Abstract
In a real Hilbert space, let the CFPP, VIP, and HFPP denote the common fixed-point problem of countable nonexpansive operators and asymptotically nonexpansive operator, variational inequality problem, and hierarchical fixed point problem, respectively. With the help of the Mann iteration method, a subgradient extragradient approach with a linear-search process, and a hybrid deepest-descent technique, we construct two modified Mann-type subgradient extragradient rules with a linear-search process for finding a common solution of the CFPP and VIP. Under suitable assumptions, we demonstrate the strong convergence of the suggested rules to a common solution of the CFPP and VIP, which is only a solution of a certain HFPP.
Keywords:
modified Mann-type subgradient extragradient rule; linear-search process; variational inequality problem; countable nonexpansive operators; strong convergence MSC:
47J25; 47J20; 47H10; 47H09
1. Introduction
Throughout this paper, we assume that is the metric projection of H onto C, with and denoting the inner product and induced norm of real Hilbert space H and C being a convex and closed set satisfying . Given nonlinear mapping , let the and indicate the fixed-point set of S and the real-number set, respectively. In the fixed point theory, we recall an important class of mappings. A self-mapping S on C is known as being asymptotically nonexpansive iff s.t. and
In particular, whenever , S is said to be nonexpansive. In the past several decades, the fixed point theory has played a key role in solving real-world problems such as the time-fractional biological population model [], fractional multi-dimensional system of boundary value problems on the methylpropane graph [], traumatic avoidance learning model [], and so forth.
Given a self-mapping A on H, we consider the classical variational inequality problem (VIP) of finding s.t. . Its solution set is written as VI(). To the best of our awareness, one of the most effective techniques for treating the VIP is the extragradient one put forward by Korpelevich [] in 1976, i.e., for any starting point , is fabricated below
where and L is Lipschitz constant of A. Whenever , the sequence converges weakly to a point in . At present, the vast literature on Korpelevich’s extragradient technique shows that many authors have paid great attention to it and enhanced this technique in different manners; for details, refer to [,,,,,,,,,,,,,,,,,,,,,,,] and references therein, to name but a few.
Very recently, Xie et al. [] suggested the amended inertial extragradient approach with a line-search process for solving the pseudomonotone VIP in H. Let be a contraction with constant and assume that . Given the sequences such that and . Their approach is formulated by Algorithm 1 below:
| Algorithm 1 Modified inertial extragradient approach (see []) |
Initial Step: Let , given any starting points in H. Iterations: Given the iterates , compute below: Step 1. Set . Step 2. Calculate and , where and is the smallest nonnegative integer m such that
If or , then stop and is an element of . Otherwise, go to Step 3. Step 3. Calculate . If , then . Again, set and go to Step 1. |
Under appropriate assumptions, they showed the strong convergence of to the solution provided . In the extragradient technique, two projections onto C have to be calculated per one iteration. In 2018, Thong and Hieu [] first proposed the inertial subgradient extragradient method, and then proved the weak convergence of this method to an element of under mild assumptions. In 2019, Thong and Hieu [] proposed the inertial-type subgradient extragradient method with a linear-search process for settling the VIP with monotone and Lipschitzian operator A and the fixed-point problem (FPP) of a quasi-nonexpansive operator S with the demiclosedness in H. Assume that . Given the sequences and . Their method is formulated by Algorithm 2 below:
| Algorithm 2 Inertial-type subgradient extragradient method (see []) |
Initial Step: Let , given any starting points in H. Iterations: Compute below: Step 1. Put and calculate , where is picked to be the largest s.t.
Step 2. Calculate with . Step 3. Calculate . If , then . Again, set and go to Step 1. |
Under suitable assumptions, it was proven in [] that converges weakly to a point in . Subsequently, Ceng and Shang [] proposed the hybrid inertial subgradient extragradient rule with a linear-search process for settling the VIP with Lipschitzian pseudomonotonicity operator A and the common fixed-point problem (CFPP) of finite nonexpansive operators and asymptotically nonexpansive operator S on H. Assume that with . Given a -contractive map with , and an operator of both -strong monotonicity and -Lipschitz continuity, fulfilling with . Let and s.t. . In addition, one writes for each , where the mod function takes values in , that is, whenever for some integers and , one has that in the case of and in the case of . Their rule is formulated by Algorithm 3 below:
| Algorithm 3 Hybrid inertial subgradient extragradient rule (see []) |
Initial Step: Let , given any starting points in H. Iterations: Compute below: Step 1. Put and calculate , with being picked to be the largest s.t.
