# Some algorithms for equilibrium problems on Hadamard manifolds

- Muhammad Aslam Noor
^{1}Email author and - Khalida Inayat Noor
^{1}

**2012**:230

https://doi.org/10.1186/1029-242X-2012-230

© Noor and Noor; licensee Springer 2012

**Received: **27 April 2012

**Accepted: **28 September 2012

**Published: **12 October 2012

## Abstract

In this paper, we suggest and analyze an iterative method for solving the equilibrium problems on Hadamard manifolds using the auxiliary principle technique. We also consider the convergence analysis of the proposed method under suitable conditions. Some special cases are considered. Results and ideas of this paper may stimulate further research in this fascinating and interesting field.

**MSC:**49J40, 90C33, 26D10, 39B62.

## Keywords

## 1 Introduction

Equilibrium problems theory provides us with a unified, natural, novel and general framework to study a wide class of problems, which arise in finance, economics, network analysis, transportation and optimization. This theory has applications across all disciplines of pure and applied sciences. Equilibrium problems include variational inequalities and related problems as special cases; see [1–31]. Recently, much attention has been given to study the variational inequalities, equilibrium and related optimization problems on the Riemannian manifold and Hadamard manifold. This framework is useful for the development of various fields. Several ideas and techniques from the Euclidean space have been extended and generalized to this nonlinear framework. Hadamard manifolds are examples of hyperbolic spaces and geodesics; see [1, 3–5, 19, 20, 26–28] and the references therein. Nemeth [8], Tang *et al.* [28], Noor *et al.* [19, 20] and Colao *et al.* [3] have considered the variational inequalities and equilibrium problems on Hadamard manifolds. They have studied the existence of solutions of equilibrium problems under some suitable conditions. To the best of our knowledge, no one has considered the auxiliary principle technique for solving the equilibrium problems on Hadamard manifolds. In this paper, we use the auxiliary principle technique to suggest and analyze an implicit method for solving the equilibrium problems on a Hadamard manifold. As special cases, our result includes the recent results of Tang *et al.* [28] for variational inequalities on a Hadamard manifold. This shows that the results obtained in this paper continue to hold for variational inequalities on a Hadamard manifold, which are due to Noor and Noor [20], Tang *et al.* [28], and Nemeth [8]. We hope that the technique and idea of this paper may stimulate further research in this area.

## 2 Preliminaries

We now recall some fundamental and basic concepts needed for reading of this paper. These results and concepts can be found in the books on Riemannian geometry [1, 3, 4, 26, 29].

Let *M* be a simply connected *m*-dimensional manifold. Given $x\in M$, the tangent space of *M* at *x* is denoted by ${T}_{x}M$ and the tangent bundle of *M* by $TM={\bigcup}_{x\in M}{T}_{x}M$, which is naturally a manifold. A vector field *A* on *M* is a mapping of *M* into *TM* which associates to each point $x\in M$, a vector $A(x)\in {T}_{x}M$. We always assume that *M* can be endowed with a Riemannian metric to become a Riemannian manifold. We denote by $\u3008\cdot ,\cdot \u3009$ the scalar product on ${T}_{x}M$ with the associated norm ${\parallel \cdot \parallel}_{x}$, where the subscript *x* will be omitted. Given a piecewise smooth curve $\gamma :[a,b]\u27f6M$ joining *x* to *y* (that is, $\gamma (a)=x$ and $\gamma (b)=y$) by using the metric, we can define the length of *γ* as $L(\gamma )={\int}_{a}^{b}\parallel {\gamma}^{\mathrm{\prime}}(t)\parallel \phantom{\rule{0.2em}{0ex}}dt$. Then for any $x,y\in M$, the Riemannian distance $d(x,y)$, which includes the original topology on *M*, is defined by minimizing this length over the set of all such curves joining *x* to *y*.

Let Δ be the Levi-Civita connection with $(M,\u3008\cdot ,\cdot \u3009)$. Let *γ* be a smooth curve in *M*. A vector field *A* is said to be parallel along *γ* if ${\mathrm{\Delta}}_{{\gamma}^{\mathrm{\prime}}}A=0$. If ${\gamma}^{\mathrm{\prime}}$ itself is parallel along *γ*, we say that *γ* is a geodesic and in this case $\parallel {\gamma}^{\mathrm{\prime}}\parallel $ is a constant. When $\parallel {\gamma}^{\mathrm{\prime}}\parallel =1$, *γ* is said to be normalized. A geodesic joining *x* to *y* in *M* is said to be minimal if its length equals $d(x,y)$.

