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Article

A Nonlinear System of Generalized Ordered XOR-Inclusion Problem in Hilbert Space with S-Iterative Algorithm

1
Department of Engineering Mathematics, College of Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram 522302, Andhra Pradesh, India
2
Department of Mathematics and Sciences, College of Arts and Applied Sciences, Dhofar University, Salalah 211, Oman
3
Department of Mathematics, School of Advanced Sciences, Kalasalingam Academy of Research and Education, Krishnankoil 626126, Tamil Nadu, India
4
Department of Mathematics, Zhejiang Normal University, Jinhua 321004, China
*
Author to whom correspondence should be addressed.
Mathematics 2023, 11(6), 1434; https://doi.org/10.3390/math11061434
Submission received: 14 February 2023 / Revised: 5 March 2023 / Accepted: 14 March 2023 / Published: 16 March 2023

Abstract

:
In this article, a nonlinear system of generalized ordered XOR-inclusion problems in Hilbert space is introduced and studied. Initially, we define the resolvent operator related to the ( α , λ ) -XOR-weak-ANODD multivalued mapping. Using the fixed point technique, we demonstrate the results of existence. In order to make the suggested system more realistic, we create the S-iterative algorithm and demonstrate that the sequence generated through this technique strongly converges with the proposed system’s solution. One example is provided in support of the existence result as well.

1. Introduction

In recent decades, the variational inclusion problems have been extended and generalized in various directions by using novel and innovative techniques. One useful and important form of inclusion problem is the set-valued inclusion problem. Many problems related to control theory, game theory, optimization economics applied sciences, etc. can be constructed in terms of set-valued inclusion problem 0 M ( x ) , for a given set-valued mapping M in Hilbert space. For more details, we refer to [1,2,3,4,5] and references therein. A system of variational inequalities (inclusions), which is a natural generalization of variational inequalities, was taken into consideration and researched by many mathematicians as [6,7,8] and reference therein.
In 1972, Amann [9] introduced a technique for finding the number of solutions of nonlinear equations in ordered Hilbert spaces and Banach spaces. The applications of nonlinear equations involving nonlinear increasing operators were investigated by Du [10] and Srivastava et al. [11,12,13]. A large amount of literature is available related to ordered inequalities (inclusions) problems in arbitrarily ordered spaces. In 2008, Li and his coauthors [14] introduced and studied ordered variational inequalities (inclusion) with XOR-operations. Generally, XOR-operation is applicable in parity checks, neural networks, controlled inverters, binary to gray/gray to binary conversion, combinational logic circuits, etc. A lot of work related to ordered inclusions problem with XOR-operation can be found in [15,16,17,18,19,20,21,22].
In 2021, Ahmad and his coauthors introduced a nonlinear system of Mixed ordered variational inclusions with XOR-operation [23]. Inspired by the aforementioned work. In this article, we consider a system of nonlinear ordered XOR-inclusion problems in an ordered Hilbert space.
The paper is designed in the following way.
In Section 2, we have presented some prerequisites that we are needed to achieve our goal. In Section 3, we formulate our problem and prove an existence result by using the resolvent operator technique. In Section 4, we develop the S-iterative algorithm for the considered system and show the convergence of the sequence generated by S-iterative algorithm. In the last section, we have presented the conclusion of our work.

2. Prerequisites

Throughout this article, we assume H to be a real ordered positive Hilbert space with the norm . H and inner product · , · H × H , the metric d induced by the norm . H , 2 H (respectively, C B ( H ) ) the nonempty collection of (respectively, closed and bounded) subsets of H , and the Hausdorff metric H ( . , . ) on C B ( H ) , is defined as:
H ( A , B ) = max { sup s A d ( s , B ) , sup t B d ( A , t ) } , A , B C B ( H ) ,
where d ( s , B ) = inf t B { s t } and d ( A , t ) = inf s A { s t } .
Definition 1
([22,24]). Let ϕ P H be closed convex subset of H . Then P is called
(i)
a cone if for any s P and any λ > 0 ,   λ s P ,
(ii)
pointed cone if s P and s P , then s = 0 .
Definition 2
([22,24]). Let P be the cone, then
(i)
P is called a normal cone if ∃ a constant λ P > 0 such that 0 s t implies s H λ P t H , s , t H ,
(ii)
for any s , t H , s t if and only if t s P ,
(iii)
s and t are said to be comparative to each other if either s t or t s holds and is denoted by s t .
Definition 3
([22,24]). For all s , t H , let l u b { s , t } denotes least upper bound and g l b { s , t } denotes greatest lower bound of the set { s , t } . Suppose l u b { s , t } and g l b { s , t } for the set { s , t } exists, then we define binary operations as below:
(i)
s t = l u b { s , t } ,
(ii)
s t = g l b { s , t } ,
(iii)
s t = ( s t ) ( t s ) ,
(iv)
s t = ( s t ) ( t s ) .
The operations , , andare called OR, AND, XOR and XNOR operations, respectively.
Proposition 1
([15,22]). Let ⊕ be an XOR-operation andbe an XNOR-operation. Then the following holds:
(i)
s t = 0 , s t = t s = ( s t ) = ( t s ) ,
(ii)
if s 0 , then s 0 s s 0 ,
(iii)
( λ s ) ( λ t ) = | λ | ( s t ) ,
(iv)
0 s t , if s t ,
(v)
if s t , then s t = 0 if and only if s = t ,
(vi)
( s + t ) ( u + v ) ( s u ) + ( t v ) ,
(vii)
( s + t ) ( u + v ) ( s v ) + ( t u ) ,
(viii)
if s , t and w are comparable to each other, then ( s t ) ( s w ) + ( w t ) ,
(ix)
if s , t and w are comparable to each other, then [ ( w s ) ( w t ) ] = ( s t ) ,
(x)
α s β s = | α β | s = ( α β ) s , if s 0 , s , t , u , v , w H and α , β , λ R .
Proposition 2
([15,22]). Let P be a normal cone with normal constant λ P in H , then for each s , t H , the following hold:
(i)
0 0   =   0   = 0 ,
(ii)
s t     s t     s + t ,
(iii)
s t     s t     λ P s t ,
(iv)
if s t , then s t   =   s t .