Step 2. Calculate with . Step 3. Calculate . Again, set and go to Step 1. |
Under appropriate assumptions, it was proven in [] that, if , then converges strongly to if and only if and as , with being only a solution to the hierarchical fixed point problem (HFPP): .
In the rest of this paper, we always assume that the CFPP and HFPP denote the common fixed-point problem of countable nonexpansivity operators and asymptotical nonexpansivity operator and hierarchical fixed-point problem, respectively. With the help of the Mann iteration method, a subgradient extragradient approach with a linear-search process, and hybrid deepest-descent technique, we construct two amended Mann-type subgradient extragradient rules with a linear-search process for finding a common solution of the CFPP of and the VIP for pseudomonotone operator A. Via suitable conditions, we show the strong convergence of the proposed rules to a point in , which is only a solution of a certain HFPP. In the end, using the main results, we deal with the CFPP and VIP in an illustrated example.
The architecture of this paper is arranged as follows: In Section 2, we recollect certain concepts and basic tools for subsequent applications. In Section 3, we prove the strong convergence of the proposed rules. Finally, in Section 4, the main theorems are exploited to settle the CFPP and VIP in a demonstrated instance. Our rules are more general and more subtle than the above algorithms because they implicate settling the VIP for pseudomonotone operator and the CFPP for countable nonexpansive operators and an asymptotically nonexpansive operator. Our theorems ameliorate and develop the associated theorems pronounced in Xie et al. [], Ceng and Shang [], and Thong and Hieu [].
2. Preliminaries
Given a sequence , let (resp., ) represent the weak (resp., strong) convergence of to . A mapping is referred to as being
- (a)
- of L-Lipschitz continuity (or of L-Lipschitzian property) iff s.t. ;
- (b)
- of monotonicity iff ;
- (c)
- of pseudomonotonicity iff ;
- (d)
- of -strong monotonicity iff s.t. ;
- (e)
- of sequential weak continuity iff , the relation holds: .
Obviously, each monotonicity mapping is of pseudomonotonicity. However, the inverse is false. It is known that , (nearest point) s.t. . is refereed to as a nearest point (or metric) projection from H onto C. The statements below are valid (see []):
- (a)
- ;
- (b)
- ;
- (c)
- ;
- (d)
- ;
- (e)
- .
The following concept and two propositions can be found in [].
Definition 1.
Let and suppose that is a sequence of nonexpansive operators from C into itself. For any , the self-mapping on C is constructed as follows:
Then, is refereed to as a W-operator fabricated by and .
Proposition 1.
Let and suppose that is a sequence of nonexpansive operators from C into itself, such that . Then,
- (a)
- is of nonexpansivity and;
- (b)
- , exists;
- (c)
- the operator W, formulated as , is a nonexpansive operator s.t. , and it is refereed to as the W-operator fabricated by and .
Proposition 2.
Let for certain and suppose that is a sequence of nonexpansive operators from C into itself, such that . Then, for each bounded set .
Throughout this paper, we always assume that for some . Later on, we will make use of the following lemmas to demonstrate our main results.
Lemma 1
([]). Let and be two real Hilbert spaces. Suppose that is of uniform continuity on each boundedness subset of and D is of boundedness in . Then, is of boundedness.
It is clear that the relation below holds for the inner product in H:
Lemma 2
([]). Each Hilbert space fulfills Opial’s condition, that is, with , the relation is true.
Lemma 3
([]). Suppose that of both pseudomonotonicity and continuity, given . Then, the relation holds: .
Lemma 4
([]). Suppose that the sequence is such that , where the real sequences and satisfy the conditions: (a) and , and (b) or . Then, .
Lemma 5
([]). Let E be a Banach space and admit a duality mapping of weak continuity. Suppose that C is convex and closed such that , and that S is asymptotically nonexpansive self-mapping on C such that . Then, is demiclosed at zero, i.e., for satisfying both and , one has , with I being the identity operator of E.
The following lemmas are very crucial to the convergence analysis of our designed rules.
Lemma 6
([]). Suppose that is a sequence in , which does not decrease at infinity, that is, s.t. . The sequence of integers is formulated below:
where s.t. . Then, the statements hold below:
(a) and ;
(b) and .
Lemma 7
([]). Given a number λ in , suppose that S is a nonexpansive self-mapping on C, and is the operator formulated as , with being of both κ-Lipschitz continuity and η-strong monotonicity. Then, is a contractive map for , that is, , with .
