SHORT COMMUNICATION. Communicated by Igor Konnov

Similar documents
Quasi-relative interior and optimization

On Gap Functions for Equilibrium Problems via Fenchel Duality

A Brøndsted-Rockafellar Theorem for Diagonal Subdifferential Operators

STABLE AND TOTAL FENCHEL DUALITY FOR CONVEX OPTIMIZATION PROBLEMS IN LOCALLY CONVEX SPACES

A New Fenchel Dual Problem in Vector Optimization

On the relations between different duals assigned to composed optimization problems

Research Article Optimality Conditions of Vector Set-Valued Optimization Problem Involving Relative Interior

Almost Convex Functions: Conjugacy and Duality

On the Brézis - Haraux - type approximation in nonreflexive Banach spaces

Constraint qualifications for convex inequality systems with applications in constrained optimization

On the use of semi-closed sets and functions in convex analysis

1 Topology Definition of a topology Basis (Base) of a topology The subspace topology & the product topology on X Y 3

Lecture 8. Strong Duality Results. September 22, 2008

Robust Duality in Parametric Convex Optimization

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

ZERO DUALITY GAP FOR CONVEX PROGRAMS: A GENERAL RESULT

Duality for almost convex optimization problems via the perturbation approach

Classical linear vector optimization duality revisited

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

Brézis - Haraux - type approximation of the range of a monotone operator composed with a linear mapping

Optimization and Optimal Control in Banach Spaces

SOME REMARKS ON SUBDIFFERENTIABILITY OF CONVEX FUNCTIONS

(convex combination!). Use convexity of f and multiply by the common denominator to get. Interchanging the role of x and y, we obtain that f is ( 2M ε

Centre d Economie de la Sorbonne UMR 8174

Sequential Pareto Subdifferential Sum Rule And Sequential Effi ciency

LECTURE 12 LECTURE OUTLINE. Subgradients Fenchel inequality Sensitivity in constrained optimization Subdifferential calculus Optimality conditions

Victoria Martín-Márquez

Monotone operators and bigger conjugate functions

Chapter 2 Convex Analysis

CHAPTER 7. Connectedness

Jensen s inequality for multivariate medians

A Dual Condition for the Convex Subdifferential Sum Formula with Applications

On constraint qualifications with generalized convexity and optimality conditions

PROBLEMS. (b) (Polarization Identity) Show that in any inner product space

A Geometric Framework for Nonconvex Optimization Duality using Augmented Lagrangian Functions

Additional Homework Problems

THE UNIQUE MINIMAL DUAL REPRESENTATION OF A CONVEX FUNCTION

STRONG AND CONVERSE FENCHEL DUALITY FOR VECTOR OPTIMIZATION PROBLEMS IN LOCALLY CONVEX SPACES

GEOMETRIC APPROACH TO CONVEX SUBDIFFERENTIAL CALCULUS October 10, Dedicated to Franco Giannessi and Diethard Pallaschke with great respect

Optimality Conditions for Nonsmooth Convex Optimization

On the acceleration of the double smoothing technique for unconstrained convex optimization problems

Applied Mathematics Letters

Extreme Abridgment of Boyd and Vandenberghe s Convex Optimization

Maximal monotonicity for the precomposition with a linear operator

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

Some Properties of the Augmented Lagrangian in Cone Constrained Optimization

Remark on a Couple Coincidence Point in Cone Normed Spaces

Lecture 5. The Dual Cone and Dual Problem

The Subdifferential of Convex Deviation Measures and Risk Functions

Continuity. Matt Rosenzweig

Dedicated to Michel Théra in honor of his 70th birthday

Integral Jensen inequality

Lecture 5. Theorems of Alternatives and Self-Dual Embedding

Convex Optimization Theory. Chapter 5 Exercises and Solutions: Extended Version

Appendix B Convex analysis

arxiv: v1 [math.oc] 1 Apr 2013

Conditions for zero duality gap in convex programming

Subdifferential representation of convex functions: refinements and applications

Introduction to Convex Analysis Microeconomics II - Tutoring Class

Extreme points of compact convex sets

A Unified Analysis of Nonconvex Optimization Duality and Penalty Methods with General Augmenting Functions

MATH 51H Section 4. October 16, Recall what it means for a function between metric spaces to be continuous:

On operator equilibrium problems

CONVEX OPTIMIZATION VIA LINEARIZATION. Miguel A. Goberna. Universidad de Alicante. Iberian Conference on Optimization Coimbra, November, 2006

