Journal of Function Spaces

Volume 2016, Article ID 1917387, 12 pages

http://dx.doi.org/10.1155/2016/1917387

## Calculus Rules for -Proximal Subdifferentials in Smooth Banach Spaces

Department of Mathematics, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia

Received 27 December 2015; Accepted 24 April 2016

Academic Editor: Adrian Petrusel

Copyright © 2016 Messaoud Bounkhel. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

In 2010, Bounkhel et al. introduced new proximal concepts (analytic proximal subdifferential, geometric proximal subdifferential, and proximal normal cone) in reflexive smooth Banach spaces. They proved, in -uniformly convex and -uniformly smooth Banach spaces, the density theorem for the new concepts of proximal subdifferential and various important properties for both proximal subdifferential concepts and the proximal normal cone concept. In this paper, we establish calculus rules (fuzzy sum rule and chain rule) for both proximal subdifferentials and we prove the Bishop-Phelps theorem for the proximal normal cone. The limiting concept for both proximal subdifferentials and for the proximal normal cone is defined and studied. We prove that both limiting constructions coincide with the Mordukhovich constructions under some assumptions on the space. Applications to nonconvex minimisation problems and nonconvex variational inequalities are established.

#### 1. Introduction

In [1], the authors introduced the concept of geometric proximal subdifferential and the concept of analytic proximal subdifferential in reflexive Banach spaces for . They also introduced the concept of generalised proximal normal cone for . The main tool in their approach is the generalised projection operator and the functional (see [1, 2]). They proved various important properties for their concepts.

In order to avoid any confusion with other existing proximal subdifferential and proximal normal cones in Banach spaces (see, e.g., [3–6]) we will call , , and analytic -proximal subdifferential, geometric -proximal subdifferential, and -proximal normal cone, respectively. These names are more natural since these concepts are strongly based on and we use these names in all the paper.

The main aim of this work is to prove the fuzzy sum rule and the chain rule for both proximal subdifferentials. Our results extend the existing results on the usual proximal subdifferential from Hilbert spaces setting to our Banach spaces setting. We start by proving that whenever the space admits an equivalent norm which is away from the origin. Sections 3 and 4 are devoted to proving the fuzzy sum rule and the chain rule. In Section 5, we define the limiting constructions for the -proximal concepts (the analytic and geometric -proximal subdifferential and the -proximal normal cone). In this section we prove that these limiting constructions coincide with the limiting constructions in [7] whenever the space admits an equivalent norm with a power of that norm being away from the origin. Section 5 is ended by proving the well known Bishop-Phelps theorem for the -proximal normal cone and its limiting construction. The paper is closed by an application, in which, we derive a necessary optimality condition for nonconvex minimisation problems and nonconvex variational inequalities in terms of generalised projections.

#### 2. Preliminaries

Let be a reflexive smooth Banach space with topological dual space . We will denote by and the closed unit ball centred at the origin in and , respectively. Let be a function and where is finite. We recall from [1] the concept of* analytic **-proximal subdifferential * (called in [1]* analytic proximal subdifferential*). An element belongs to provided that there exists so thatfor very close to , where is the normalized duality mapping and is a functional defined by

For a closed nonempty set in and , the authors in [1] defined the concept of *-proximal normal cone * (called in [1]* proximal normal cone*) by . Using this -proximal normal cone, the authors in [1] defined another concept of -proximal subdifferential, called* geometric proximal subdifferential*, as follows: An element belongs to provided , where is the epigraph of defined by . In this paper will be called* geometric **-proximal subdifferential*. We recall, respectively, the well known concepts of proximal subdifferential and Fréchet subdifferential (see, e.g., [5]):(i) if and only if there exist such that(ii) if and only if for any there exists such thatThe Fréchet and proximal normal cone are defined as and Notice that (see [7, 8]) Fréchet and proximal subdifferential can be defined geometrically by the formulas and .

We recall (see, e.g., [1, 9]) the definition of -uniformly convex and -uniformly smooth Banach spaces. The space is said to be -uniformly convex (resp., -uniformly smooth) if there is a constant such that where and are defined, respectively, by Notice that the constants and in the previous definition always satisfy and .

The following inclusions have been proved in [1]:Consider the following two assumptions on the norm on at a given point : (A1), for close to and for some and .(A2), for close to and for some and .Using Lemma in [1], we get that (A1) is satisfied for any -uniformly smooth Banach spaces and (A2) is satisfied for any -uniformly convex Banach spaces. Easily we can check that if (A1) is satisfied with , then we have and and so and . This is the case, for instance, of spaces with . The reverse inclusions and hold whenever (A2) is satisfied with and so and which is the case of spaces with . In the general case we cannot provide a relationship between and the two -proximal subdifferentials and .