3. Criteria of Strong Convergence
In what follows, let us suppose that the conditions are valid below.
is a sequence of nonexpansive operators on H and S is asymptotically nonexpansive operator on H with .
is the W-operator constructed by and , with for certain .
A is of both pseudomonotonicity and L-Lipschitz continuity on H, s.t. for each with .
g is a -contractive map on H with , and F is of -strong monotonicity and -Lipschitz continuity on H s.t. with .
where .
and with , s.t.
- (i)
- and ;
- (ii)
- and ;
- (iii)
- ;
- (iv)
- .
Lemma 8.
The linear-search process (6) in the following Algorithm 4 is well formulated, and the relation holds: .
Proof.
Lemma 9.
Suppose that the sequences are constructed in Algorithm 4. Then,
| Algorithm 4 The 1st modified Mann-type subgradient extragradient rule |
Initial Steps: Let , given any starting points in H. Iterations: Calculate below: Step 1. Set and , and calculate , with being picked to be the largest s.t.
Step 2. Calculate with . Step 3. Calculate
Put and return to Step 1. |
Proof.
It is clear that . Observe that ,
Thus, one has
Owing to , one has
Lemma 10.
Suppose that are boundedness sequences constructed in Algorithm 4. Assume that and . Then, , where .
Proof.
Take a fixed arbitrarily. Then, s.t. . Thanks to , we know that s.t. . In what follows, we claim . In fact, by Lemma 9, we obtain that, for each ,
Since and , from boundedness of , we deduce that
This immediately yields
Clearly, one has (due to ). Hence, we have
Noticing , we obtain , which immediately yields
Thus, it follows that
Since and are of boundedness, one obtains
We claim . Indeed, using the asymptotical nonexpansivity of S, one deduces that
Since , and , we obtain
In addition, let us show that . In fact, note that
where . Using Proposition 2, from (10), we obtain
□
In what follows, we claim . Indeed, noticing and , we have . In addition, noticing and , by the convexity and closedness of C, one obtains . Next, we discuss two situations. When , it is readily known that (due to ).
Let . Since as , using the hypothesis on A, one obtains . Hence, one might assume . Moreover, using , one has , and hence
Since A is uniform continuous, is of boundedness (by Lemma 1). Noticing the boundedness of , by Lemma 8 and (13), one obtains . In addition, it is readily known that . Note that and A is uniform continuous. Thus, one obtains . This hence arrives at .
In order to demonstrate , one chooses s.t. . For each l, one denotes by the smallest natural number satisfying
Note that is of decreasement. Thus, it is readily known that is an increasing. Using (owing to ), we set , and obtain . Thus, from (14), one obtains . In addition, by the pseudomonotonicity of A, one has . This immediately arrives at
We show that . In fact, from and , we obtain . Note that and . Thus, one deduces that . Therefore, one obtains . Note that A is uniformly continuous, the sequences are of boundedness, and . Consequently, letting , one concludes that . By Lemma 3, one has .
Next, we show that . In fact, since (11) guarantees , by Lemma 5, we obtain the demiclosedness of at zero. Thus, from , one obtains , that is, . In addition, we claim . Conversely, we suppose that , that is, . Using Lemma 2 and Proposition 1 (c), we obtain
which together with (12) yields , which leads to a contradiction. Thus, one has . Consequently, , that is, .
Theorem 1.
Suppose that is the sequence constructed in Algorithm 4. Then,
with being only a solution of the HFPP: .
Proof.
Because and , we might suppose that and for all n. Let us show that is the contractive map on H. Indeed, using Lemma 7, one has
This ensures that is a contractive map. Thus, it is readily known that there exists , which is only a fixed point of , that is, . That is, there exists , which is only a solution to the following VIP:
We first show the necessity of the theorem. In fact, when , we know that and
Since , one has
This immediately yields .
In what follows, we claim the sufficiency of the theorem. To the goal, under the assumption with , we divide the remainder of the proof into several claims. □
Claim 1.
One claims the boundedness of . In fact, picking a arbitrarily, one has that , , and (5) leads to
which hence yields
By the formulation of , one obtains
Noticing and , one obtains , which guarantees that s.t.
Therefore, one obtains the boundedness of . This ensures that , and are bounded.
Claim 2.
One claims that
for certain . In fact, one has
Using the convex property of , one obtains
In addition, from (23), we have
where for certain . From (25) and (26), one obtains
where for certain . Consequently,
Claim 3.
One claims that
for some . In fact, one has
Claim 4.
One claims that , which is only a solution to the HFPP: . In fact, using (29) with , one obtains
Putting , one demonstrates in both aspects below.
