volume 2, issue 3, article 27, 2001.
Received — ; accepted 15 March, 2001.
Communicated by:D. Bainov
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Journal of Inequalities in Pure and Applied Mathematics
GENERALIZED AUXILIARY PROBLEM PRINCIPLE AND SOLVABILITY OF A CLASS OF NONLINEAR VARIATIONAL INEQUALITIES INVOLVING COCOERCIVE AND
CO-LIPSCHITZIAN MAPPINGS
RAM U. VERMA
University of Toledo, Department of Mathematics, Toledo, Ohio 43606, USA.
EMail:verma99@msn.com
c
2000Victoria University ISSN (electronic): 1443-5756 025-01
Generalized Auxiliary Problem Principle and Solvability of a Class of Nonlinear Variational
Inequalities Involving Cocoercive and Co-Lipschitzian
Mappings Ram U. Verma
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Abstract
The approximation-solvability of the following class of nonlinear variational in- equality (NVI) problems, based on a new generalized auxiliary problem princi- ple, is discussed.
Find an elementx∗∈Ksuch that
h(S−T) (x∗), x−x∗i+f(x)−f(x∗)≥0 for allx∈K,
whereS, T:K→Hare mappings from a nonempty closed convex subsetKof a real Hilbert spaceHintoH, andf:K→Ris a continuous convex functional onK.The generalized auxiliary problem principle is described as follows: for given iteratexk∈Kand, for constantsρ >0andσ >0), findxk+1such that
D
ρ(S−T)
yk
+h0
xk+1
−h0
yk
, x−xk+1 E
+ρ(f(x)−f(xk+1))
≥0 for all x∈K,
where D
σ(S−T) xk
+h0 yk
−h0 xk
, x−ykE
+σ(f(x)−f(yk))
≥0 for all x∈K, wherehis a functional onKandh0the derivative ofh.
Generalized Auxiliary Problem Principle and Solvability of a Class of Nonlinear Variational
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2000 Mathematics Subject Classification:49J40.
Key words: Generalized auxiliary variational inequality problem, Cocoercive map- pings, Approximation-solvability, Approximate solutions, Partially relaxed monotone mappings.
Contents
1 Introduction. . . 4 2 Generalized Auxiliary Problem Principle. . . 9
References
Generalized Auxiliary Problem Principle and Solvability of a Class of Nonlinear Variational
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1. Introduction
Recently, Zhu and Marcotte [23], based on the auxiliary problem principle in- troduced by Cohen [3], investigated the approximation-solvability of a class of variational inequalities involving the cocoercive and partially cocoercive map- pings in the Rn space. The auxiliary problem technique introduced by Cohen [3], is quite similar to that of the iterative algorithm characterized as the auxil- iary variational inequality studied by Marcotte and Wu [12], but the estimates for the approximate solutions seem to be significantly different, which makes a difference establishing the convergence of the sequence of approximate solu- tions to a given solution of the original variational inequality under considera- tion. On the top of that, using the auxiliary problem principle, one does not re- quire any projection formula leading to a fixed point and eventually the solution of the variational inequality, which has been the case following the variational inequality type algorithm adopted by Marcotte and Wu [12]. Recently Verma [21] introduced an iterative scheme characterized as an auxiliary variational inequality type of algorithm and applied to the approximation-solvability of a class of nonlinear variational inequalities involving cocoercive as well as par- tially relaxed monotone mappings [18] in a Hilbert space setting. The partially relaxed monotone mappings seem to be weaker than cocoercive and strongly monotone mappings. In this paper, we first intend to introduce the general- ized auxiliary problem principle, and then apply the generalized auxiliary prob- lem principle, which includes the auxiliary problem principle of Cohen [3] as a special case, to approximation-solvability of a class of nonlinear variational inequalities involving cocoercive mappings. The obtained results do comple- ment the earlier works of Cohen [3], Zhu and Marcotte [23] and Verma [18] on
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the approximation- solvability of nonlinear variational inequalities in different space settings.
LetH be a real Hilbert space with the inner producth·,·iand normk·k. Let S,T : K → H be any mappings and K a closed convex subset of H. Let f : K →Rbe a continuous convex function. We consider a class of nonlinear variational inequality (abbreviated as NVI) problems: find an elementx∗ ∈ K such that
(1.1) h(S−T) (x∗), x−x∗i+f(x)−f(x∗)≥0 for all x∈K.