Topology. Xiaolong Han. Department of Mathematics, California State University, Northridge, CA 91330, USA address:

Examples of Convex Functions and Classifications of Normed Spaces

On duality theory of conic linear problems

BASICS OF CONVEX ANALYSIS

Continuous Sets and Non-Attaining Functionals in Reflexive Banach Spaces

Geometry of Banach spaces with an octahedral norm

A Note on Nonconvex Minimax Theorem with Separable Homogeneous Polynomials

Continuity of convex functions in normed spaces

DO NOT OPEN THIS QUESTION BOOKLET UNTIL YOU ARE TOLD TO DO SO

Weak-Star Convergence of Convex Sets

Recall that if X is a compact metric space, C(X), the space of continuous (real-valued) functions on X, is a Banach space with the norm

On the order of the operators in the Douglas Rachford algorithm

DUALITY AND FARKAS-TYPE RESULTS FOR DC INFINITE PROGRAMMING WITH INEQUALITY CONSTRAINTS. Xiang-Kai Sun*, Sheng-Jie Li and Dan Zhao 1.

Economics 204 Fall 2011 Problem Set 2 Suggested Solutions

Functional Analysis. Franck Sueur Metric spaces Definitions Completeness Compactness Separability...

Induced Norms, States, and Numerical Ranges

Smarandachely Precontinuous maps. and Preopen Sets in Topological Vector Spaces

Solutions for Math 217 Assignment #3

SOME STABILITY RESULTS FOR THE SEMI-AFFINE VARIATIONAL INEQUALITY PROBLEM. 1. Introduction

On the convexity of piecewise-defined functions

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

Real Analysis Notes. Thomas Goller

CHAPTER 5. Birkhoff Orthogonality and a Revisit to the Characterization of Best Approximations. 5.1 Introduction

CHARACTERIZATION OF (QUASI)CONVEX SET-VALUED MAPS

Characterizing Robust Solution Sets of Convex Programs under Data Uncertainty

Overview of normed linear spaces

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

Boundedly complete weak-cauchy basic sequences in Banach spaces with the PCP

arxiv: v1 [math.oc] 15 Apr 2016

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

Set, functions and Euclidean space. Seungjin Han

Optimality Conditions for Constrained Optimization

arxiv: v1 [math.fa] 2 Jan 2017

Subgradients. subgradients and quasigradients. subgradient calculus. optimality conditions via subgradients. directional derivatives

Mathematical programs with complementarity constraints in Banach spaces

Math 341 Summer 2016 Midterm Exam 2 Solutions. 1. Complete the definitions of the following words or phrases:

Transcription:

On Some Erroneous Statements in the Paper Optimality Conditions for Extended Ky Fan Inequality with Cone and Affine Constraints and Their Applications by A. Capătă SHORT COMMUNICATION R.I. Boţ 1 and E.R. Csetnek 2 Communicated by Igor Konnov 1 Corresponding author. Department of Mathematics, Chemnitz University of Technology, D-09107 Chemnitz, Germany, e-mail: radu.bot@mathematik.tu-chemnitz.de 2 Department of Mathematics, Chemnitz University of Technology, D-09107 Chemnitz, Germany, e-mail: robert.csetnek@mathematik.tu-chemnitz.de 1

Abstract. In this note we show that the main result of the paper [1] due to A. Capătă and, consequently, all its particular cases are false. Key Words. Lagrange duality, quasi-relative interior, separation theorem, Ky Fan inequality AMS Classification. 46N10, 90C25 2

1 The Incorrect Statements The following statement, concerning a convex optimization problem (P) with geometric and cone constraints and its Lagrange dual problem (D), given in Adela Capătă s paper [1] captured our attention: The next corollary is an improvement of Corollary 4.1 of [18], where the authors considered a superfluous condition in order to prove the above mentioned corollary. Corollary 5.1 Let cl(k K) = Z, and let x S such that g(x) qri K. If a A is a solution of (P) then there exists λ K a weak solution of the dual problem (D) and the value of (P) equals the value of (D). The paper [18], to which the author of [1] refers, is our manuscript [R.I. Boţ, E.R. Csetnek, A. Moldovan: Revisiting some duality theorems via the quasirelative interior in convex optimization, Journal of Optimization Theory and Applications 139(1), 67 84, 2008], quoted in this note as reference [2]. Corollary 5.1 in [1] is obtained by successively particularizing the main result of this paper. In the following we show that [1, Corollary 5.1] is false, which has as a consequence the fact that the main result of the paper in discussion, as well as all its particular instances provide incorrect statements. For the beginning let us recall the framework considered in [1, Corollary 5.1]. Let X be a real linear space, S X a nonempty and convex set, F : S R a convex function on S, Z a separated locally convex space partially ordered by 3