Definition 4
([15,22]). A single-valued mapping A : H H is said to be
(i)
a comparison mapping if for each s , t H and s t then A ( s ) A ( t ) ,   s A ( s ) and t A ( t ) ,
(ii)
strongly comparison mapping if A is a comparison mapping and A ( s ) A ( t ) if and only if s t , for any s , t H ,
(iii)
β-ordered compression mapping if A is a comparison mapping and
A ( s ) A ( t ) β ( s t ) , f o r β ( 0 , 1 ) a n d s , t H .
Definition 5.
Let f , g : H H be strongly comparison single-valued mappings. Then, the mapping P : H × H H is said to be
(i)
γ P f -ordered compression mapping in the first argument with respect to f if there exists a constant γ P f > 0 such that
P ( f ( s ) , . ) P ( f ( t ) , . ) γ P f ( s t ) ,
(ii)
ξ P g -ordered compression mapping in the second argument with respect to g if there exists a constant γ P g > 0 such that
P ( . , g ( s ) ) P ( . , g ( t ) ) ξ P g ( s t ) .
Definition 6
([15,22]). Let F : H 2 H be a multi-valued mapping and A : H H be a single-valued mapping. Then
(i)
F is said to be H -Lipschitz-type-continuous if for any s , t H , s t , there exists a constant λ H F > 0 such that
H ( F ( s ) , F ( t ) ) λ H F s t ,
(ii)
F is said to be a comparison mapping if for any v s F ( t ) , s v s , and if s t , then for v s F ( s ) and v t F ( t ) , v s v t , s , t H ,
(iii)
a comparison mapping F is said to be α A -non-ordinary difference mapping with respect to A if for each s , t H , v s F ( s ) and v t F ( t ) such that
( v s v t ) α A ( A ( s ) A ( t ) ) = 0 ,
(iv)
a comparison mapping F is said to be λ- X O R -ordered different weak comparison mapping with respect to A, if s t , thena constant λ > 0 such that
λ ( v s v t ) s t , s , t H , v s F ( A ( s ) ) , v t F ( A ( t ) ) ,
(v)
F is said to be a ( α A , λ ) -XOR-weak-ANODD mapping, if F is a α A -weak-non-ordinary difference mapping with respect to A, λ-XOR-ordered different weak comparison mapping with respect to A and [ A λ F ] ( H ) = H .
Definition 7
([23]). Let F : H 2 H be a ( α A , λ ) -XOR-weak-ANODD multi-valued mapping with respect to the strongly comparison and β-ordered compression mapping A : H H . Then the resolvent operator R λ , F A : H H associated with A and F is defined by
R λ , F A ( s ) = [ A λ F ] 1 ( s ) , s H ,
where  α A , λ > 0 , a n d β ( 0 , 1 ) .
Proposition 3
([22,23]). Let F : H 2 H be a ( α A , λ ) -XOR-weak-ANODD multi-valued mapping with respect to the strongly comparison and β-ordered compression mapping A : H H such that α A λ > β . Then the resolvent operator R λ , F A : H H is well defined and single value for α λ > 0 and β ( 0 , 1 ) .
Proposition 4
([22,23]). Let F : H 2 H be a ( α A , λ ) -XOR-weak-ANODD multi value mapping with respect to R λ , F A . Let A : H H be the strongly comparison and β-ordered compression mapping with respect to R λ , F A for μ 1 and α A λ > β . Then, R λ , F A is a comparison mapping and satisfies the condition
R λ , F A ( s ) R λ , F A ( t ) μ ( λ α A β ) ( s t ) , s , t H ,
i.e., the resolvent operator R λ , F A is Lipschitz-type-continuous.

3. Problem Formulation Furthermore, Existence of Solution

Throughout, in rest portion of this article, we assume for κ N , i = 1 , 2 , , κ . Let A i , f i , g i : H H and P i : H × H H be single valued mappings. Suppose F i : H 2 H are ( α A i , λ i ) -XOR-weak-ANODD multi-valued mapping and M i , N i : H C B ( H ) are closed and bounded multi-valued mappings. Then, the problem of finding ( x 1 , , x κ ) H × × H κ - times , ( u 1 , , u k ) M 1 ( x 1 ) × × M κ ( x κ ) and ( v 1 , , v k ) N 1 ( x 1 ) × × N κ ( x κ ) such that
ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) F 1 ( u 1 , v 2 ) , ω 2 P 2 ( f 2 , ( x 2 ) , g 3 ( x 3 ) ) F 2 ( u 2 , v 3 ) , ω κ P κ ( f κ ( x κ ) , g 1 ( x 1 ) ) F κ ( u κ , v 1 ) ,
holds, for some ω ^ = ( ω 1 , ω κ ) H × × H κ - times , is called a nonlinear system of generalized ordered XOR-inclusion problems. By suitable assumptions of mappings involving in system (3), one can obtain many existing problems like [25]. Some of them are mentioned here.
Special Cases:
  • For i = 1 , 2 . If we define N i = g i = I (the identity operator on H ), M i = h i and ⊕ is replaced by +, then the System (3) reduces to the system of finding ( x , y ) H × H such that
    ω 1 P 1 ( f 1 ( x ) , y ) + F 1 ( h 1 ( x ) , y ) , ω 2 P 2 ( f 2 ( y ) , x ) + F 2 ( h 2 ( y ) , x ) ,
    for some ( ω 1 , ω 2 ) H × H . System (4) is introduced and studied by [26].
  • For i = 1 , 2 , if we define P 1 ( f 1 ( x ) , y ) = S ( x f 1 ( x ) , y ) + C A , λ M ( x ) , P 2 ( f 2 ( y ) , x ) = T ( x , y f 2 ( y ) ) + C A , λ N ( y ) F 1 ( u 1 ( x ) , v 2 ( y ) ) = M ( x ) a n d F 2 ( u 2 ( x ) , v 1 ( y ) ) = N ( y ) , then for ω i = 0 , i ,  the system (3) reduces into the System of Multi-Valued Mixed Variational Inclusions with XOR-Operation; that is, the problem of finding ( x , y ) H × H , u M ( x ) and v N such that
    0 S ( x f 1 ( x ) , y ) + C A , λ M ( x ) M ( x ) , 0 T ( x , y f 2 ( y ) ) + C A , λ N ( y ) N ( y ) ,
    hold. The system (5) studied by [27].
The fixed point formulation for the nonlinear system of generalized ordered XOR -inclusion problems is the following lemma.
Lemma 1.
