A Convexity of Functions on Convex Metric Spaces of Takahashi and Applications 349 Balls ( [4] , Propositions 1 and 2)
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View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Journal of the Egyptian Mathematical Society (2016) 24 , 348–354 Egyptian Mathematical Society Journal of the Egyptian Mathematical Society www.etms-eg.org www.elsevier.com/locate/joems Original Article A convexity of functions on convex metric spaces of Takahashi and applications ∗ Ahmed A. Abdelhakim Department of Mathematics, Faculty of Science, Assiut University, Assiut 71516, Egypt Received 29 August 2015; accepted 4 October 2015 Available online 28 November 2015 Keywords Abstract We show that Takahashi’s idea of convex structures on metric spaces is a natural gener- Convex metric space; alization of convexity in normed linear spaces and Euclidean spaces in particular. Then we introduce W -convex functions; a concept of convex structure based convexity to functions on these spaces and refer to it as W - Metric projection convexity. W -convex functions generalize convex functions on linear spaces. We provide illustrative examples of (strict) W -convex functions and dedicate the major part of this paper to proving a variety of properties that make them fit in very well with the classical theory of convex analysis. As expected, the lack of linearity forced us to make some compromises in terms of conditions on either the metric or the convex structure. Finally, we apply some of our results to the metric projection problem and fixed point theory. 2010 Mathematics Subject Classification: 26A51; 52A01; 46N10; 47N10 Copyright 2015, Egyptian Mathematical Society. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ). 1. Introduction and preliminaries spaces there is the work of Liepi ņ š [5] and Taskovi cˇ [6] . Taka- hashi [4] introduced the following general concept of convexity There have been a few attempts to introduce the structure of in metric spaces: convexity outside linear spaces. Kirk [1,2] , Penot [3] and Taka- Definition 1 [4] . Let ( X , d ) be a metric space and I = [0 , 1] . A hashi [4] , for example, presented notions of convexity for sets in continuous function W : X × X × I → X is said to be a con- metric spaces. Even in the more general setting of topological vex structure on X if for each x , y ∈ X and all t ∈ I , d ( u, W (x, y ; t) ) ≤ (1 − t) d(u, x ) + t d(u, y ) (1) ∗ Tel.: + 2 01095087950. for all u ∈ X . A metric space ( X , d ) with a convex structure W E-mail address: [email protected] is called a convex metric space and is denoted by ( X , W , d ). A Peer review under responsibility of Egyptian Mathematical Society. subset C of X is called convex if W ( x , y ; t ) ∈ C whenever x , y ∈ C and t ∈ I . What makes Takahashi’s notion of convexity solid is the Production and hosting by Elsevier invariance under taking intersections and convexity of closed S1110-256X(15)00080-2 Copyright 2015, Egyptian Mathematical Society. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ). http://dx.doi.org/10.1016/j.joems.2015.10.003 A convexity of functions on convex metric spaces of Takahashi and applications 349 balls ( [4] , Propositions 1 and 2). The convex structure W in proved a convergence theorem in a convex metric space. To our Definition 1 has the following property which is stated in [4] best knowledge, this is the first time a fixed point iteration, other without proof. For the sake of completeness, we give a proof of than the well-known Picard iteration, was introduced to metric it here. spaces. Later, a lot of strong convergence results in convex met- ric spaces followed (see [8] ). Lemma 1. For any x , y in a convex metric space ( X , W , d ) and In the light of Definition 1 , it is tempting to identify convex any t ∈ I we have functions on convex metric spaces. Based on the idea of convex d(x, W (x, y ; t)) = t d(x, y ) , structures on metric spaces, we define and illustrate by examples what we call W -convex functions. In linear metric spaces with d(y, W (x, y ; t)) = (1 − t) d(x, y ) . W defined by (2) , W -convex functions coincide with traditional Proof. For simplicity, let a , b and c stand for d ( x, W (x, y ; t) ), convex functions. We show throughout the paper that many of d ( y, W (x, y ; t) ) and d ( x , y ) respectively. Using (1) we get a ≤ t c the main properties