A Riemannian manifold is complete if for any $x\in M$, all geodesics emanating from *x* are defined for all $t\in R$. By the Hopf-Rinow theorem, we know that if *M* is complete, then any pair of points in *M* can be joined by a minimal geodesic. Moreover, $(M,d)$ is a complete metric space, and bounded closed subsets are compact.

Let *M* be complete. Then the exponential map ${exp}_{x}:{T}_{x}M\u27f6M$ at *x* is defined by ${exp}_{x}v={\gamma}_{v}(1,x)$ for each $v\in {T}_{x}M$, where $\gamma (\cdot )={\gamma}_{v}(\cdot ,x)$ is the geodesic starting at *x* with velocity *v* (*i.e.*, $\gamma (0)=x$ and ${\gamma}^{\mathrm{\prime}}(0)=v$). Then ${exp}_{x}tv={\gamma}_{v}(t,x)$ for each real number *t*.

A complete simply connected Riemannian manifold of nonpositive sectional curvature is called a *Hadamard manifold*. Throughout the remainder of this paper, we always assume that *M* is an *m*-dimensional Hadamard manifold.

We also recall the following well-known results, which are essential for our work.

**Lemma 2.1** ([26])

*Let* $x\in M$. *Then* ${exp}_{x}:{T}_{x}M\u27f6M$ *is a diffeomorphism*, *and for any two points* $x,y\in M$, *there exists a unique normalized geodesic joining* *x* *to* *y*, ${\gamma}_{x,y}$, *which is minimal*.

So, from now on, when referring to the geodesic joining two points, we mean the unique minimal normalized one. Lemma 2.1 says that *M* is diffeomorphic to the Euclidean space ${R}^{m}$. Thus, *M* has the same topology and differential structure as ${R}^{m}$. It is also known that Hadamard manifolds and Euclidean spaces have similar geometrical properties. Recall that a geodesic triangle $\mathrm{\u25b3}({x}_{1},{x}_{2},{x}_{3})$ of a Riemannian manifold is a set consisting of three points ${x}_{1}$, ${x}_{2}$, ${x}_{3}$ and three minimal geodesics joining these points.

**Lemma 2.2** (Comparison theorem for triangles [3, 4, 26])

*Let*$\mathrm{\u25b3}({x}_{1},{x}_{2},{x}_{3})$

*be a geodesic triangle*.

*Denote*,

*for each*$i=1,2,3\phantom{\rule{0.25em}{0ex}}(mod3)$,

*by*${\gamma}_{i}:[0,{l}_{i}]\u27f6M$

*the geodesic joining*${x}_{i}$

*to*${x}_{i+1}$,

*and*${\alpha}_{i};=L({\gamma}_{i}^{\mathrm{\prime}}(0),-{\gamma}_{l}^{\mathrm{\prime}}(i-1)(li-1))$,

*the angle between the vectors*${\gamma}_{i}^{\mathrm{\prime}}(0)$

*and*$-{\gamma}_{i-1}^{\mathrm{\prime}}({l}_{i-1})$,

*and*${l}_{i};=L({\gamma}_{i})$.

*Then*

*In terms of the distance and the exponential map*,

*the inequality*(2.2)

*can be rewritten as*

*since*

**Lemma 2.3** ([26])

*Let*$\mathrm{\u25b3}(x,y,z)$

*be a geodesic triangle in a Hadamard manifold*

*M*.

*Then there exist*${x}^{\mathrm{\prime}},{y}^{\mathrm{\prime}},{z}^{\mathrm{\prime}}\in {R}^{2}$

*such that*

*The triangle* $\mathrm{\u25b3}({x}^{\mathrm{\prime}},{y}^{\mathrm{\prime}},{z}^{\mathrm{\prime}})$ *is called the comparison triangle of the geodesic triangle* $\mathrm{\u25b3}(x,y,z)$, *which is unique up to isometry of* *M*.

From the properties of the exponential map, we have the following known result.

**Lemma 2.4** ([26])

*Let*${x}_{0}\in M$

*and*$\{{x}_{n}\}\subset M$

*such that*${x}_{n}\u27f6{x}_{0}$.

*Then the following assertions hold*.

