, hemicontinuous and densely relaxed μ pseudomonotone, then the variational inequality problem has a solution. In order to compare with Proposition 2.3 we first show the following proposition. Proposition 2.4 Assume that the operator T : K X is densely relaxed μ pseudomonotone and hemicontinuous. Then, T is properly relaxed μ quasimonotone. Proof Suppose that T is not properly relaxed μ quasimonotone. Then, there exist x 1,x 2,...,x n K, x = n i=1 λ i x i, with λ i > 0 and n i=1 λ i = 1, such that μ x x i 2 > T(x i ), x i x, i = 1, 2,...,n. (11) By assumption, there exists v X and a sequence (t k ) k N converging to zero, such that T is relaxed μ pseudomonotone at x k = x + t k v, k N. Setting x k i = x i + t k v, from (11), it follows that, for k sufficiently large, μ x k xi k 2 > T(xi k ), xk i xk, i = 1, 2,...,n. Since T is relaxed μ pseudomonotone at x k, we deduce that T(x k ), x k i xk < 0. (12) It is clear that x k = n i=1 λ i xi k. Then, (12) implies T(xk ), x k x k < 0, a contradiction.

J Optim Theory Appl (2008) 138: 329 339 335 As the previous proposition shows, hemicontinuity together with densely relaxed μ pseudomonotonicity imply that T is properly relaxed μ quasimonotone. In particular, T is relaxed μ quasimonotone, thus the existence result in [10] can be derived from Proposition 2.3. It should be noted that properly relaxed μ pseudomonotonicity implies that RM(T,K) (see the proof of Proposition 2.3), hence the assumptions in [10] imply that RM(T,K). This is not the case when T is only relaxed μ quasimonotone. Likewise, in [5] a single-valued operator T : K X is called pseudomonotone at x K if, for every y K, the following implication holds: T(y),x y 0 T(x),x y 0. The operator is called densely pseudomonotone if it is pseudomonotone for every x in a segment-dense subset K 0 of K. Note that the difference with the definition of dense relaxed μ pseudomonotonicity is not simply that one takes μ = 0. However, by a suitable modification of the proof of Proposition 2.4 we obtain a similar result. Proposition 2.5 Assume that the operator T : K X is densely pseudomonotone and hemicontinuous. Then, T is properly quasimonotone. Proof Suppose that T is not properly quasimonotone. Then, there exist x 1,x 2,..., x n K, x = n i=1 λ i x i, with λ i > 0 and n i=1 λ i = 1, such that T(x i ), x x i > 0, i = 1, 2,...,n. By assumption, there exist v i X and sequences (ti k) k N converging to 0 as k +, such that T is pseudomonotone at xi k = x i + ti kv i. Set x k = n i=1 λ i xi k. Then, xi k x i and x k x strongly and T(xi k) T(x i) in the weak topology as k + ; thus, for k sufficiently large, T(xi k ), xk xi k > 0, i = 1, 2,...,n. Since T is pseudomonotone at xi k, we deduce that T(x k ), x k xi k > 0. From the definition of x k, we infer that T(x k ), x k x k > 0, a contradiction. 3 Relaxed Quasiconvex Functions In this section, nonsmooth relaxed quasiconvex functions will be introduced. We will show that they are characterized by the relaxed quasimonotonicity of their subdifferential. Throughout this section, X denotes a Banach space with a -smooth renorming [12]. Given a l.s.c. function f : X R {+ }, f denotes any subdifferential of f (see [12]). We need the following approximate mean-value inequality result from [12].