Now we need to recall the following auxiliary result, most commonly used in the context of the approximation-solvability of the nonlinear variational in- equality problems based on the iterative procedures.
Lemma 1.1. An elementu∈Kis a solution of the NVI problem (1.1) if h(S−T)(u), x−ui+f(x)−f(u)≥0 for all x∈K.
A mappingS : H → H is said to beα-cocoercive [19] if for allx, y ∈ H, we have
kx−yk2 ≥α2kS(x)−S(y)k2+kα(S(x)−S(y))−(x−y)k2, whereα >0is a constant.
A mappingS :H →His calledα-cocoercive [12] if there exists a constant α >0such that
hS(x)−S(y), x−yi ≥αkS(x)−S(y)k2 for all x, y ∈H.
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S is calledr-strongly monotone if for eachx, y ∈H, we have hS(x)−S(y), x−yi ≥rkx−yk2 for a constant r >0.
This implies that
kS(x)−S(y)k ≥rkx−yk,
that is, S is r-expanding, and when r = 1, it is expanding. The mapping S is calledβ−Lipschitz continuous (orβ−Lipschitzian) if there exists a constant β ≥0such that
kS(x)−S(y)k ≤βkx−yk for all x, y ∈H.
We note that ifSisα-cocoercive and expanding, thenSisα-strongly mono- tone. On the top of that, ifSisα-strongly monotone andβ−Lipschitz continu- ous, thenS is
α β2
cocoercive forβ >0. Clearly everyα-cocoercive mapping S is α1
−Lipschitz continuous.
Proposition 1.2. [21]. LetS : H → H be a mapping from a Hilbert spaceH into itself. Then the following statements are equivalent:
(i) For eachx, y ∈H and for a constantα >0, we have
kx−yk2 ≥α2kS(x)−S(y)k2+kα(S(x)−S(y))−(x−y)k2. (ii) For eachx, y ∈H, we have
hS(x)−S(y), x−yi ≥αkS(x)−S(y)k2, whereα >0is a constant.
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Lemma 1.3. For all elementsv, w∈H, we have
kvk2+hv, wi ≥ −1 4kwk2.
A mappingS : H → H is said to beγ−partially relaxed monotone [18] if for allx, y, z ∈H, we have
hS(x)−S(y), z−yi ≥ −γkz−xk2 for γ >0.
Proposition 1.4. [18]. Let S : H → H be anα-cocoercive mapping on H.
ThenSis 4α1
−partially relaxed monotone.
Proof. We include the proof for the sake of the completeness. Since S is α- cocoercive, it implies by Lemma1.1, for allx, y, z ∈H, that
hS(x)−S(y), z−yi = hS(x)−S(y), x−yi+hS(x)−S(y), z−xi
≥ αkS(x)−S(y)k2+hS(x)−S(y), z−xi
= α
kS(x)−S(y)k2+ 1
α
hS(x)−S(y), z−xi
≥ − 1
4α
kz−xk2,
that is,Sis 4α1
−partially relaxed monotone.
A mappingT : H → H is said to beµ-co-Lipschitz continuous if for each x, y ∈H and for a constantµ >0, we have
kx−yk ≤µkT(x)−T(y)k.
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This clearly implies that
hT(x)−T(y), x−yi ≤µkT(x)−T(y)k2.
Clearly, everyµ-co-Lipschitz continuous mappingT is
1 µ
−expanding.
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2. Generalized Auxiliary Problem Principle
This section deals with the approximation-solvability of the NVI problem (1.1), based on the generalized auxiliary nonlinear variational inequality problem prin- ciple by Verma [18], which includes the auxiliary problem principle introduced by Cohen [3] and later applied and studied by others, including Zhu and Mar- cotte [22]. This generalized auxiliary nonlinear variational inequality (GANVI) problem is as follows: for a given iteratexk, determine an xk+1 such that (for k ≥0):
(2.1)
ρ(S−T) yk
+h0 xk+1
−h0 yk
, x−xk+1 +ρ f(x)−f xk+1
≥0 for all x∈K, where
(2.2)
σ(S−T) xk
+h0 yk
−h0 xk
, x−yk +σ f(x)−f yk
≥0 for all x∈K, and for a strongly convex function honK (whereh0 denotes the derivative of h).
Whenσ = ρin the GANVI problem (2.1)-(2.2), we have GANVI problem as follows: for a given iteratexk, determine anxk+1such that (fork ≥0):
(2.3)
ρ(S−T) yk
+h0 xk+1
−h0 yk
, x−xk+1 +ρ f(x)−f xk+1
≥0 for all x∈K,
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where (2.4)
ρ(S−T) xk
+h0 yk
−h0 xk
, x−yk +ρ f(x)−f yk
≥0 for all x∈K.