The triplets ( x , u , v ) , i.e., x = ( x 1 , , x κ ) H × × H , u = ( u 1 , , u k ) M 1 ( x 1 ) × × M κ ( x κ ) and v = ( v 1 , , v k ) N 1 ( x 1 ) × × N κ ( x κ ) is a solution of system (3) if and only if the following equations hold:
x 1 = R λ 1 , F 1 ( u 1 , v 2 ) A 1 A 1 ( x 1 ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) } , x 2 = R λ 2 , F 2 ( u 2 , v 3 ) A 2 A 2 ( x 2 ) + λ 2 { ω 2 P 2 ( f 2 ( x 2 ) , g 3 ( x 3 ) ) } , x κ = R λ κ , F κ ( u κ , v 1 ) A κ A κ ( x κ ) + λ κ { ω κ P κ ( f κ ( x κ ) , g 1 ( x 1 ) ) } .
hold, where λ i s > 0 are constants.
Proof. 
Utilizing Definition 7 of the resolvent operator, the proof is simple and easily achieved.
Under some reasonable assumptions, the existence of the solution to system (3) is demonstrated by the following theorem.    □
Theorem 1.
For ı = 1 , 2 , , κ , κ N a n d   w e   s e t κ + 1 = 1 , let A i , f i , g i : H H be single value mappings such that A i s are β A i -ordered compression mapping and f i , g i be strongly comprasion mappings. Assume that P i : H × H H is single value mapping such that P i is γ P i f i -ordered compression in first argument with respect to f i and ξ P i g i -ordered compression in second argument with respect to g i , respectively. Suppose F i : H 2 H is a ( α A i , λ i ) -XOR-weak-ANODD multi-value mapping and M i , N i : H C B ( H ) are H -Lipschitz continuous with constants λ H M i and λ H N i , respectively.
Furthermore, if  x i x i + 1 f i ( x i ) f i ( x i + 1 ) , g i ( x i ) g i ( x i + 1 ) , R λ i , F i ( u i , v i + 1 ) A i ( x i ) R λ i , F i ( u i , v i + 1 ) A i ( y i ) and for all constants λ 1 , λ 2 , , λ κ , 1 Λ 2 , 2 Λ 3 , , κ Λ 1 > 0 , the following relations hold:
R λ i , F i ( u i , v i + 1 ) A i ( x i ) R λ i , F i ( u i , v i + 1 ) A i ( x i ) i Λ i + 1 ( u i u i + v i + 1 v i + 1 ) , f o r e a c h i ,
and
Θ 1 ( β A 1 + λ 1 γ g 1 f 1 ) + ϵ 1 ( 1 Λ 2 λ H M 1 + 1 Λ 2 λ H N 2 ) < 1 λ C Θ κ λ κ ξ P κ g 1 , Θ 2 ( β A 2 + λ 2 γ g 2 f 2 ) + ϵ 2 ( 2 Λ 3 λ H M 2 + 2 Λ 3 λ H N 3 ) < 1 λ C Θ 1 λ 1 ξ P 1 g 2 , Θ κ ( β A κ + λ κ γ g κ f κ ) + ϵ κ ( κ Λ 1 λ H M κ + κ Λ 1 λ H N 1 ) < 1 λ C Θ κ 1 λ κ 1 ξ P κ g κ ,
where
Θ i = μ i λ i α A i β A i .
Proof. 
We define the mapping B : H × × H κ - times H × × H κ - times by
B ( x 1 , , x κ ) : = ( B 1 ( x 1 , x 2 ) , , B κ ( x κ , x 1 ) ) , ( x 1 , , x κ ) H × × H κ - times ,
where B i : H × H H are mappings defined as
B 1 ( x 1 , x 2 ) = R λ 1 , F 1 ( u 1 , v 2 ) A 1 A 1 ( x 1 ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) } , B 2 ( x 2 , x 3 ) = R λ 2 , F 2 ( u 2 , v 3 ) A 2 A 2 ( x 2 ) + λ 2 { ω 2 P 2 ( f 2 ( x 2 ) , g 3 ( x 3 ) ) } , B κ ( x κ , x 1 ) = R λ κ , F κ ( u κ , v 1 ) A κ A κ ( x κ ) + λ κ { ω κ P κ ( f κ ( x κ ) , g 1 ( x 1 ) ) } .
For any x i , y i H , u i M i ( x i ) , v i N i ( x i ) such that x i x j , y i y j , u i u j v i v j and using Proposition 1, we have
0 B 1 ( x 1 , x 2 ) B 1 ( y 1 , y 2 ) = R λ 1 , F 1 ( u 1 , v 2 ) A 1 A 1 ( x 1 ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) } R λ 1 , F 1 ( u 1 , v 2 ) A 1 A 1 ( y 1 ) + λ 1 { ω 1 P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) } .
Using the Proposition 1, Proposition 4,  (7) and the compression of A 1 , we have
0 B 1 ( x 1 , x 2 ) B 1 ( y 1 , y 2 ) Θ 1 [ A 1 ( x 1 ) A 1 ( y 1 ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) } λ 1 { ω 1 P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) } ] + 1 Λ 2 ( u 1 u 1 + v 2 v 2 ) Θ 1 β A 1 ( x 1 y 1 ) + λ 1 ( P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) ) + 1 Λ 2 ( u 1 u 1 + v 2 v 2 ) .
By using the normal cone definition and (9), we have
B 1 ( x 1 , x 2 ) B 1 ( y 1 , y 2 ) λ P B 1 ( x 1 , x 2 ) B 1 ( y 1 , y 2 ) λ P [ Θ 1 β A 1 x 1 y 1 + Θ 1 λ 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) + 1 Λ 2 [ u 1 u 1 + v 2 v 2 ] ] .
Using ( v i i i ) of Proposition 1, we calculate
P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) P 1 ( f 1 ( x 1 ) , g 2 ( y 2 ) ) + P 1 ( f 1 ( x 1 ) , g 2 ( y 2 ) ) P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) .
Since P 1 is γ P 1 f 1 -ordered compression mapping in the first argument with respect to f 1 and ξ P 1 g 2 -ordered compression mapping in the second argument with respect to g 2 , we have
P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) γ P 1 f 1 x 1 y 1 + ξ P 1 g 2 x 2 y 2 .