Aspect 1.
Suppose that ∃ (integer) s.t. is non-increasing. It is clear that the limit and . Setting , by (27) and one obtains
Noticing , and , one has
Thus, it follows that
Noticing and , we obtain
Since , and , using (31), one has
Moreover, noticing , we obtain from (23) that
This hence arrives at
Since , and , from the boundedness of , we infer that
Thus, it follows that
Since is bounded, we know that s.t.
Noticing the reflexivity of H and boundedness of , one might suppose that . Hence, using (35), we obtain
Note that (due to ). Thus, we obtain
Noticing and , from Lemma 10, one obtains . Thus, using (36) and (16), one has
which, together with (34), yields
Since , and
by the application of Lemma 4 to (30), one has .
Aspect 2.
Suppose that s.t. , with being the set of all natural numbers. The self-mapping on is formulated as
Using Lemma 6, one obtains
Using the similar arguments to those of Aspect 1, one obtains
and
Thus, . In addition, note that
Owing to , one obtains
This means that as .
In particular, when S is a nonexpansive operator, it is also asymptotically nonexpansive. In this case, the power in Algorithm 4 can be simplified into S. In this way, we can obtain the following Theorem 2.
Theorem 2.
Suppose that S is of nonexpansivity on H and is constructed in the modification of Algorithm 4, i.e., for any starting points in H,
with and being picked as in Algorithm 4. Then, , with being only a solution of the HFPP: .
Proof.
We first pick a arbitrarily. Obviously, the necessity holds. Next, it is sufficient to demonstrate the sufficiency. To this goal, under the condition , one divides the remainder of the proof into several claims. □
Claim 1.
One claims the boundedness of . In fact, using the similar inferences to those of Claim 1 in the proof of the above theorem, one obtains the claim.
Claim 2.
One claims that
for some . In fact, using the similar inferences to those of Step 2 in the proof of the above theorem, one obtains the claim.
Claim 3.
One claims that
for some . In fact, using the similar inferences to those of Claim 3 in the proof of the above theorem, one obtains the claim.
Claim 4.
One claims that , which is only a solution to the HFPP: . In fact, setting , by Claim 3, one obtains
Setting , one demonstrates in both aspects below.
Aspect 1.
Suppose that ∃ (integer) s.t. is non-increasing. Then, the limit and . Using the similar inferences to those of Aspect 1 of Claim 4 in the proof of the above theorem, one obtains
This hence arrives at
Since , and , from the boundedness of , we infer that
Therefore,
Again utilizing the similar inferences to those of Aspect 1 of Claim 4 in the proof of the above theorem, one obtains .
Aspect 2.
Suppose that s.t. , with being the set of all natural numbers. The self-mapping on is formulated as
From Lemma 6, one obtains
Finally, by the similar inferences to those of Aspect 2 of Claim 4 in the proof of the above theorem, one can obtain the claim.
On the other hand, we put forward another modification of a Mann-type subgradient extragradient rule.
It is worth mentioning that (9) and Lemmas 8–10 remain true for Algorithm 5:
| Algorithm 5 The 2nd modified Mann-type subgradient extragradient rule |
Initial Step: Let , given any starting points in H. Iterations: Compute below: Step 1. Set and , and calculate , with being picked to be the largest s.t.
Step 2. Calculate , where . Step 3. Calculate
Put and return to Step 1. |
Theorem 3.
Suppose that is the sequence constructed in Algorithm 5. Then,
with being only a solution of the HFPP: .
Proof.
By the similar inferences to those in the proof of the first theorem, one obtains that , which is only a solution of the HFPP: . Obviously, the necessity holds.
In what follows, one claims the sufficiency. To the goal, under the assumption with , one divides the claim of the sufficiency into several claims. □
Claim 1.
Therefore, we show the boundedness of . This ensures that the sequences are bounded.
Claim 2.
One claims that
for some —in fact, since
Using the same inferences as those of (24), one has
with for certain . In addition, using (19) and (20), one obtains
with for certain . Moreover, using (49), we deduce that
which, together with (9) and (50), leads to
where for certain . Thus, we obtain
Claim 3.
One claims that
for certain . In fact, one has
and hence
Claim 4.
One claims that , which is only a solution to the HFPP: . In fact, using (54) with , one obtains
Setting , one demonstrates in both aspects below.
Aspect 1.