Forσ = 0 andyk = xk, the GANVI problem (2.1)-(2.2) reduces to: for a given iteratexk, determine anxk+1such that (fork ≥0):
(2.5)
ρ(S−T) xk
+h0 xk+1
−h0 xk
, x−xk+1 +ρ f(x)−f xk+1
≥0 for all x∈K.
Next, we recall some auxiliary results crucial to the approximation-solvability of the NVI problem (1.1).
Lemma 2.1. [23]. Leth : K → Rbe continuously differentiable on a convex subsetKofH. Then we have the following conclusions:
(i) Ifhisb-strongly convex, then
h(x)−h(y)≥ hh0(y), x−yi+ b
2
kx−yk2 for all x, y ∈K.
(ii) If the gradienth0isp−Lipschitz continuous, then
h(x)−h(y)≤ hh0(y), x−yi+ b
2
kx−yk2 for all x, y ∈K.
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We are just about ready to present, based on the GANVI problem (2.1) – (2.2), the approximation-solvability of the NVI problem (1.1) involvingγ−co- coercive mappings in a Hilbert space setting.
Theorem 2.2. LetHbe a real Hilbert space andS :K →H aγ−cocoercive mapping from a nonempty closed convex subset K of H into H. Let T : K → H be a µ-co-Lipschitz continuous mapping. Suppose that h : K → R is continuously differentiable and b-strongly convex, and h0, the derivative of h, is p−Lipschitz continuous. Then xk+1 is a unique solution of (2.1) – (2.2). If in addition, ifx∗ ∈ K is any fixed solution of the NVI problem (1.1), then xk is bounded and converges to x∗ for 0 < ρ < 2bγ, ρ +σ < b and xk+1−xk, xk−yk
≥0.
Proof. Before we can show that the sequences
xk converges to x∗, a solu- tion of the NVI problem (1.1), we need to compute the estimates. Since h is b−strongly convex, it ensures the uniqueness of solutionxk+1 of the GANVI problem (2.1) – (2.2). Let us define a functionΛ∗ by
Λ∗(x) := h(x∗)−h(x)− hh0(x), x∗−xi
≥ b
2
kx∗−xk2 for x∈K,
wherex∗ is any fixed solution of the NVI problem (1.1). It follows foryk ∈K that
Λ∗ yk
= h(x∗)−h yk
−
h0 yk
, x∗−yk
= h(x∗)−h yk
−
h0 yk
, x∗−xk+1+xk+1−yk .
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Similarly, we can have Λ∗ xk+1
=h(x∗)−h xk+1
−
h0 xk+1
, x∗−xk+1 .
Now we can write Λ∗ yk
−Λ∗ xk+1 (2.6)
=h xk+1
−h yk
−
h0 yk
, xk+1−yk +
h0 xk+1
−h0 yk
, x∗−xk+1
≥ b
2
xk+1−yk
2+
h0 xk+1
−h0 yk
, x∗ −xk+1
≥ b
2
xk+1−yk
2+ρ
(S−T) yk
, xk+1−x∗ +ρ f xk+1
−f(x∗) , forx=x∗ in (2.1).
If we replacexbyxk+1in (1.1) and combine with (2.6), we obtain Λ∗ yk
−Λ∗ xk+1
≥ b
2
xk+1−yk
2
+ρ
(S−T) yk
, xk+1−x∗
−ρ
(S−T) (x∗), xk+1−x∗
= b
2
xk+1−yk
2+ρ
(S−T) yk
−(S−T) (x∗), xk+1−x∗
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= b
2
xk+1−yk
2+ρ
(S−T) yk
−(S−T) (x∗), xk+1−yk+yk−x∗
= b
2
xk+1−yk
2+ρ
(S−T) yk
−(S−T) (x∗), yk−x∗ +ρ
(S−T) yk
−(S−T) (x∗), xk+1−yk .