a nonempty convex cone K and g : S Z a K-convex function on S, that is g(αs 1 + (1 α)s 2 ) αg(s 1 ) (1 α)g(s 2 ) K α ]0, 1[ s 1, s 2 S. Corollary 5.1 in [1] concerns the primal optimization problem (P ) inf x A F (x), where A = {x S : g(x) K}, and its Lagrange dual problem (D) sup inf {F (x) + λ(g(x))}. λ K x S Here K := {λ Z : λ(k) 0 k K} denotes the dual cone of K, Z being the topological dual space of Z. Let us also mention that, by a weak solution of the dual problem (D) the author simply means an optimal solution of the Lagrange dual to (P). Further, let us recall that the quasi-relative interior of a convex set M Z is (see [3]) qri M := {z M : cl ( cone(m z) ) is a linear subspace of Z}, where cl and cone denote the closure and the conic hull of a set, respectively. For properties and characterizations of this generalized interiority notion we invite the reader to consult [2-5] and the references therein. Denoting by v(p ) the optimal objective value for (P), assumed to be finite, the conic extension for (P) is the set E v(p ) := {(v(p ) F (x) α, g(x) y) : x S, α 0, y K} = (v(p ), 0) (F, g)(s) R + K. 4

The condition we gave in [2, Corollary 4.1], erroneously characterized by A. Capătă as superfluous, reads 0 / qri E v(p ). The question, whenever one can omit it, was already addressed in [2], where one can also find an example showing that [2, Corollary 4.1] in the absence of this condition fails to be true. A careful reading of our paper would have made the author of [1] clear that her Corollary 5.1 is an incorrect result. We present below the example in question below, concomitantly providing evidence for the fact that [1, Corollary 5.1] is false. Example 1.1 (see also [2, Example 3.2]) Let be X = S = Z = l 2, where l 2 is the real Hilbert space of real sequences (x n ) n N such that n=1 x n 2 < ( ) 1/2 +, equipped with the norm : l 2 R, x = n=1 x n 2 for all x = (x n ) n N l 2. Take K := l 2 + = {(x n ) n N l 2 : x n 0 n N} and define F : l 2 R, F (x) = c, x l2 l 2, where c = (c n) n N, c n = (1/n) for all n N and g : l 2 l 2, g(x) = Bx, where (Bx) n = (1/2 n )x n for all n N. Then A = {x l 2 : Bx l 2 +} = l 2 +. It holds cl(l 2 + l 2 +) = l 2 and qri l 2 + = {x = (x n ) n N l 2 : x n > 0 n N} = (cf. [3]), while one can easily find an x l 2 with g(x) qri l 2 +. We also have that v(p ) = inf c, x = 0 x A and x = 0 is an optimal solution of the primal problem. On the other hand, for λ K = l 2 +, it holds inf x S {F (x) + λ(g(x))} = inf 2{ c, x + λ, g(x) } x l 5

= inf x=(x n) n N l 2 ( ) 1 n x 1 n λ n 2 n x n = inf n=1 n=1 0, if λ n = 2n n n N, =, otherwise. (x n) n N l 2 n=1 ( 1 n λ ) n 2 n x n Since (2 n /n) n N does not belong to l 2, thus neither to l 2 +, it follows that the optimal objective value of the dual problem is v(d) =. Hence, all the hypotheses of [1, Corollary 5.1] are fulfilled, however its conclusion is wrong. The article [1] mainly deals with the extended Ky Fan inequality: (EKF ) find a A such that f(a, b) / int C b A, where X is a real linear space, Y, Z and W are real separated locally convex spaces, Y is partially ordered by a solid (that is, with nonempty interior), pointed and convex cone C, Z is partially ordered by a nonempty convex cone K, S X is a nonempty convex set, f : S S Y is a C-convex function in its second variable fulfilling f(x, x) = 0 for all x S, g : S Z is a K-convex function, h : S W is an affine function, A = {x S : g(x) K and h(x) = 0} and the following condition is fulfilled for all (z, w ) K W \ {0, 0} there is x S such that z (g(x)) + w (h(x)) < 0. The main result of this paper reads: 6