Since u 1 M 1 ( x 1 ) ,   v 2 N 2 ( x 2 ) , by Nadler [28], ∃ u 1 M 1 ( y 1 ) , v 2 N 2 ( y 2 ) such that
1 Λ 2 u 1 u 1 + 1 Λ 2 v 2 v 2 1 Λ 2 ϵ 1 H ( M 1 ( x 1 ) , M 1 ( y 1 ) ) + 1 Λ 2 ϵ 2 H ( N 2 ( x 2 ) , N 2 ( y 2 ) ) .
Using H -Lipschitz continuity of M 1 and N 2 , we obtain
1 Λ 2 u 1 u 1 + 1 Λ 2 v 2 v 2 1 Λ 2 [ ϵ 1 λ H M 1 x 1 y 1 + ϵ 2 λ H N 2 x 2 y 2 ] .
Using (12), (14) and Proposition 1 in (10), we get
B 1 ( x 1 , x 2 ) B 1 ( y 1 , y 2 ) λ P [ Θ 1 β A 1 x 1 y 1 + Θ 1 λ 1 [ γ P 1 f 1 x 1 y 1 + ξ P 1 g 2 x 2 y 2 ] + 1 Λ 2 [ ϵ 1 λ H M 1 x 1 y 1 + ϵ 2 λ H N 2 x 2 y 2 ] ] = λ P [ ( Θ 1 β A 1 + Θ 1 λ 1 γ P 1 f 1 + 1 Λ 2 ϵ 1 λ H M 1 ) x 1 y 1 + ( Θ 1 λ 1 ξ P 1 g 2 + 1 Λ 2 ϵ 2 λ H N 2 ) x 2 y 2 ] .
For any x i , y i H , u 3 M 3 ( x 3 ) , v 3 N 3 ( x 3 ) such that x i x j , y i y j , u i u j v i v j and using Proposition 1, we have
0 B 2 ( x 2 , x 3 ) B 2 ( y 2 , y 3 ) = R λ 2 , F 2 ( u 2 , v 3 ) A 2 A 2 ( x 2 ) + λ 2 { ω 2 P 2 ( f 2 ( x 2 ) , g 3 ( x 3 ) ) } R λ 2 , F 2 ( u 2 , v 3 ) A 2 A 2 ( y 2 ) + λ 2 { ω 2 P 2 ( f 2 ( y 2 ) , g 3 ( y 3 ) ) } .
Using the Proposition 1, Proposition 4,  (7) and the compression of A 2 , we have
0 B 2 ( x 2 , x 3 ) B 2 ( y 2 , y 3 ) Θ 2 [ A 2 ( x 2 ) A 2 ( y 2 ) + λ 2 { ω 2 P 2 ( f 2 ( x 2 ) , g 3 ( x 3 ) ) } λ 2 { ω 2 P 2 ( f 2 ( y 2 ) , g 3 ( y 3 ) ) } ] + 2 Λ 3 ( u 2 u 2 + v 3 v 3 ) Θ 2 β A 2 ( x 2 y 2 ) + λ 2 ( P 2 ( f 2 ( x 2 ) , g 3 ( x 3 ) ) P 2 ( f 2 ( y 2 ) , g 3 ( y 3 ) ) ) + 2 Λ 3 ( u 2 u 2 + v 3 v 3 ) .
Using Proposition 2 and (16), we have
B 2 ( x 2 , x 3 ) B 2 ( y 2 , y 3 ) λ P B 2 ( x 2 , x 3 ) B 2 ( y 2 , y 3 ) λ P [ Θ 2 β A 2 x 2 y 2 + Θ 2 λ 2 P 2 ( f 2 ( x 2 ) , g 3 ( x 3 ) ) P 2 ( f 2 ( y 2 ) , g 3 ( y 3 ) ) + 2 Λ 3 [ u 2 u 2 + v 3 v 3 ] ] .
Since P 2 is γ P 2 f 2 -ordered compression mapping in the first argument with respect to f 2 and ξ P 2 g 3 -ordered compression mapping in the second argument with respect to g 3 . Hence, importing the same logic as in (11) for (12), we have
P 2 ( f 2 ( x 2 ) , g 3 ( x 3 ) ) P 2 ( f 2 ( y 2 ) , g 3 ( y 3 ) ) γ P 2 f 2 x 2 y 2 + ξ P 2 g 3 x 3 y 3 .
Similarly,
2 Λ 3 u 2 u 2 + 2 Λ 3 v 3 v 3 2 Λ 3 [ ϵ 2 λ H M 2 x 2 y 2 + ϵ 3 λ H N 3 x 3 y 3 ] .
Using (18),  (19) and Proposition 1 in (17), we obtain
B 2 ( x 2 , x 3 ) B 2 ( y 2 , y 3 ) λ P [ Θ 2 β A 2 x 2 y 2 + Θ 2 λ 2 [ γ P 2 f 2 x 2 y 2 + ξ P 2 g 2 x 3 y 3 ] + 2 Λ 3 [ ϵ 2 λ H M 2 x 2 y 2 + ϵ 3 λ H N 3 x 3 y 3 ] ] = λ P [ ( Θ 2 β A 2 + Θ 2 λ 2 γ P 2 f 2 + 2 Λ 3 ϵ 2 λ H M 2 ) x 2 y 2 + ( Θ 2 λ 2 ξ P 2 g 3 + 2 Λ 3 ϵ 3 λ H N 3 ) x 3 y 3 .
Continuing in this way, for any x i , y i H , u κ M κ ( x κ ) , v 1 N 1 ( x 1 ) such that x i x j , y i y j , u i u j v i v j and using Proposition 1, we have
0 B κ ( x κ , x 1 ) B κ ( y κ , y 1 ) = R λ κ , F κ ( u κ , v 1 ) A κ A κ ( x κ ) + λ κ { ω κ P κ ( f κ ( x κ ) , g 1 ( x 1 ) ) } R λ κ , F κ ( u κ , v 1 ) A κ A κ ( y κ ) + λ κ { ω κ P κ ( f κ ( y κ ) , g 1 ( y 1 ) ) } .
Using the Proposition 4,  (7) and the compression of A κ , we have
0 B κ ( x κ , x 1 ) B κ ( y κ , y 1 ) Θ κ [ A κ ( x κ ) A κ ( y κ ) + λ κ { ω κ P κ ( f κ ( x κ ) , g 1 ( x 1 ) ) } λ κ { ω κ P κ ( f κ ( y κ ) , g 1 ( y 1 ) ) } ] + κ Λ 1 ( u κ u κ + v 1 v 1 ) Θ κ β A κ ( x κ y κ ) + λ κ ( P κ ( f κ ( x κ ) , g 1 ( x 1 ) ) P κ ( f κ ( y κ ) , g 1 ( y 1 ) ) ) + κ Λ 1 ( u κ u κ + v 1 v 1 ) .