of convex functions on linear spaces are sat- and b ≤ (1 − t) c . But c ≤ a + b by the triangle inequality. isfied by W-convex functions. As expected some of these proper- So c ≤ a + b ≤ (1 − t) c + t c = c. This means a + b = c . If ties do not carry over automatically from linear spaces to con- a < t c then we would have a + b < c which is a contradic- vex metric spaces. In order to achieve such properties we had tion. Therefore, we must have a = t c and consequently b = to require additional assumptions on the convex structure W. (1 − t) c. For instance, while midpoint convex continuous functions on normed linear spaces are convex, midpoint W -convexity on its The necessity for the condition (1) on W to be a convex struc- own seems insufficient to obtain an analogous result in con- ture on a metric space ( X , d ) is natural. To see this, assume that vex metric spaces. Another example appears when we study ( X , . X ) is a normed linear space. Then the mapping W : X × the equivalence between local boundedness from above and lo- X × I → X given by cal Lipschitz continuity of W -convex functions. To achieve this equivalence we required the convex metric space to satisfy a cer- W (x, y ; t) = (1 − t) x + t y, x, y ∈ X , t ∈ I, (2) tain property that is naturally satisfied in any linear space. Other properties necessitated providing a suitable framework to prove. defines a convex structure on X . Indeed, if ρ is the metric in- For example, to investigate the relation between W -convexity of duced by the norm . X then functions and the convexity of their epigraphs, we had to design a convex structure on product metric spaces to be able to define ρ( u, W (x, y ; t) ) = u − ( (1 − t) x + ty ) X convex product metric spaces and characterize their convex sub- ≤ (1 − t) u − x X + t u − y X sets. Finally, we apply some of our results on W-convexity to the metric projection problem and fixed point theory. For this pur- = (1 − t) ρ(u, x ) + t ρ(u, y ) , ∀ u ∈ X , t ∈ I. pose, we give a definition for strictly convex metric spaces that The picture gets clearer in the linear space R 2 with the Eu- generalizes strict convexity in Banach spaces and relate it to a clidean metric and the convex structure given by (2) . In certain class of strictly W -convex functions. this case, given two points x, y ∈ R 2 and a t ∈ I , z = W (x, y ; t) is a point that lies on the line segment joining 2. W -convex functions on convex metric spaces x and y . Moreover, Lemma 1 implies that if xy = L then and their main properties xz = t L and zy = (1 − t) L and we arrive at an interesting exercise of elementary trigonometry to show that uz ≤ (1 − Definition 2. A realvalued function f on a convex metric t) ux + t uy for any point u in the plane. (Hint: apply the space ( X , W , d ) is W -convex if for all x , y ∈ X and t ∈ Pythagorean theorem to the triangles uyv, uvz and uvx I , f ( W ( x, y ; t ) ) ≤ (1 − t) f (x ) + tf (y ) . We call f strictly W - in the figure below then use the fact that xy ≤ xu + uy). convex if f ( W ( x, y ; t ) ) < (1 − t) f (x ) + tf (y ) for all distinct u points x , y ∈ X and every t ∈ I o = ]0 , 1[ . Example 1. Consider the Euclidean space R 3 with the Eu- clidean norm . . Let B be the subset of R 3 that consists of xz t = all closed balls B ( ξ, r ) with center ξ ∈ R 3 and radius r > 0. For zy 1 − t any two balls B(ξ1 , r 1 ) , B(ξ2 , r 2 ) ∈ B, define the distance func- x v y z = W (x, y; t) tion d B (B(ξ1 , r 1 ) , B(ξ2 , r 2 )) = ξ1 − ξ2 + | r 1 − r 2 | . It is easy to check that (B, d B ) is a metric space. Let W B : B × B × I → B Takahashi’s concept of convexity was used extensively in be the continuous mapping given by fixed point theory in metric spaces (cf. [7] and the references W B ( B(ξ , r ) , B(ξ , r ) ; θ ) = B((1 − θ) ξ + θξ , therein). One of its most important applications is probably it- 1 1 2 2 1 2 ( − θ) + θ ) , ξ ∈ R 3, > , θ ∈ . erative approximation of fixed points in metric spaces. There is 1 r1 r2 i ri 0 I quite huge literature on fixed point iterations (cf. [8,9] ). Roughly Since for all θ ∈ I and any three balls B(ξi , r i ) ∈ B, i = 1 , 2 , 3 , speaking, the formation of most, if not all, known fixed point d B (W B ( B(ξ , r ) B(ξ , r ) ; θ ) B(ξ , r ) ) iterative procedures is based on that of the Mann iteration [10] 1 1 , 2 2 , 3 3 and the Ishikawa iteration [11] as its very first generalization.