336 J Optim Theory Appl (2008) 138: 329 339 Lemma 3.1 Let a,b X with a dom f and a b, and let r R be such that r f(b). Then, there exist c [a,b], c b, and sequences x n c and x n f (x n) such that lim inf n + x n,c x n 0 and lim inf n + x n,b a r f(a). Definition 3.1 A l.s.c. function f : X R {+ }is called relaxed μ quasiconvex if, for all x,y X, the following implication holds: x f (x) :x,y x > 0 z [x,y], f(y) f(z) μ y z y x. (13) In order to understand the above definition, it is useful to compare it with the characterization of quasiconvex functions in [13]: A l.s.c. function is quasiconvex if and only if x f (x) :x,y x > 0 z [x,y], f(y) f(z). Proposition 3.1 Let X be a Banach space with a -smooth renorming and let f : X R {+ }be a l.s.c. function. If f is relaxed μ quasimonotone, then f is relaxed μ quasiconvex. Proof Suppose that f is relaxed μ quasimonotone. Let x dom f, y dom f, x y, and z [x,y], z y, be such that Then, we can find μ 0 >μsuch that f(y)<f(z) μ y z y x. f(z)>f(y)+ μ 0 y z y x. Letting r = f(y)+ μ 0 y z y x and applying Lemma 3.1 to y and z, we can find c [y,z], c z and sequences x n converging to c and x n f (x n) satisfying lim inf n + x n,c x n 0 and lim inf n + x n,z y μ 0 y z y x. Letting u = c + t(z y) with t>0, we find that lim inf n + x n,u x n lim inf n + x n,c x n +lim inf n + tx n,z y 0 + tμ 0 y z y x = μ 0 u c y x. In particular, taking u = x, we deduce that

J Optim Theory Appl (2008) 138: 329 339 337 lim inf n + x n,x x n μ 0 x c y x >μ lim n + x x n 2, since lim n + x x n = x c y x. Hence, for n sufficiently large, x n,x x n >μ x x n 2. By relaxed μ quasimonotonicity of f,wehave x f (x) :x,x x n 0, for n sufficiently large. Letting n +, it follows that, for all x f (x), x,x c 0, and so, x,x y =[ x y / x c ]x,x c 0. Thus, f is relaxed μ quasiconvex and the proof is completed. The converse of Proposition 3.1 also holds for a fairly large class of subdifferentials. Consider the so-called dag subdifferential [14]: { f(x):= x X : x,v } f(w+ t(v+ x w)) f(w) lim sup, v X. t 0,w x t The dag subdifferential is larger than most known subdifferentials. For instance, it is larger than the Gâteaux subdifferential, the upper Dini subdifferential, the Clarke- Rockafellar subdifferential etc. Consequently, it is also larger than the proximal subdifferential and the Fréchet subdifferential. Proposition 3.2 Assume that is any subdifferential such that f (x) f(x), for every x X. If f is relaxed μ quasiconvex, then f is relaxed μ quasimonotone. Proof Obviously, it is sufficient to show that f is relaxed μ quasimonotone. Assume that f is relaxed μ quasiconvex. Let x,y x > 0forsomex f(x). Then, x,w x > 0 for every w X sufficiently close to y. Relaxed μ quasiconvexity of f implies that f(w+ t(x w)) f(w) μt w x 2, t [0, 1]. So, for all y f(y), y f(w+ t(x y + y w) f(w),x y lim sup t 0,w y t lim sup μ w x 2 t 0,w y

338 J Optim Theory Appl (2008) 138: 329 339 = μ y x 2, i.e., y,y x μ y x 2, which implies f is relaxed μ quasimonotone. This completes the proof. Especially, if f is a Gâteaux differentiable function, and if we set z = x in the right-hand side of (13), then from Proposition 3.1 we also get the following property: if f is relaxed μ quasimonotone, then there exists a ν>0 such that the following implication holds: f(x),y x > 0 f(y) f(x) ν x y 2. (14) (Actually, ν = μ.) The following example shows that a differentiable function f may satisfy (14) while f is not relaxed μ quasimonotone for any μ. Example 3.1 Let f 1 :[0, + ) R be a function with the following properties: 0 f 1 1, f 1 is differentiable on [0, + ) with f 1 0 and f 1 ( 1 n ) = n3. See the end of the example for the construction of such a function. Define f : R R by { x f(x)= 2 (1 + f 1 (x)), x > 0, x 2, x 0. This function is differentiable and 2x(1 + f 1 (x)) x 2 f f 1 (x) < 0, x >0, (x) = 0, x = 0, 2x >0, x <0. We show that f satisfies (14). Assume that f (x)(y x) > 0. If f (x) > 0, then x<0 and y>x.ifx<y 0, then If y>0, then f(y)= y 2 > x 2 2(y x) 2. f(y)= y 2 (1 + f 1 (y)) 2y 2 > x 2 2(y x) 2. In the second case, f (x) < 0, we have x>0 and y<x.ify 0 then f(y)= y 2 > x 2 (y x) 2 x 2 (1 + f 1 (x)) 2(y x) 2. Finally, if 0 <y<x, then f 1 0 implies that f 1(y) f 1 (x); thus, f(y) f(x) (x 2 y 2 )(1 + f 1 (x)) > 2(y x) 2.