Using Proposition 2 and (21), we have
B κ ( x κ , x 1 ) B κ ( y κ , y 1 ) λ P B κ ( x κ , x 1 ) B κ ( y κ , y 1 ) λ P [ Θ κ β A κ x κ y κ + Θ κ λ κ P κ ( f κ ( x κ ) , g 1 ( x 1 ) ) P κ ( f κ ( y κ ) , g 1 ( y 1 ) ) + δ 1 κ u κ u κ + v 1 v 1 ] ] .
Importing the same logic as in (11) for (12), we obtain
P κ ( f κ ( x κ ) , g 1 ( x 1 ) ) P κ ( f κ ( y κ ) , g 1 ( y 1 ) ) γ P κ f κ x κ y κ + ξ P κ g 1 x 1 y 1 .
Using (23), Proposition 1 and H -Lipschitz continuity of M κ and N 1 in (22), we obtain
B κ ( x κ , x 1 ) B κ ( y κ , y 1 ) λ P [ Θ κ β A κ x κ y κ + Θ κ λ κ [ γ P κ f κ x κ y κ + ξ P κ g κ x 1 y 1 ] + κ Λ 1 [ ϵ κ λ H M κ x κ y κ + ϵ 1 λ H N 1 x 1 y 1 ] ] = λ P [ ( Θ κ β A κ + Θ κ λ κ γ P κ f κ + κ Λ 1 ϵ κ λ H M κ ) x κ y κ + ( Θ κ λ κ ξ P κ g 1 + κ Λ 1 ϵ 1 λ H N 1 ) x 1 y 1 .
From (15), (20) and (24), we have
B 1 ( x 1 , x 2 ) B 1 ( y 1 , y 2 ) + B 2 ( x 2 , x 3 ) B 2 ( y 2 , y 3 ) + + B κ ( x κ , x 1 ) B κ ( y κ , y 1 ) λ P [ { Θ 1 ( β A 1 + λ 1 γ P 1 f 1 ) + ϵ 1 ( 1 Λ 2 λ H M 1 + κ Λ 1 λ H N 1 ) + Θ κ λ κ ξ P κ g 1 } x 1 y 1 + { Θ 2 ( β A 2 + λ 2 γ P 2 f 2 ) + ϵ 2 ( 2 Λ 3 λ H M 2 + 1 Λ 2 λ H N 2 ) + Θ 1 λ 1 ξ P 1 g 2 } x 2 y 2 + + { Θ κ ( β A κ + λ κ γ P κ f κ ) + ϵ κ ( κ Λ 1 λ H M κ + κ 1 Λ κ λ H N κ ) + Θ κ 1 λ κ 1 ξ P κ 1 g κ } x κ y κ ] ,
that is,
B 1 ( x 1 , x 2 ) B 1 ( y 1 , y 2 ) + B 2 ( x 2 , x 3 ) B 2 ( y 2 , y 3 ) + + B κ ( x κ , x 1 ) B κ ( y κ , y 1 ) = ϕ 1 x 1 y 1 + ϕ 2 x 2 y 2 + + ϕ κ x κ y κ ,
where
ϕ 1 = λ P [ Θ 1 ( β A 1 + λ 1 γ P 1 f 1 ) + ϵ 1 ( 1 Λ 2 λ H M 1 + κ Λ 1 λ H N 1 ) + Θ κ λ κ ξ P κ g 1 ] ϕ 2 = λ P [ Θ 2 ( β A 2 + λ 2 γ P 2 f 2 ) + ϵ 2 ( 2 Λ 3 λ H M 2 + 1 Λ 2 λ H N 2 ) + Θ 1 λ 1 ξ P 1 g 2 ] ϕ κ = λ P [ Θ κ ( β A κ + λ κ γ P κ f κ ) + ϵ κ ( κ Λ 1 λ H M κ + κ 1 Λ κ λ H N κ ) + Θ κ 1 λ κ 1 ξ P κ 1 g κ ] .
Now, we define ( x 1 , , x κ ) 1 o n H × × H   by
( x 1 , , x κ ) 1 = x 1 + + x κ , ( x 1 , , x κ ) H × × H .
It is easy to prove that ( H × × H , . 1 ) is a Banach space. Hence, from definition of the mapping B, (25) and (26), we have
B ( x 1 , , x κ ) B ( y 1 , , y κ ) 1 = B 1 ( x 1 , x 2 ) B 1 ( y 1 , y 2 ) + + B κ ( x κ , x 1 ) B κ ( y κ , y 1 ) max ϕ 1 , ϕ 2 , , ϕ κ ( x 1 y 1 + x 2 y 2 + x κ y κ ) .
From (8) we know that max ϕ 1 , , ϕ κ < 1 . Therefore, the mapping B is a contraction mapping. Hence, there exists a unique fixed point ( x 1 , , x κ ) H × × H of B (by Banach contraction principle); that is,
B ( x 1 , , x κ ) = ( x 1 , , x κ ) .
This leads to
x 1 = R λ 1 , F 1 ( u 1 , v 2 ) A 1 A 1 ( x 1 ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) } , x 2 = R λ 2 , F 2 ( u 2 , v 3 ) A 2 A 2 ( x 2 ) + λ 2 { ω 2 P 2 ( f 2 ( x 2 ) , g 3 ( x 3 ) ) } , x κ = R λ κ , F κ ( u κ , v 1 ) A κ A κ ( x κ ) + λ κ { ω κ P κ ( f κ ( x κ ) , g 1 ( x 1 ) ) } .
It is determined by Lemma (1) that ( x , u , v ) is a solution of system (3).    □
In support of Theorem 1, we give the following numerical example.
Example 1.
Let ı = 1 , 2 , H = P = R + { 0 } , the mappings A ı , f ı , g ı : H H , F i : H : 2 H , be defined by
f i ( x i ) = 2 x i 7 ( i + 1 ) , g i ( x i ) = 3 x i 49 i , A i ( x i ) = i 14 x i a n d F i ( x i ) = { x i 3 i } .