- (i)
*For any*$y\in M$,${exp}_{{x}_{n}}^{-1}y\u27f6{exp}_{{x}_{o}}^{-1}y\phantom{\rule{1em}{0ex}}\mathit{\text{and}}\phantom{\rule{1em}{0ex}}{exp}_{y}^{-1}{x}_{n}\u27f6{exp}_{y}^{-1}{x}_{o}.$ - (ii)
*If*$\{{v}_{n}\}$*is a sequence such that*${v}_{n}\in {T}_{{x}_{n}}M$*and*${v}_{n}\u27f6{v}_{0}$,*then*${v}_{0}\in {T}_{{x}_{0}}M$. - (iii)
*Given the sequences*$\{{u}_{n}\}$*and*$\{{v}_{n}\}$*satisfying*${u}_{n},{v}_{n}\in {T}_{{x}_{n}}M$,*if*${u}_{n}\u27f6{u}_{0}$*and*${v}_{n}\u27f6{v}_{0}$,*with*${u}_{0},{v}_{0}\in {T}_{{x}_{0}}M$,*then*$\u3008{u}_{n},{v}_{n}\u3009\u27f6\u3008{u}_{0},{v}_{0}\u3009.$

A subset $K\subseteq M$ is said to be convex if for any two points $x,y\in K$, the geodesic joining *x* and *y* is contained in *K*, that is, if $\gamma :[a,b]\u27f6M$ is a geodesic such that $x=\gamma (a)$ and $y=\gamma (b)$, then $\gamma ((1-t)a+tb)\in K$, $\mathrm{\forall}t\in [0,1]$. From now on, $K\subseteq M$ will denote a nonempty, closed and convex set, unless explicitly stated otherwise.

*f*defined on

*K*is said to be convex, if for any geodesic

*γ*of

*M*, the composition function $f\circ \gamma :R\u27f6R$ is convex, that is,

*∂f*defined by

The existence of subgradients for convex functions is guaranteed by the following proposition, see [29].

*Let* *M* *be a Hadamard manifold and* $f:M\u27f6R$ *be convex*. *Then for any* $x\in M$, *the subdifferential* $\partial f(x)$ *of* *f* *at* *x* *is nonempty*. *That is*, $D(\partial f)=M$.

which is called the equilibrium problem on Hadamard manifolds. This problem was considered by Colao *et al.* [3]. They proved the existence of a solution of the problem (2.5) using the KKM maps. Colao *et al.* [3] have given an example of the equilibrium problem defined in an Euclidean space whose set *K* is not a convex set, so it cannot be solved using the technique of Blum and Oettli [2]. However, if one can reformulate the equilibrium problem on a Riemannian manifold, then it can be solved. This shows the importance of considering these problems on Hadamard manifolds. Noor *et al.* [19, 20] have used the auxiliary principle technique to suggest and analyze an implicit method for solving the equilibrium problems on a Hadamard manifold. For the applications, formulation and other aspects of equilibrium problems in the linear setting, see [2, 5, 7–18, 22].

which is called the variational inequality on Hadamard manifolds. Nemeth [8], Colao *et al.* [3], Tang *et al.* [28] and Noor and Noor [19] studied variational inequalities on a Hadamard manifold from different points of view. In the linear setting, variational inequalities have been studied extensively; see [2, 6, 9–22, 27, 30, 31] and the references therein.

**Definition 2.1**A bifunction $F(\cdot ,\cdot )$ is said to be partially relaxed strongly monotone if and only if there exists a constant $\alpha >0$ such that

We note that if $z=u$, then partially relaxed strongly monotonicity reduces to the monotonicity of the bifunction $F(\cdot ,\cdot )$.

## 3 Main results

We now use the auxiliary principle technique of Glowinski *et al.* [6] to suggest and analyze an implicit iterative method for solving the equilibrium problems (2.5).

which is called the auxiliary equilibrium problem on Hadamard manifolds. We note that if $w=u$, then *w* is a solution of (2.5). This observation enables us to suggest and analyze the following implicit method for solving the equilibrium problems (2.5). This is the main motivation of this paper.

**Algorithm 3.1**For a given ${u}_{0}$, compute the approximate solution by the iterative scheme

Algorithm 3.1 is called the explicit iterative method for solving the equilibrium problem on the Hadamard manifold.

If *K* is a convex set in ${R}^{n}$, then Algorithm 3.1 collapses to

**Algorithm 3.2**For a given ${u}_{0}\in K$, find the approximate solution ${u}_{n+1}$ by the iterative scheme

which is known as the explicit method for solving the equilibrium problem. For the convergence analysis of Algorithm 3.2, see [12, 15, 16].

If $F(u,v)=\u3008Tu,{exp}_{u}^{-1}v\u3009$, where *T* is a single valued vector filed $T:K\u27f6TM$, then Algorithm 3.1 reduces to the following implicit method for solving the variational inequalities.