We recall from [1] the following important characterisation of -proximal normal cone in terms of the generalised projection.

Proposition 1. *For any closed set and any point we have *

Here is the generalised projection operator defined as follows (see [10, 11]):

We summarise in the following proposition some needed results of the analytic and geometric -proximal subdifferentials proved in [1].

Proposition 2. *Let be a -uniformly convex and -uniformly smooth Banach space and let be a lower semicontinuous function and :*(i)*If is on a neighbourhood of , then *(ii)*Let , and . Then *

*It has been proved in [1] that the equality form holds for convex l.s.c. functions and for indicator functions associated with closed nonempty sets in any reflexive smooth Banach space. So, it is a natural question to ask whether this equality is valid for general forms of functions. In the following proposition we give a positive answer with additional assumptions on the space for any l.s.c. function.*

*Proposition 3. Let be -uniformly convex and -uniformly smooth Banach space. Assume that admits an equivalent which is on . Let be the functional associated with . Let be a lower semicontinuous function at . Then .*

*Proof. *The direct inclusion has been proved in [1]. Let ; that is, and hence there exists such that It follows that By lower semicontinuity of we may choose some such that , for all . Also, we can take too small so that Therefore, for any we have which yieldsSet and . Then , for all ; that is, is a local minimum of and so . Now, we can easily check that is around with for very close to . Indeed, since we can find smaller than for which we have , for any . Thus by the differentiability of the equivalent norm we have for any that is, the function is differentiable at any and . Now, we use the property of the norm around , that is, the property of the duality mapping around , and we obtain the property of around with . Now, we return to and we use the previous proposition to get ; that is, and hence the proof is complete.

*Remark 4. *The assumption on the norm used in the previous proposition is true for any Hilbert space and for many other Banach spaces (see, e.g., [9, 12]). Using Theorem in Section in [9] we get that all spaces for satisfy the property with their canonical norm and the same result is also true for the Sobolev spaces (). We refer the reader for more examples and discussions to [9, 12] and the references therein.

*3. Fuzzy Sum Rules*

*In this section, we are going to prove the fuzzy sum rule for the analytic -proximal subdifferential. To do that, we need the following new version of Borwein-Preiss variational principle in terms of the functional . For its proof we refer the reader to [13].*

*Theorem 5. Let be -uniformly convex and -uniformly smooth Banach space and let be bounded below lower semicontinuous function, and . Suppose that is a point satisfying . Then for any there exist points and withand having the property that the function has a unique minimum at .*

*Let us prove the following lemma needed in the proof of the main result in this section. Its proof follows the same lines of the proof of Proposition in [8].*

*Lemma 6. Let be -uniformly convex and -uniformly smooth Banach space. Let , , be l.s.c. functions at ; one of them is Lipschitz continuous around . Let be a closed convex subset of with . Let and let be any equivalent norm on . Then for any with we have *

*Proof. *Obviously we always have and so Conversely, let such that Since and are bounded below on we get This ensures that for some which yields that since .

We use now the Lipschitz continuity of over for some to getTaking the limit as yields the desired inequality and hence the proof is finished.

*Now, we assume that the space satisfies an additional assumption. Assume that admits an equivalent such that (for some ) is -differentiable on . We refer the reader to [9, 12] for many examples of Banach space satisfying this assumption. So, we are ready to prove the main result.*

*Theorem 7. Let be -uniformly smooth and -uniformly convex Banach space. Let , , be l.s.c. functions at ; one of them is Lipschitz continuous around . Assume that admits an equivalent such that (for some ) is -differentiable on and let be the functional associated with that . Let . Then for any , there exist with , such that *

*Proof. *Let . There exist such that attains a minimum over at . We take also small enough so that and are bounded below on and is Lipschitz on which is satisfied for any . Let where . Now consider the problem of minimising over . Applying Lemma 6 with the functions and yields the conclusion that the nonnegative quantity as ; that is, for large enough the couple satisfies We apply now the variational principle stated in Theorem 5 with , , and . Then there exist two points and such thatand such that the function has a unique minimum at over the space . Thus for sufficiently large (since ) both and are in , so that the fact of the minimisation implies the separate necessary conditions:Thus using the fact that the functions and are on with and by using Proposition 2, we can write Adding these two inclusions yields Let . For large enough we can ensure that and and so Thus, it remains to show that , , for large enough. Since , we haveand so for large enough. From this inequality we derive Using now the l.s.c. of both functions and and and we obtainand so we deduce from the previous inequalities that Using this equality and the l.s.c. of we getThis inequality with the l.s.c. of ensures that Similarly for we obtain These two equalities ensure , , for large enough.