Suppose that ∃ (integer) s.t. is non-increasing. Then, the limit and . Using (52) with and , one obtains
Noticing , and , one has
Hence, one obtains
Since and , we obtain
Moreover, noticing , we obtain from (49) that
This hence arrives at
Since , and , from the boundedness of , we infer that
Thus, it follows from Algorithm 5 that
Utilizing the same inferences as those of (38), one obtains
Since , and
Therefore, by the application of Lemma 4 to (55), one has .
Aspect 2.
Suppose that s.t. , with being the set of all natural numbers. The self-mapping on is formulated as
From Lemma 6, one obtains
Finally, by the similar inferences to those of Aspect 2 of Claim 4 in the proof of the first theorem, one can derive the claim.
In particular, when S is a nonexpansive operator, it is also asymptotically nonexpansive. In this case, the power in Algorithm 5 can be simplified into S. In this way, we can obtain the following Theorem 3.
Theorem 4.
Suppose that S is of nonexpansivity on H and is constructed in the modification of Algorithm 5, i.e., for any starting points in H,
with and being picked as in Algorithm 5. Then, , with being only a solution of the HFPP: .
Proof.
We first pick a arbitrarily. Obviously, the necessity holds. Next, it is sufficient to demonstrate the sufficiency. To the goal, under the condition , one divides the surplus of the proof into several claims. □
Claim 1.
One claims the boundedness of . In fact, using the similar inferences to those of Claim 1 in the proof of the third theorem, one obtains the claim.
Claim 2.
One claims that
for certain . In fact, using the similar inferences to those of Claim 2 in the proof of the third theorem, one obtains the claim.
Claim 3.
One claims that
for certain . In fact, using the similar inferences to those of Claim 3 in the proof of the third theorem, one obtains the claim.
Claim 4.
One claims that , which is only a solution to the HFPP: . In fact, setting , by Claim 3, one obtains
Putting , one shows in both aspects below.
Aspect 1.
Suppose that ∃ (integer) s.t. is non-increasing. Then, the limit and . Using the similar inferences to those of Aspect 1 of Claim 4 in the proof of the third theorem, one obtains
Since , and , from the boundedness of , we infer that
Therefore,
Again utilizing the similar inferences to those of Aspect 1 of Claim 4 in the proof of the third theorem, one obtains .
Aspect 2.
Suppose that s.t. , with being the set of all natural numbers. The self-mapping on is formulated as
Using Lemma 6, one obtains
Finally, by the similar inferences to those of Aspect 2 of Claim 4 in the proof of the third theorem, one can obtain the claim.
It is remarkable that, in comparison with the associated theorems in Xie et al. [], Ceng and Shang [], and Thong and Hieu [], our theorems ameliorate and develop them in the aspects below.
- (i)
- The issue for one to find a point in (see []) is developed into the issue for us to find a point in with both each being of nonexpansivity and being of asymptotical nonexpansivity. The modified inertial extragradient rule with a linear-search process for settling the VIP in [] is developed into our modified Mann-type subgradient extragradient rule with a linear-search process for settling the CFPP and VIP, which is on the basis of the Mann iteration method, subgradient extragradient approach with a linear-search process, and the hybrid deepest-descent technique.
- (ii)
- The issue for ones to find a point in with a quasi-nonexpansive operator S in [] is developed into the issue for us to find a point in with both being of nonexpansivity and being of asymptotical nonexpansivity. The inertial subgradient extragradient rule with a linear-search process for settling the VIP and FPP in [] is developed into our modified Mann-type subgradient extragradient rule with a linear-search process for settling the CFPP and VIP, which is on the basis of the Mann iteration method, subgradient extragradient approach with a linear-search process, and the hybrid deepest-descent technique.
- (iii)
- The issue for one to find a point in with finite nonexpansive operators (see []) is developed into the issue for us to find a point in with countable nonexpansive operators . The hybrid inertial subgradient extragradient rule with a linear-search process in [] is developed into our modified Mann-type subgradient extragradient rule with a linear-search process, e.g., the original inertial step is developed into the modified Mann iteration step: and . In addition, it was shown in [] that, under the condition , the relation holds:
In this paper, using Lemma 6, we show that, under the condition , the relation holds:
4. Implementability and Applicability of Rules
In what follows, we provide an illustrated instance to demonstrate the implementability and applicability of proposed rules. Put and . First, we construct an example of with , where is of both pseudomonotonicity and Lipschitz continuity, is of asymptotical nonexpansivity and each is of nonexpansivity. We put and use the and to denote its inner product and induced norm, respectively. Moreover, we set . The starting points are arbitrarily picked in . Let with
Let and be formulated by , and , respectively. We now claim that A is pseudomonotone and Lipschitz continuous. In fact, one has
This means that A is of Lipschitz continuity. In addition, one shows that A is of pseudomonotonicity. It can be readily seen that
Meanwhile, it is easily known that S is of asymptotical nonexpansivity with , such that as . Indeed, we observe that
and
It is clear that and
In addition, it is easy to see that is of nonexpansivity and . Thus, .