**Algorithm 3.3**For a given ${u}_{0}\in K$, compute the approximate solution ${u}_{n+1}$ by the iterative scheme

For $M={R}^{n}$, Algorithm 3.3 reduces to

**Algorithm 3.4**For a given ${u}_{0}\in K$, compute the approximate solution ${u}_{n+1}$ by the iterative scheme

which can be written in the following equivalent form.

**Algorithm 3.5**For a given ${u}_{0}\in K$, compute the approximate solution ${u}_{n+1}$ by the iterative scheme

which is known as the projection method. For the convergence analysis and its applications, see [10, 11].

In a similar way, one can obtain several iterative methods for solving the variational inequalities on the Hadamard manifold.

We now consider the convergence analysis of Algorithm 3.1, and this is the motivation of our next result.

**Theorem 3.1**

*Let*$F(\cdot ,\cdot )$

*be a partially relaxed strongly monotone bifunction with a constant*$\alpha >0$.

*Let*${u}_{n}$

*be the approximate solution of the equilibrium problem*(2.5)

*obtained from Algorithm*3.1,

*then*

*where* $u\in K$ *is a solution of the equilibrium problem* (2.5).

*Proof*Let $u\in K$ be a solution of the equilibrium problem (2.5). Then

Thus, from (3.7) and (3.8), we obtained the inequality (3.3), the required result. □

**Theorem 3.2** *Let* $u\in K$ *be solution of* (2.5), *and let* ${u}_{n+1}$ *be the approximate solution obtained from Algorithm * 3.1. *If* $\rho <\frac{1}{2\alpha}$, *then* ${lim}_{n\u27f6\mathrm{\infty}}{u}_{n+1}=u$.

*Proof*Let $\stackrel{\u02c6}{u}$ be a solution of (2.5). Then, from (3.3), it follows that the sequence $\{{u}_{n}\}$ is bounded and

which implies that the sequence $\{{u}_{n}\}$ has a unique cluster point and ${lim}_{n\u27f6\mathrm{\infty}}{u}_{n}=\stackrel{\u02c6}{u}$ is a solution of (2.5), the required result. □

## 4 Conclusion

The auxiliary principle technique is used to suggest and analyze an explicit method for solving the equilibrium problems on Hadamard manifolds. It is shown that the convergence analysis of this method requires only the partially relaxed strongly monotonicity. Some special cases are discussed. Results proved in this paper may stimulate research in this area.

## Declarations

### Acknowledgements

The authors would like to thank Dr. S. M. Junaid Zaidi, Rector, COMSATS Institute of Information Technology, Islamabad, Pakistan, for providing excellent research facilities. The authors are grateful to the referees for their constructive suggestions and comments.