SinceSisγ−cocoercive andT isµ-co-Lipschitz continuous, it implies that
Λ∗ yk
−Λ∗ xk+1 (2.7)
≥ b
2
xk+1−yk
2+ργ
(S−T) yk
−(S−T) (x∗)
2
+ρ
(S−T) yk
−(S−T) (x∗), xk+1−yk
= b
2
xk+1−yk
2+ργ
(S−T) yk
−(S−T) (x∗) 2
+ 1
γ
(S−T) yk
−(S−T) (x∗), xk+1−yk
≥ b
2
xk+1−yk
2−
ρ 4(γ−µ)
xk+1−yk
2 (by Lemma1.3)
= 1 2
b−
ρ 2(γ−µ)
xk+1−yk
2 for γ−µ >0.
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Similarly, we can have
Λ∗ xk
−Λ∗ yk (2.8)
=h yk
−h xk
−
h0 xk
, yk−xk +
h0 yk
−h0 xk
, x∗ −yk
≥ b
2
yk−xk
2+
h0 yk
−h0 xk
, x∗−yk
≥ b
2
yk−xk
2+σ T xk
, yk−x∗
+σ f yk
−f(x∗) , forx=x∗ in (2.2).
Again, if we replacexbyykin (1.1) and combine with (2.8), we obtain Λ∗ xk
−Λ∗ yk (2.9)
≥ b
2
yk−xk
2
+σ
(S−T) xk
, yk−x∗
−σ
(S−T) (x∗), yk−x∗
= b
2
yk−xk
2
+σ
(S−T) xk
−(S−T) (x∗), yk−x∗ +xk−xk
= b
2
yk−xk
2+σ
(S−T) xk
−(S−T) (x∗), xk−x∗ +σ
(S−T) xk
−(S−T) (x∗), yk−xk
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≥ b
2
yk−xk
2−
σ 4(γ−µ)
yk−xk
2
= 1
2 b−
σ 2(γ −µ)
yk−xk
2.
Finally, we move toward finding the required estimate
Λ∗ xk
−Λ∗ xk+1 (2.10)
= Λ∗ xk
−Λ∗ yk
+ Λ∗ yk
−Λ∗ xk+1
≥ 1
2 b−
σ 2(γ−µ)
yk−xk
2
+ 1
2 b−
ρ 2(γ−µ)
xk+1−yk
2
= 1
2 b−
σ 2(γ−µ)
yk−xk
2
+ 1
2 b−
ρ 2(γ−µ)
×
xk+1−xk 2+
xk−yk
2+ 2
xk+1−xk, xk−yk
= 1
2 b−
ρ 2(γ−µ)
xk+1−xk 2
+
b−
σ+ρ 4(γ−µ)
yk−xk
2
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+
b−
ρ 2(γ−µ)
xk+1−xk, xk−yk
≥ 1
2 b−
ρ 2(γ−µ)
xk+1−xk
2 forb− ρ
2(γ−µ) >0, b− 4(γ−µ)σ+ρ >0and
xk+1−xk, xk−yk
≥0.
It follows from (2.10) that forxk+1 = yk = xk that xk is a solution of the variational inequality. If not, the conditions b − 2(γ−µ)ρ > 0, b − 4(γ−µ)σ+ρ > 0 and
xk+1−xk, xk−yk
≥ 0ensure that the sequence
Λ∗(xk)−Λ∗(xk+1) is nonnegative and, as a result, we have
k→∞lim
xk+1−xk = 0.
On the top of that,
x∗−xk
2 ≤ 2b
Λ∗ xk
and the sequence Λ∗ xk is decreasing , that means
xk is a bounded sequence. Assume that x0 is a cluster point of
xk . Then ask → ∞ in (2.1) – (2.2), x0 is a solution of the variational inequality because there is no loss generality ifx∗is replaced byx0. If we associatex0 toΛ0and defineΛ0 by
Λ0 xk
= h(x0)−h xk
−
h0 xk
, x0−xk
≤ p 2
x0 −xk
2 (by Lemma2.1),
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then we have
Λ0 xk
≤p 2
x0−xk
2. Since the sequence
Λ0 xk is strictly decreasing, it follows thatΛ0 xk
→0.
On the other hand, we already have Λ0 xk
≥ b
2
x0−xk
2.
Thus, we can conclude that the entire sequence
xk converges to x0, and this completes the proof. Forσ =ρin Theorem2.2, we find:
Theorem 2.3. Let Hbe a real Hilbert space andT :K →H aγ−cocoercive mapping from a nonempty closed convex subsetK ofHintoH. Leth:K →R be continuously differentiable andb−strongly convex, andh0, the derivative of h, isp−Lipschitz continuous. Thenxk+1is a unique solution of (2.3) – (2.4).