Example 1.
Noticing and , we rewrite Algorithm 4 as follows:
with and being picked as in Algorithm 4 for every n. Hence, using Theorem 1, one has that if and only if .
Example 2.
From the nonexpansivity of , one obtains the following modification of Algorithm 4:
with and being picked in the above way. Thus, using Theorem 2, one knows that if and only if .
Example 3.
Noticing and , we rewrite Algorithm 5 as follows:
with and being picked as in Algorithm 5 for every n. Hence, using Theorem 3, one has that if and only if .
Example 4.
From the nonexpansivity of , one obtains the following modification of Algorithm 5:
with and being picked in the above way. Thus, using Theorem 4, one knows that if and only if .
It is noteworthy that the above two modified Mann-type subgradient extragradient algorithms with a linear-search process (i.e., Algorithms 4 and 5) are both applied for finding a point in the common solution set with countable nonexpansive operators and asymptotically nonexpansive operator S. Under the same conditions imposed on the parameter sequences, we show the strong convergence of these two different algorithms to an element , which is also a unique solution of the HFPP: ; see Theorems 1 and 3 for more details. Note that Algorithm 4 is very similar to Algorithm 5 because these two different algorithms belong to the same class of modified Mann-type subgradient extragradient rules with a linear-search process. It is not difficult to find that Algorithm 4 is extended to develop Algorithm 5, e.g., (i) the original Mann iterative step in Algorithm 4 is developed into the modified Mann iterative step in Algorithm 5, and (ii) the original viscosity hybrid deepest-descent step in Algorithm 4 is developed into the modified viscosity hybrid deepest-descent step in Algorithm 5. In the above Examples 1 and 3, the iterative schemes (66) and (68) are numerical examples of Algorithms 4 and 5, respectively, and both are applied for finding . Compared with scheme (66), the scheme (68) improves and develops it in the following aspects:
- (i)
- (ii)
5. Conclusions
In real Hilbert spaces, we have designed two modified Mann-type subgradient extragradient rules with a linear-search process for settling the variational inequality problem (VIP) for a Lipschitz continuity and pseudomonotonicity operator A, and the common fixed-point problem (CFPP) for countable nonexpansivity operators and an asymptotical nonexpansivity operator . Under the lack of the sequential weak continuity and Lipschitz constant of the cost operator A, we have demonstrated the strong convergence of the constructed algorithms to a common element of the solution set of the VIP and the common fixed-point set of operators , which is only a solution of a certain hierarchical fixed-point problem (HFPP). In addition, an illustrated example is provided to demonstrate the implementability and applicability of our proposed rules.
It is worth pointing out that there are our contributions to the research area of finding a common solution of the VIP and CFPP in three aspects below:
First, we extend the problem considered in [], that is, the problem of finding a point in with finite nonexpansive operators is developed into the problem of finding a point in with countable nonexpansive operators .
Second, we improve the rules proposed in [], that is, the hybrid inertial subgradient extragradient rule with a linear-search process in [] is developed into our modified Mann-type subgradient extragradient rule with a linear-search process, e.g., the original inertial step is developed into the modified Mann iteration step: and .
Finally, we weaken the convergence criteria presented in []. Indeed, it was shown in [] that, under the condition , the relation holds:
In this article, using Lemma 6 (i.e., Maingé’s lemma []), we show that, under the condition , the relation holds:
In addition, it is worth mentioning that part of our future research is aimed at acquiring the strong convergence results for the modifications of our proposed rules with a Nesterov inertial extrapolation step and adaptive stepsizes.
Author Contributions
Conceptualization, F.-F.Z. and H.-Y.H.; Data curation, F.-F.Z.; Formal analysis, Y.-L.C., C.-S.W., J.-Y.L. and L.H.; Funding acquisition, L.-C.C.; Investigation, Y.-L.C., L.-C.C., F.-F.Z., C.-S.W., J.-Y.L., H.-Y.H. and L.H.; Methodology, H.-Y.H.; Project administration, L.-C.C.; Resources, Y.-L.C.; Software, C.-S.W. and J.-Y.L.; Supervision, L.-C.C.; Validation, L.H.; Writing—original draft, Y.-L.C. and L.-C.C.; Writing—review & editing, L.-C.C. All authors have read and agreed to the published version of the manuscript.