Suppose that the mappings P i : H × H H is defined as
P i ( x 1 , x 2 ) = x 1 + x 2 10 + i
Now,
A i ( x i ) A i ( y i ) = i 14 x i i 14 y i 2 i 14 ( x i y i )
i.e., A i is i 7 -ordered compression. Furthermore,
P i f i ( x i ) , g i + 1 ( x i + 1 ) P i f i ( y i ) , g i + 1 ( y i + 1 ) = 1 49 ( i + 1 ) ( i + 10 ) ( 14 x i + 3 x i + 1 ) ( 14 y i + 3 y i + 1 ) 21 49 ( i + 1 ) ( i + 10 ) x i + y i + 7 49 ( i + 1 ) ( i + 10 ) x i + 1 + y i + 1
i.e., P i is 3 7 ( i + 1 ) ( 10 + i ) -ordered compression in first argument with respect to f i and 1 7 ( i + 1 ) ( 10 + i ) in second argument with respect to g i .
It is also trivial to verify that F i are 14 3 i 2 -weak-non-ordinary-difference mappings and λ i -XOR-ordered different weak compression with respect to A i where λ i 42 i . For λ i 42 i , [ A i + λ i F i ] ( H ) = H which exhibits that F i are 14 3 i 2 , 42 i -XOR weak ANODD multi-mappings.
Hence the resolvent operator R λ i , F i A i : H H assciated with A i and F i are of the form
R λ i , F i A i ( x i ) = x i i 14 λ i 3 i = 42 i 3 i 2 14 λ i x i ,
which are single-valued and comparisons. Now,
R λ i , F i A i ( x i ) R λ i , F i A i ( y i ) = 42 i 3 i 2 14 λ i x i 42 i 3 i 2 14 λ i y i = 42 i 3 i 2 14 λ i ( x i y i ) 7 i λ i ( x i y i ) , w h e r e λ i 42 i .
Therefore, the resolvent operators R λ i , F i A i are continuous Lipschitz type with constants 7 i λ i . Clearly, Theorem 1’s requirements are all satisfied.

4. S-Iteration and Its Convergence

In this section, based on Lemma 1, we develop the S-iterative algorithm for finding the approximate solution of the new system of generalized XOR-inclusion problem (Algorithm 1). The convergence of the sequence generated by the S-iterative algorithm is shown under some suitable assumptions. For more details related to S-iterative algorithm, we refer to [29] and reference therein.
Algorithm 1 S-iterative algorithm
For i = 1 , 2 , , κ , κ N a n d κ + 1 = 1 , let A i , f i , g i : H H and P i : H × H H be the single-valued mappings. Suppose M i , N i : H C B ( H ) are H -Lipschitz continuous mappings and F i : H × H 2 H are ( α A i , λ i ) XOR-weak-ANODD multi-valued mappings. Then,
Initially: Choose ( x 1 0 , , x k 0 ) H × × H κ - times , ( u 1 0 , , u κ 0 ) M 1 ( x 1 0 ) × × M κ ( x κ 0 ) , and ( v 1 0 , , v κ 0 ) N 1 ( x 1 0 ) × × N κ ( x κ 0 ) .
Step: I   L e t x i ( n + 1 ) x i ( n ) , u i ( n ) u i ( n ) a n d v i ( n ) v i ( n ) . We define
x 1 ( n + 1 ) = ( 1 α n ) R λ 1 , F 1 ( u 1 ( n ) , v 2 ( n ) ) A 1 [ A 1 ( x 1 ( n ) ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ( n ) ) , g 2 ( x 2 ( n ) ) ) } ] + α n R λ 1 , F 1 ( u 1 ( n ) , v 2 ( n ) ) A 1 [ A 1 ( y 1 ( n ) ) + λ 1 { ω 1 P 1 ( f 1 ( y 1 ( n ) ) , g 2 ( y 2 ( n ) ) ) } ] , y 1 ( n ) = ( 1 β n ) x 1 ( n ) + β n R λ 1 , F 1 ( u 1 ( n ) , v 2 ( n ) ) A 1 [ A 1 ( x 1 ( n ) ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ( n ) ) , g 2 ( x 2 ( n ) ) ) } ] , x 2 ( n + 1 ) = ( 1 α n ) R λ 2 , F 2 ( u 2 ( n ) , v 3 ( n ) ) A 2 [ A 2 ( x 2 ( n ) ) + λ 2 { ω 2 P 2 ( f 2 ( x 2 ( n ) ) , g 3 ( x 3 ( n ) ) ) } ] + α n R λ 1 , F 2 ( u 2 ( n ) , v 3 ( n ) ) A 2 [ A 2 ( y 2 ( n ) ) + λ 2 { ω 2 P 2 ( f 2 ( y 2 ( n ) ) , g 3 ( y 3 ( n ) ) ) } ] , y 2 ( n ) = ( 1 β n ) x 2 ( n ) + β n R λ 2 , F 2 ( u 2 ( n ) , v 2 ( n ) ) A 2 [ A 2 ( x 2 ( n ) ) + λ 2 { ω 2 P 2 ( f 2 ( x 2 ( n ) ) , g 3 ( x 3 ( n ) ) ) } ] , x κ ( n + 1 ) = ( 1 α n ) R λ κ , F κ ( u κ ( n ) , v 1 ( n ) ) A κ [ A κ ( x κ ( n ) ) + λ κ { ω κ P κ ( f κ ( x κ ( n ) ) , g 1 ( x 1 ( n ) ) ) } ] + α n R λ κ , F κ ( u κ ( n ) , v 1 ( n ) ) A κ [ A κ ( y κ ( n ) ) + λ κ { ω κ P κ ( f κ ( y κ ( n ) ) , g 1 ( y 1 ( n ) ) ) } ] , y κ ( n ) = ( 1 β n ) x κ ( n ) + β n R λ κ , F κ ( u κ ( n ) , v 1 ( n ) ) A κ [ A κ ( x κ ( n ) ) + λ κ { ω κ P κ ( f κ ( x κ ( n ) ) , g 1 ( x 1 ( n ) ) ) } ] ,
for n = 0 , 1 , 2 , , where λ i > 0 constants and α n , β n are real sequences in (0,1) such that the following condition satisfies
n = 1 α n β n ( 1 β n ) = .
Step: II  Choose u i ( n + 1 ) M i ( x i ( n + 1 ) ) and v i ( n + 1 ) N i ( x i ( n + 1 ) ) such that
u i ( n + 1 ) u i ( n ) ( 1 + 1 n + 1 ) H ( M i ( x i ( n + 1 ) ) , M i ( x i ( n ) ) ) ,
v i ( n + 1 ) v i ( n ) ( 1 + 1 n + 1 ) H ( N i ( x i ( n + 1 ) ) , N i ( x i ( n ) ) ) ,
where H ( . , . ) is the Hausdorff metric on H .