*We notice that the fuzzy sum rule for the geometric -proximal subdifferential cannot be deduced directly from the previous one. However, it will be used for that purpose. First we need to prove the following proposition.*

*Proposition 8. Let be -uniformly smooth and -uniformly convex Banach space. Let be a l.s.c. function at . Assume that admits an equivalent such that (for some ) is -differentiable on and let be the functional associated with that . For any and any , there exist with such that*

*Proof. *Let . Fix any . Then by definition of the Fréchet subdifferential there exists such that attains a minimum over at . Hence Using the fuzzy sum rule for the analytic -proximal subdifferential in Theorem 7 we can find with such thatThus,and so the proof of the proposition is complete.

*Now, we are ready to prove the fuzzy sum rule for the geometric -proximal subdifferential.*

*Theorem 9. Let be -uniformly smooth and -uniformly convex Banach space. Let , , be l.s.c. functions at ; one of them is Lipschitz continuous around . Assume that admits an equivalent such that (for some ) is -differentiable on and let be the functional associated with that . If , then for any , there exist with , , such that *

*Proof. *Fix any and let be the Lipschitz constant of around . Let . Assume that . By Proposition 2 we get . Then, by Proposition 8 there exists with , such that We use now the fuzzy sum rule for the analytic -proximal subdifferential to obtain some points with , , such that Obviously we have . Also we have This completes the proof.

*The following corollary is a direct consequence of Theorem 7. It is also valid for the geometric -proximal subdifferential.*

*Corollary 10. Let be -uniformly smooth and -uniformly convex Banach space. Assume that admits an equivalent such that (for some ) is -differentiable on and let be the functional associated with that . Let be locally Lipschitz function around . If minimises over , then for any , there exist with and such that *

*4. Chain Rule*

*Using the fuzzy sum rule established in the previous section for the analytic -proximal subdifferential, we prove the chain rule for both analytic and geometric -proximal subdifferentials. Let be another -uniformly convex and -uniformly smooth Banach space and let and . In this section, will denote the norm on and the closed unit ball in will be denoted by . We will denote by functional (2) associated with the . We will say that is a locally -Lipschitz mapping around provided that there exist and such that*

*Theorem 11. Let , be a locally -Lipschitz mapping around , and let be locally Lipschitz around . Assume that (resp., ) admit an equivalent (resp., ) such that (resp., ) (for some ) is -differentiable on (resp., ) and let (resp., ) be the functional associated with (resp., ). Let . Then for all there exist , , and such that and *

*Proof. *Fix . By Lipschitz property of around and by definition of the analytic -proximal subdifferential there exist a positive number (we may assume that ), , and such thatSet , the graph of in . The previous inequalities ensure that for any This means that the function attains a local minimum at and hence Applying our fuzzy sum rule in Theorem 7 with there exist and in such that for some we have This ensures that ; that is, . Using Proposition 2 we obtain for some Thus Hence there exist , , , and such that for any we haveThe last inequality follows from Lemma in [1] and hence for any we have and hence we getwhere Thus We use the fuzzy sum rule once again to obtain two points and in such thatThe Lipschitz property of with ratio around ensures that is Lipschitz with ratio around and hence by Proposition 2 we obtain Also the uniform continuity of ensures by shrinking that and hence Therefore, by taking and , we get and with and , thus completing the proof.

*Remark 12. *As for the fuzzy sum rule for geometric -proximal subdifferential, we combine the chain rule for the analytic -proximal subdifferential and Proposition 8 to prove easily the chain rule for the geometric -proximal subdifferential.

*5. Limiting -Proximal Subdifferential and Limiting -Proximal Normal Cone*

*After proving the density theorem for in [1] and consequently for , it is a natural question to consider the limiting object of both -proximal subdifferential concepts as follows:where means with . These two subdifferentials will be called, respectively, the limting analytic -proximal subdifferential and the limiting geometric -proximal subdifferential. Our main aim in this section is to prove, under the assumptions of Theorem 7, that these two constructions coincide with the limiting Fréchet subdifferential (also called Mordukhovich subdifferential) (see [7]).*

*Theorem 13. Let be -uniformly smooth and -uniformly convex Banach space. Let be a l.s.c. function at . Assume that admits an equivalent such that (for some ) is -differentiable on and let be the functional associated with that . ThenHere and are limiting Fréchet subdifferential and limiting proximal subdifferential, respectively; that is, and *

*Proof. *The last equality has been proved in [6] which is our setting. So, it remains to prove the other two equalities. It will be enough to prove the inclusion . Fix . There exists with such that , . Using Proposition 8 with we get a sequence