Funding
This research was supported by the 2020 Shanghai Leading Talents Program of the Shanghai Municipal Human Resources and Social Security Bureau (20LJ2006100), the Innovation Program of Shanghai Municipal Education Commission (15ZZ068) and the Program for Outstanding Academic Leaders in Shanghai City (15XD1503100).
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Rashid, S.; Ashraf, R.; Bonyah, E. On analytical solution of time-fractional biological population model by means of generalized integral transform with their uniqueness and convergence analysis. J. Funct. Spaces 2022, 2022, 7021288. [Google Scholar] [CrossRef]
- Rezapour, S.; Deressa, C.T.; Hussain, A.; Etemad, S.; George, R.; Ahmad, B. A theoretical analysis of a fractional multi-dimensional system of boundary value problems on the methylpropane graph via fixed point technique. Mathematics 2022, 10, 568. [Google Scholar] [CrossRef]
- Turab, A.; Sintunavarat, W. On the solution of the traumatic avoidance learning model approached by the Banach fixed point theorem. J. Fixed Point Theory Appl. 2020, 22, 12. [Google Scholar] [CrossRef]
- Korpelevich, G.M. The extragradient method for finding saddle points and other problems. Ekon. Mat. Metod. 1976, 12, 747–756. [Google Scholar]
- Yao, Y.; Liou, Y.C.; Kang, S.M. Approach to common elements of variational inequality problems and fixed point problems via a relaxed extragradient method. Comput. Math. Appl. 2010, 59, 3472–3480. [Google Scholar] [CrossRef] [Green Version]
- Jolaoso, L.O.; Shehu, Y.; Yao, J.C. Inertial extragradient type method for mixed variational inequalities without monotonicity. Math. Comput. Simul. 2022, 192, 353–369. [Google Scholar] [CrossRef]
- Ceng, L.C.; Petrusel, A.; Yao, J.C.; Yao, Y. Hybrid viscosity extragradient method for systems of variational inequalities, fixed points of nonexpansive mappings, zero points of accretive operators in Banach spaces. Fixed Point Theory 2018, 19, 487–501. [Google Scholar] [CrossRef]
- Ceng, L.C.; Petrusel, A.; Qin, X.; Yao, J.C. Two inertial subgradient extragradient algorithms for variational inequalities with fixed-point constraints. Optimization 2021, 70, 1337–1358. [Google Scholar] [CrossRef]
- Xie, Z.; Cai, G.; Li, X.; Dong, Q.L. Strong convergence of the modified inertial extragradient method with line-search process for solving variational inequality problems in Hilbert spaces. J. Sci. Comput. 2021, 88, 19. [Google Scholar] [CrossRef]
- Yao, Y.; Shahzad, N.; Yao, J.C. Convergence of Tseng-type self-adaptive algorithms for variational inequalities and fixed point problems. Carpathian J. Math. 2021, 37, 541–550. [Google Scholar] [CrossRef]
- He, L.; Cui, Y.L.; Ceng, L.C.; Zhao, T.Y.; Wang, D.Q.; Hu, H.Y. Strong convergence for monotone bilevel equilibria with constraints of variational inequalities and fixed points using subgradient extragradient implicit rule. J. Inequal. Appl. 2021, 2021, 37. [Google Scholar] [CrossRef]
- Zhao, T.Y.; Wang, D.Q.; Ceng, L.C.; He, L.; Wang, C.Y.; Fan, H.L. Quasi-inertial Tseng’s extragradient algorithms for pseudomonotone variational inequalities and fixed point problems of quasi-nonexpansive operators. Numer. Funct. Anal. Optim. 2020, 42, 69–90. [Google Scholar] [CrossRef]
- Denisov, S.V.; Semenov, V.V.; Chabak, L.M. Convergence of the modified extragradient method for variational inequalities with non-Lipschitz operators. Cybern. Syst. Anal. 2015, 51, 757–765. [Google Scholar] [CrossRef]
- Cai, G.; Shehu, Y.; Iyiola, O.S. Strong convergence results for variational inequalities and fixed point problems using modified viscosity implicit rules. Numer. Algorithms 2018, 77, 535–558. [Google Scholar] [CrossRef]
- Yang, J.; Liu, H.; Liu, Z. Modified subgradient extragradient algorithms for solving monotone variational inequalities. Optimization 2018, 67, 2247–2258. [Google Scholar] [CrossRef]