J Optim Theory Appl (2008) 138: 329 339 339 Thus, (14) holds with ν = 2. On the other hand, f is not relaxed μ quasimonotone for any μ. Indeed, assume that f is relaxed μ quasimonotone. For every y>0 and every x<0, one has f (x)(y x) > 0; thus, we should have f (y) μ(y x). (15) Taking y = n 1, we find that ( ) 1 f 1 ( ) 1 n n 2 f 1 = n. n Thus, it is clear that (15) is not possible. A note on the construction of the function f 1 :seti n =[ n 1 1, 1 4n 5 n + 1 ]. These 4n intervals are disjoint. Let g be any continuous nonnegative function such that 5 g = 0 on R\ n 1 I n and on each I n takes its maximum value at n 1 with g( n 1 ) = n3.this g is integrable with R g n 1 n3 1 = π 2 2n 5 12 < 1. Finally, define f 1 :[0, + ) R by f 1 (x) = This function f 1 has all desired properties. x 0 g(t)dt. References 1. Cottle, R.W., Yao, J.C.: Pseudomonotone complementarity problems in Hilbert spaces. J. Optim. Theory Appl. 75, 281 295 (1992) 2. Crouzeix, J.P.: Pseudomonotone variational inequality problems: existence of solutions. Math. Program. 78, 305 314 (1997) 3. Hadjisavvas, N., Schaible, S.: Quasimonotone variational inequalities in Banach spaces. J. Optim. Theory Appl. 90, 95 111 (1996) 4. Daniilidis, A., Hadjisavvas, N.: On the subdifferentials of pseudoconvex and quasiconvex functions and cyclic monotonicity. J. Math. Anal. Appl. 237, 30 42 (1999) 5. Luc, D.T.: Existence results for densely pseudomonotone variational inequalities. J. Math. Anal. Appl. 254, 291 308 (2001) 6. Aussel, D., Hadjisavvas, N.: On quasimonotone variational inequalities. J. Optim. Theory Appl. 121, 445 450 (2004) 7. Farouq, N.L.: Convergent algorithm based on progressive regularization for solving pseudomonotone variational inequalities. J. Optim. Theory Appl. 120, 455 485 (2004) 8. Konnov, I.V.: Partial proximal point method for nonmonotone equilibrium problems. Optim. Methods Softw. 21, 373 384 (2006) 9. Bai, M.R., Zhou, S.Z., Ni, G.Y.: Variational-like inequalities with relaxed η α pseudomonotone mappings in Banach spaces. Appl. Math. Lett. 19, 547 554 (2006) 10. Bai, M.R., Zhou, S.Z., Ni, G.Y.: On generalized monotonicity of variational inequalities. Comput. Math. Appl. 53, 910 917 (2007) 11. Fan, K.: A generalization of Tychonoff s fixed point theorem. Math. Ann. 142, 305 310 (1961) 12. Aussel, D., Corvellec, J.N., Lassonde, M.: Mean value property and subdifferential criteria for lower semicontinuous functions. Trans. Am. Math. Soc. 347, 4147 4161 (1995) 13. Aussel, D.: Subdifferential properties of quasiconvex and pseudoconvex functions: unified approach. J. Optim. Theory Appl. 97, 29 45 (1998) 14. Penot, J.P.: Are generalized derivatives useful for generalized convex functions? In: Crouzeix, J.-P., Martínez-Legaz, J.-E., Volle, M. (eds.) Generalized Convexity, Generalized Monotonicity, pp. 3 59. Kluwer Academic, Dordrecht (1998)