If in addition, x∗ ∈ K is any fixed solution of the NVI problem (1.1), then xk is bounded and converges tox∗for0< ρ < 2bγ and
xk+1−xk, xk−yk
≥ 0.
Whenσ = 0andyk=xk, Theorem 2. reduces to:
Theorem 2.4. [23]. Let H be a real Hilbert space and T : K → H a γ−cocoercive mapping from a nonempty closed convex subsetK ofHintoH.
Let h : K → Rbe continuously differentiable andb−strongly convex, andh0, the derivative of h, isp−Lipschitz continuous. Then xk+1 is a unique solution of (2.5).
If in addition,x∗ ∈ K is any fixed solution of the NVI problem (1.1), then xk is bounded and converges tox∗for0< ρ < 2bγ.
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References
[1] C. BAIOCCHI AND A. CAPELO, Variational and Quasivariational In- equalities, Wiley & Sons, New York, 1984.
[2] J.S. PANG ANDD. CHAN, Iterative methods for variational and comple- mentarity problems, Math. Programming, 24 (1982), 284–313.
[3] G. COHEN, Auxiliary problem principle extended to variational inequali- ties, J. Optim. Theo. Appl., 59(2) (1988), 325–333.
[4] J.C. DUNN, Convexity, monotonicity and gradient processes in Hilbert spaces, J. Math. Anal. Appl., 53 (1976), 145–158.
[5] J.S. GUOANDJ.C. YAO, Extension of strongly nonlinear quasivariational inequalities, Appl. Math. Lett., 5(3) (1992), 35–38.
[6] B.S. HE, A projection and contraction method for a class of linear comple- mentarity problems and its applications, Applied Math. Optim., 25 (1992), 247–262.
[7] B.S. HE, A new method for a class of linear variational inequalities, Math.
Programming, 66 (1994), 137–144.
[8] B.S. HE, Solving a class of linear projection equations, Numer. Math., 68 (1994), 71–80.
[9] B.S. HE, A class of projection and contraction methods for monotone vari- ational inequalities, Applied Math. Optim., 35 (1997), 69–76.
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Inequalities Involving Cocoercive and Co-Lipschitzian
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[10] D. KINDERLEHRERANDG. STAMPACCHIA, An Introduction to Vari- ational Inequalities, Academic Press, New York, 1980.
[11] G. M. KORPELEVICH, The extragradient method for finding saddle points and other problems, Matecon, 12 (1976), 747–756.
[12] P. MARCOTTE AND J. H. WU, On the convergence of projection meth- ods, J. Optim. Theory Appl., 85 (1995), 347–362.
[13] R.U. VERMA, Nonlinear variational and constrained hemivariational in- equalities involving relaxed operators, ZAMM, 77(5) (1997), 387–391.
[14] R.U. VERMA, RKKM mapping theorems and variational inequalities, Math. Proc. Royal Irish Acad., 98A(2) (1998), 131–138.
[15] R.U. VERMA, Generalized pseudocontractions and nonlinear variational inequalities, Publicationes Math. Debrecen, 33(1-2) (1998), 23–28.
[16] R.U. VERMA, An iterative algorithm for a class of nonlinear variational inequalities involving generalized pseudocontractions, Math. Sci. Res.
Hot-Line, 2(5) (1998), 17–21.
[17] R.U. VERMA, Strongly nonlinear quasivariational inequalities, Math. Sci.
Res. Hot-Line, 3(2) (1999), 11–18.
[18] R.U. VERMA, Approximation-solvability of nonlinear variational in- equalities involving partially relaxed monotone (prm) mappings, Adv.
Nonlinear Var. Inequal., 2(2) (1999), 137–148.
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Mappings Ram U. Verma
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[19] R.U. VERMA, An extension of a class of nonlinear quasivariational in- equality problems based on a projection method, Math. Sci. Res. Hot-Line, 3(5) (1999), 1–10.
[20] R.U. VERMA, A class of projection-contraction methods applied to monotone variational inequalities, Appl. Math. Lett., (to appear).
[21] R.U. VERMA, A new class of iterative algorithms for approximation- solvability of nonlinear variational inequalities, Computers Math. Appl., (to appear).
[22] E. ZEIDLER, Nonlinear Functional Analysis and its Applications I, Springer-Verlag, New York, 1986.
[23] D.L. ZHU AND P. MARCOTTE, Co-coercivity and its role in the con- vergence of iterative schemes for solving variational inequalities, SIAM J.
Optim., 6(3) (1996), 714–726.