Step: III  If x i ( n + 1 ) , u i ( n ) and v i ( n ) i satisfying step-I and the accuracy is satisfactory, quit; otherwise, set n = n + 1 and go back to step-II.
Lemma 2.
Let v n and η n be the sequences in [ 0 , ) such that that the following are satisfy
(i)
0 η n < 1 , n = 0 , 1 , 2 , and l i m s u p n η n < 1 ;
(ii)
v n + 1 η n v n , n = 0 , 1 , 2 , 3 , .
Then v n 0 as n .
Theorem 2.
With the exception of the condition (8), let all the mappings and conditions be the same as in Theorem 1. Moreover,
Ω i ( n ) : = Θ i β A i + Θ i λ i γ P i f i + i Λ i + 1 ( 1 + 1 n + 1 ) λ H M i ,
δ i ( n ) : = Θ i λ i ξ P i g i + 1 + i Λ i + 1 ( 1 + 1 n + 1 ) λ H N i + 1 ,
and
sup n 1 { α n β n ( Ω 1 ( n ) ( 1 Ω 1 ( n ) δ κ ( n ) ) + δ κ ( n ) ( 1 Ω κ ( n ) δ κ 1 ( n ) ) ) } < sup n 1 ( Ω 1 ( n ) + δ κ ( n ) ) , sup n 1 { α n β n ( Ω 2 ( n ) ( 1 Ω 2 ( n ) δ 1 ( n ) ) + δ 1 ( n ) ( 1 Ω 1 ( n ) δ κ ( n ) ) ) } < sup n 1 ( Ω 2 ( n ) + δ 1 ( n ) ) , sup n 1 { α n β n ( Ω κ ( n ) ( 1 Ω κ ( n ) δ κ 1 ( n ) ) + δ κ 1 ( n ) ( 1 Ω κ 1 ( n ) δ κ 2 ( n ) ) ) } < sup n 1 ( Ω κ ( n ) + δ κ 1 ( n ) ) ,
hold, then the sequences { ( x i ( n ) , u i ( n ) , v i ( n ) } generated by Algorithm 1 converge strongly to the solution { ( x i , u i , v i ) } of system (3).
Proof. 
Using Proposition 1 and iterative Algorithm 1, we have
0 x 1 ( n + 1 ) x 1 = ( ( 1 α n ) R λ 1 , F 1 ( u 1 ( n ) , v 2 ( n ) ) A 1 [ A 1 ( x 1 ( n ) ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ( n ) ) , g 2 ( x 2 ( n ) ) ) } ] + α n R λ 1 , F 1 ( u 1 ( n ) , v 2 ( n ) ) A 1 [ A 1 ( y 1 ( n ) ) + λ 1 { ω 1 P 1 ( f 1 ( y 1 ( n ) ) , g 2 ( y 2 ( n ) ) ) } ] ) ( ( 1 α n ) R λ 1 , F 1 ( u 1 , v 2 ) A 1 [ A 1 ( x 1 ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) } ] + α n R λ 1 , F 1 ( u 1 , v 2 ) A 1 [ A 1 ( y 1 ) + λ 1 { ω 1 P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) } ] ) ( 1 α n ) R λ 1 , F 1 ( u 1 ( n ) , v 2 ( n ) ) A 1 [ A 1 ( x 1 ( n ) ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ( n ) ) , g 2 ( x 2 ( n ) ) ) } ] ( 1 α n ) R λ 1 , F 1 ( u 1 , v 2 ) A 1 [ A 1 ( x 1 ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) } ] + α n R λ 1 , F 1 ( u 1 ( n ) , v 2 ( n ) ) A 1 [ A 1 ( y 1 ( n ) ) + λ 1 { ω 1 P 1 ( f 1 ( y 1 ( n ) ) , g 2 ( y 2 ( n ) ) ) } ] α n R λ 1 , F 1 ( u 1 , v 2 ) A 1 [ A 1 ( y 1 ) + λ 1 { ω 1 P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) } ] .
Applying (2) and (7), we get
( 1 α n ) [ Θ 1 [ A 1 ( x 1 ( n ) ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ( n ) ) , g 2 ( x 2 ( n ) ) ) } ] A 1 ( x 1 ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) } + 1 Λ 2 ( u 1 ( n ) u 1 + v 2 ( n ) v 2 ) ] + α n [ Θ 1 [ A 1 ( y 1 ( n ) ) + λ 1 { ω 1 P 1 ( f 1 ( y 1 ( n ) ) , g 2 ( y 2 ( n ) ) ) } ] A 1 ( y 1 ) + λ 1 { ω 1 P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) } + 1 Λ 2 ( u 1 ( n ) u 1 + v 2 ( n ) v 2 ) ]
By using Proposition 1 and β A 1 -ordered compression of A 1 , we obtain
x 1 ( n + 1 ) x 1 ( 1 α n ) [ Θ 1 ( A 1 ( x 1 ( n ) ) A 1 ( x 1 ) ) + Θ 1 ( λ 1 { ω 1 P 1 ( f 1 ( x 1 ( n ) ) , g 2 ( x 2 ( n ) ) ) } λ 1 { ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) } ) + 1 Λ 2 ( u 1 ( n ) u 1 + v 2 ( n ) v 2 ) ] + α n [ Θ 1 ( A 1 ( y 1 ( n ) ) A 1 ( y 1 ) ) + Θ 1 ( λ 1 { ω 1 P 1 ( f 1 ( y 1 ( n ) ) , g 2 ( y 2 ( n ) ) ) } λ 1 { ω 1 P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) } ) + 1 Λ 2 ( u 1 ( n ) u 1 + v 2 ( n ) v 2 ) ]
( 1 α n ) [ Θ 1 β A 1 ( x 1 ( n ) x 1 ) + Θ 1 λ 1 ( P 1 ( f 1 ( x 1 ( n ) ) , g 2 ( x 2 ( n ) ) ) P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) ) + 1 Λ 2 ( u 1 ( n ) u 1 + v 2 ( n ) v 2 ) ] + α n [ Θ 1 β A 1 ( y 1 ( n ) y 1 ) + Θ 1 λ 1 { P 1 ( f 1 ( y 1 ( n ) ) , g 2 ( y 2 ( n ) ) ) P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) } + 1 Λ 2 ( u 1 ( n ) u 1 + v 2 ( n ) v 2 ) ] ,
which implies that
x 1 ( n + 1 ) x 1 ( 1 α n ) [ Θ 1 β A 1 x 1 ( n ) x 1 + Θ 1 λ 1 P 1 ( f 1 ( x 1 ( n ) ) , g 2 ( x 2 ( n ) ) ) P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) + 1 Λ 2 u 1 ( n ) u 1 + v 2 ( n ) v 2 ] + α n [ Θ 1 β A 1 y 1 ( n ) y 1 + Θ 1 λ 1 P 1 ( f 1 ( y 1 ( n ) ) , g 2 ( y 2 ( n ) ) ) P 1 ( f 1 ( y 1 ) , g 2 ( y 2 ) ) + 1 Λ 2 u 1 ( n ) u 1 + v 2 ( n ) v 2 ] .