- Vuong, P.T. On the weak convergence of the extragradient method for solving pseudo-monotone variational inequalities. J. Optim. Theory Appl. 2018, 176, 399–409. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Thong, D.V.; Hieu, D.V. Inertial subgradient extragradient algorithms with line-search process for solving variational inequality problems and fixed point problems. Numer. Algorithms 2019, 80, 1283–1307. [Google Scholar] [CrossRef]
- Shehu, Y.; Iyiola, O.S. Strong convergence result for monotone variational inequalities. Numer. Algorithms 2019, 76, 259–282. [Google Scholar] [CrossRef]
- Thong, D.V.; Dong, Q.L.; Liu, L.L.; Triet, N.A.; Lan, N.P. Two fast converging inertial subgradient extragradient algorithms with variable stepsizes for solving pseudo-monotone VIPs in Hilbert spaces. J. Comput. Appl. Math. 2022, 410, 19. [Google Scholar] [CrossRef]
- Vuong, P.T.; Shehu, Y. Convergence of an extragradient-type method for variational inequality with applications to optimal control problems. Numer. Algorithms 2019, 81, 269–291. [Google Scholar] [CrossRef]
- Shehu, Y.; Dong, Q.L.; Jiang, D. Single projection method for pseudo-monotone variational inequality in Hilbert spaces. Optimization 2019, 68, 385–409. [Google Scholar] [CrossRef]
- Thong, D.V.; Hieu, D.V. Modified subgradient extragradient method for variational inequality problems. Numer. Algorithms 2018, 79, 597–610. [Google Scholar] [CrossRef]
- Kraikaew, R.; Saejung, S. Strong convergence of the Halpern subgradient extragradient method for solving variational inequalities in Hilbert spaces. J. Optim. Theory Appl. 2014, 163, 399–412. [Google Scholar] [CrossRef]
- Ceng, L.C.; Wen, C.F. Systems of variational inequalities with hierarchical variational inequality constraints for asymptotically nonexpansive and pseudocontractive mappings. Rev. R. Acad. Cienc. Exactas Fís. Nat. Ser. A Mat. Racsam 2019, 113, 2431–2447. [Google Scholar] [CrossRef]
- Ceng, L.C.; Shang, M.J. Hybrid inertial subgradient extragradient methods for variational inequalities and fixed point problems involving asymptotically nonexpansive mappings. Optimization 2021, 70, 715–740. [Google Scholar] [CrossRef]
- Ceng, L.C.; Petrusel, A.; Qin, X.; Yao, J.C. Pseudomonotone variational inequalities and fixed points. Fixed Point Theory 2021, 22, 543–558. [Google Scholar] [CrossRef]
- Reich, S.; Thong, D.V.; Dong, Q.L.; Li, X.H.; Dung, V.T. New algorithms and convergence theorems for solving variational inequalities with non-Lipschitz mappings. Numer. Algorithms 2021, 87, 527–549. [Google Scholar] [CrossRef]
- Iusem, A.N.; Nasri, M. Korpelevich’s method for variational inequality problems in Banach spaces. J. Global Optim. 2011, 50, 59–76. [Google Scholar] [CrossRef]
- Goebel, K.; Reich, S. Uniform Convexity, Hyperbolic Geometry, and Nonexpansive Mappings; Marcel Dekker: New York, NY, USA, 1984. [Google Scholar]
- Chang, S.S.; Lee, H.W.J.; Chan, C.K. A new method for solving equilibrium problem fixed point problem and variational inequality problem with application to optimization. Nonlinear Anal. 2009, 70, 3307–3319. [Google Scholar] [CrossRef]
- Opial, Z. Weak convergence of the sequence of successive approximations for nonexpansive mappings. Bull. Am. Math. Soc. 1967, 73, 591–597. [Google Scholar] [CrossRef] [Green Version]
- Xu, H.K.; Kim, T.H. Convergence of hybrid steepest-descent methods for variational inequalities. J. Optim. Theory Appl. 2003, 119, 185–201. [Google Scholar] [CrossRef]
- Ceng, L.C.; Xu, H.K.; Yao, J.C. The viscosity approximation method for asymptotically nonexpansive mappings in Banach spaces. Nonlinear Anal. 2008, 69, 1402–1412. [Google Scholar] [CrossRef]
- Maingé, P.E. Strong convergence of projected subgradient methods for nonsmooth and nonstrictly convex minimization. Set-Valued Anal. 2008, 16, 899–912. [Google Scholar] [CrossRef]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).