Theorem 3.1 Let qri((g, h)(s)+k {0}). A point a A is a solution of (EKF ) if and only if there exists (y, z, w ) C \{0} K W such that z (g(a)) = 0 and 0 = y (f(a, a))+z (g(a))+w (h(a)) = min x S {y (f(a, x))+z (g(x))+w (h(x))}. Since [1, Corollary 5.1] has been obtained by successively particularizing it, Example 1.1 leads to the conclusion that this theorem, but also all its particular instances [1, Corollary 3.1, Theorem 4.1, Theorem 4.2, Theorem 5.1, Theorem 5.2 and Corollary 5.1] are false. 2 Where Does the Error Come From? In this section, we indicate the source of errors for [1, Theorem 3.1] and, from here, for the other results in [1] listed above. The proof of [1, Theorem 3.1] relies on the following separation statement given in [1, Corollary 2.1]: Corollary 2.1 Let M be a nonempty convex subset of Y and y 0 Y such that qri M and y 0 / qri M. Then there exists y Y \ {0} such that y (y) y (y 0 ) for all y M. Indeed, according to the proof of [1, Theorem 3.1], the author first proves, 7

for a a solution of (EKF ), that the set M := {(y, z, w) Y Z W : x S, y f(a, x)+int C, z g(x)+k, w = h(x)} has an nonempty quasi-relative interior and that y 0 := (0, 0, 0) / qri M and then applies the above corollary in this special setting. As it follows from the next example, the separation statement [1, Corollary 2.1] is false. Example 2.1 (see also [6, Remark 2]) Let Y be an infinite dimensional normed space and f : Y R a linear and discontinuous functional. Define M = {y Y : f(y) = 1}, which is an affine and dense subset of Y. Take y 0 := 0. One can see that qri M = M and y 0 / M = qri M. Hence all the hypotheses of [1, Corollary 2.1] are fulfilled. However, y 0 and M cannot be separated. Indeed, if there would exists y Y \ {0} such that y (y) y (y 0 ) for all y M, then by employing the fact that M is dense in Y, one would obtain y = 0, which is a contradiction. In [5, Corollary 2.1], in order to obtain a valid separation result, one has to assume that y 0 M \ qri M, whereby the condition qri M needs not necessarily be fulfilled. Other separation theorems involving the quasi-relative interior of a convex set can be found in [2, 4, 5] and the references therein. 8

3 Concluding Remarks In this note, we have shown that the main result and all its particular cases of the paper [1] due to A. Capătă are false, by sustaining our claims with examples and pointing out the flaw in the proof of the main result [1, Theorem 3.1]. Let us also mention that in [1] there is a considerable number of inaccuracies, inconsistencies and false assertions, however, we omit mentioning them, as this would exceed our intentions. All these aspects make us question the quality of the reviewing process of [1]. We stress that fact that, when a paper emphasizes a possible improvement of some results of another work, then the reviewers have to verify carefully at least this statement. This was for [1], definitively, not the case. Otherwise, a short look in [2] would have been enough to come to the conclusion that, due to [2, Example 3.2], the statement in [1, Corollary 5.1] is false. 9

References 1. Capătă, A.: Optimality conditions for extended Ky Fan inequality with cone and affine constraints and their applications, J. Optim. Theory Appl., published Online First on 10 September 2011 2. Boţ, R.I., Csetnek, E.R., Moldovan, A.: Revisiting some duality theorems via the quasirelative interior in convex optimization, J. Optim. Theory Appl. 139, 67 84 (2008) 3. Borwein, J.M., Lewis, A.S.: Partially finite convex programming, part I: Quasi relative interiors and duality theory, Math. Program. 57, 15 48 (1992) 4. Boţ, R.I., Csetnek, E.R.: Regularity conditions via generalized interiority notions in convex optimization: new achievements and their relation to some classical statements, Optimization DOI: 10.1080/02331934.2010.505649, Preprint arxiv:0906.0453v1, posted 2 June (2009) 5. Boţ, R.I., Csetnek, E.R., Wanka, G.: Regularity conditions via quasirelative interior in convex programming, SIAM J. Optim. 19, 217 233 (2008) 6. Daniele, P., Giuffrè, S., Idone, G., Maugeri, A.: Infinite dimensional duality and applications, Math. Ann. 339, 221 239 (2007) 10