## Authors’ Affiliations

## References

- Azagra D, Ferrera J, Lopez-Mesas F: Nonsmooth analysis and Hamiltonian-Jacobi equations on Riemannian manifolds.
*J. Funct. Anal.*2005, 220: 304–361. 10.1016/j.jfa.2004.10.008MathSciNetView ArticleGoogle Scholar - Blum E, Oettli W: From optimization and variational inequalities to equilibrium problems.
*Math. Stud.*1994, 63: 123–145.MathSciNetGoogle Scholar - Colao V, Lopez G, Marino G, Martin-Marquez V: Equilibrium problems in Hadamard manifolds.
*J. Math. Anal. Appl.*2012, 388: 61–77. 10.1016/j.jmaa.2011.11.001MathSciNetView ArticleGoogle Scholar - DoCarmo MP:
*Riemannian Geometry*. Birkhäuser, Boston; 1992.Google Scholar - Ferrera OP, Oliveira PR: Proximal point algorithms on Riemannian manifolds.
*Optimization*2002, 51(2):257–270. 10.1080/02331930290019413MathSciNetView ArticleGoogle Scholar - Glowinski R, Lions JL, Tremolieres R:
*Numerical Analysis of Variational Inequalities*. North-Holland, Amsterdam; 1981.Google Scholar - Li C, Lopez G, Martin-Marquez V, Wang JH: Resolvent of set valued monotone vector fields in Hadamard manifolds.
*Set-Valued Var. Anal.*2011, 19(3):361–383. 10.1007/s11228-010-0169-1MathSciNetView ArticleGoogle Scholar - Nemeth SZ: Variational inequalities on Hadamard manifolds.
*Nonlinear Anal.*2003, 52(5):1491–1498. 10.1016/S0362-546X(02)00266-3MathSciNetView ArticleGoogle Scholar - Noor MA: General variational inequalities.
*Appl. Math. Lett.*1988, 1: 119–121. 10.1016/0893-9659(88)90054-7MathSciNetView ArticleGoogle Scholar - Noor MA: New approximation schemes for general variational inequalities.
*J. Math. Anal. Appl.*2000, 251: 217–229. 10.1006/jmaa.2000.7042MathSciNetView ArticleGoogle Scholar - Noor MA: Some developments in general variational inequalities.
*Appl. Math. Comput.*2004, 152: 199–277. 10.1016/S0096-3003(03)00558-7MathSciNetView ArticleGoogle Scholar - Noor MA: Fundamentals of mixed quasi variational inequalities.
*Int. J. Pure Appl. Math.*2004, 15: 137–258.MathSciNetGoogle Scholar - Noor MA: Auxiliary principle technique for equilibrium problems.
*J. Optim. Theory Appl.*2004, 122: 131–146.View ArticleGoogle Scholar - Noor MA: Fundamentals of equilibrium problems.
*Math. Inequal. Appl.*2006, 9: 529–566.MathSciNetGoogle Scholar - Noor MA: Extended general variational inequalities.
*Appl. Math. Lett.*2009, 22: 182–185. 10.1016/j.aml.2008.03.007MathSciNetView ArticleGoogle Scholar - Noor MA: On an implicit method for nonconvex variational inequalities.
*J. Optim. Theory Appl.*2010, 147: 411–417. 10.1007/s10957-010-9717-yMathSciNetView ArticleGoogle Scholar - Noor MA: Auxiliary principle technique for solving general mixed variational inequalities.
*J. Adv. Math. Stud.*2010, 3(2):89–96.MathSciNetGoogle Scholar - Noor MA, Noor KI: On equilibrium problems.
*Appl. Math. E-Notes*2004, 4: 125–132.MathSciNetGoogle Scholar - Noor MA, Noor KI: Proximal point methods for solving mixed variational inequalities on Hadamard manifolds.
*J. Appl. Math.*2012., 2012: Article ID 657278Google Scholar - Noor MA, Zainab S, Yao Y: Implicit methods for equilibrium problems on Hadamard manifolds.
*J. Appl. Math.*2012., 2012: Article ID 437391Google Scholar - Noor MA, Noor KI, Rassias TM: Some aspects of variational inequalities.
*J. Comput. Appl. Math.*1993, 47: 285–312. 10.1016/0377-0427(93)90058-JMathSciNetView ArticleGoogle Scholar - Noor MA, Oettli W: On general nonlinear complementarity problems and quasi equilibria.
*Matematiche*1994, 49: 313–331.MathSciNetGoogle Scholar - Pitea A, Postolache M: Duality theorems for a new class multitime multiobjective variational problems.
*J. Glob. Optim.*2012, 54(1):47–58. 10.1007/s10898-011-9740-zMathSciNetView ArticleGoogle Scholar - Pitea A, Postolache M: Minimization of vectors of curvilinear functionals on the second order jet: necessary conditions.
*Optim. Lett.*2012, 6(3):459–470. 10.1007/s11590-010-0272-0MathSciNetView ArticleGoogle Scholar - Pitea A, Postolache M: Minimization of vectors of curvilinear functionals on the second order jet: sufficient efficiency conditions.
*Optim. Lett.*2011. doi:10.1007/s11590–011–0357–4Google Scholar - Sakai T 149. In
*Riemannian Geometry*. Am. Math. Soc., Providence; 1996.Google Scholar - Stampacchia G: Formes bilineaires coercivities sur les ensembles coercivities sur les ensembles convexes.
*C. R. Math. Acad. Sci. Paris*1964, 258: 4413–4416.MathSciNetGoogle Scholar - Tang G, Zhou LW, Huang NJ: The proximal point algorithm for pseudomonotone variational inequalities on Hadamard manifolds.
*Optim. Lett.*2012. doi:10.1007/s11590–012–0459–7Google Scholar - Udriste C:
*Convex Functions and Optimization Methods on Riemannian Manifolds*. Kluwer Academic, Dordrecht; 1994.View ArticleGoogle Scholar - Yao Y, Noor MA, Liou YC: Strong convergence of a modified extra-gradient method to the minimum-norm solution of variational inequalities.
*Abstr. Appl. Anal.*2012., 2012: Article ID 817436Google Scholar - Yao Y, Noor MA, Liou YC, Kang SM: Iterative algorithms for general multi-valued variational inequalities.
*Abstr. Appl. Anal.*2012., 2012: Article ID 768272Google Scholar

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