Since P 1 is a γ P 1 f 1 -ordered compression mapping in the first component with respect to f 1 and a ξ P 1 g 2 -ordered compression mapping in the second component with respect to g 2 , therefore, by applying the same logic as in (11) for (12), we obtain
x 1 ( n + 1 ) x 1 ( 1 α n ) [ Θ 1 β A 1 x 1 ( n ) x 1 + Θ 1 λ 1 { γ P 1 f 1 x 1 ( n ) x 1 + ξ P 1 g 2 x 2 ( n ) x 2 } + 1 Λ 2 { u 1 ( n ) u 1 + v 2 ( n ) v 2 } ] + α n [ Θ 1 β A 1 y 1 ( n ) y 1 + Θ 1 λ 1 { γ P 1 f 1 y 1 ( n ) y 1 + ξ P 1 g 2 y 2 ( n ) y 2 } + 1 Λ 2 { u 1 ( n ) u 1 + v 2 ( n ) v 2 } ] .
Using (29), (30) and H -Lipschitz continuity of M 1 and N 2 , respectively, there will
x 1 ( n + 1 ) x 1 ( 1 α n ) [ Θ 1 β A 1 x 1 ( n ) x 1 + Θ 1 λ 1 { γ P 1 f 1 x 1 ( n ) x 1 + ξ P 1 g 2 x 2 ( n ) x 2 } + 1 Λ 2 { ( 1 + 1 n + 1 ) λ H M 1 x 1 ( n ) x 1 + ( 1 + 1 n + 1 ) λ H N 2 x 2 ( n ) x 2 } ] + α n [ Θ 1 β A 1 y 1 ( n ) y 1 + Θ 1 λ 1 { γ P 1 f 1 y 1 ( n ) y 1 + ξ P 1 g 2 y 2 ( n ) y 2 } + 1 Λ 2 { ( 1 + 1 n + 1 ) λ H M 1 y 1 ( n ) y 1 + ( 1 + 1 n + 1 ) λ H N 2 y 2 ( n ) y 2 } ]
= ( 1 α n ) [ { Θ 1 β A 1 + Θ 1 λ 1 γ P 1 f 1 + 1 Λ 2 ( 1 + 1 n + 1 ) λ H M 1 } x 1 ( n ) x 1 + { Θ 1 λ 1 ξ P 1 g 2 + 1 Λ 2 ( 1 + 1 n + 1 ) λ H N 2 } x 2 ( n ) x 2 ] + α n [ { Θ 1 β A 1 + Θ 1 λ 1 γ P 1 f 1 + 1 Λ 2 ( 1 + 1 n + 1 ) λ H M 1 } y 1 ( n ) y 1 + { Θ 1 λ 1 ξ P 1 g 2 + 1 Λ 2 ( 1 + 1 n + 1 ) λ H N 2 } y 2 ( n ) y 2 ] .
Using (31) and (32), we have
x 1 ( n + 1 ) x 1 | ( 1 α n ) | [ Ω 1 ( n ) x 1 ( n ) x 1 + δ 1 ( n ) x 2 ( n ) x 2 ] + | α n ( n ) | [ Ω 1 y 1 ( n ) y 1 + δ 1 ( n ) y 2 ( n ) y 2 ] .
Furthermore, by using algorithm (1), we calculate
y 1 ( n ) y 1 { ( 1 β n ) x 1 ( n ) + β n R λ 1 , F 1 ( u 1 ( n ) , v 2 ( n ) ) A 1 [ A 1 ( x 1 ( n ) ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ( n ) ) , g 2 ( x 2 ( n ) ) ) } ] } { ( 1 β n ) x 1 + β n R λ 1 , F 1 ( u 1 , v 2 ) A 1 [ A 1 ( x 1 ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) } ] } .
Using Proposition 1, Lipschitz-type-continuity of R λ 1 , F 1 ( u 1 ( n ) , v 2 ( n ) ) A 1 and condition (7), we have
y 1 ( n ) y 1 ( 1 β n ) x 1 ( n ) x 1 + β n R λ 1 , F 1 ( u 1 ( n ) , v 2 ( n ) ) A 1 [ A 1 ( x 1 ( n ) ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ( n ) ) , g 2 ( x 2 ( n ) ) ) } ] R λ 1 , F 1 ( u 1 , v 2 ) A 1 [ A 1 ( x 1 ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) } ] ( 1 β n ) x 1 ( n ) x 1 + β n [ Θ 1 ( A 1 ( x 1 ( n ) ) A 1 ( x 1 ) ) + λ 1 { ω 1 P 1 ( f 1 ( x 1 ( n ) ) , g 2 ( x 2 ( n ) ) ) } λ 1 { ω 1 P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) } + 1 Λ 2 { u 1 ( n ) u 1 + v 2 ( n ) v 2 ] ( 1 β n ) x 1 ( n ) x 1 + β n [ Θ 1 β A 1 x 1 ( n ) x 1 + Θ 1 λ 1 P 1 ( f 1 ( x 1 ( n ) ) , g 2 ( x 2 ( n ) ) ) P 1 ( f 1 ( x 1 ) , g 2 ( x 2 ) ) + 1 Λ 2 { u 1 ( n ) u 1 + v 2 ( n ) v 2 ] .
Using (12) and H -Lipschitz continuity of M 1 and N 2 , we have
y 1 ( n ) y 1 | ( 1 β n ) | x 1 ( n ) x 1 + | β n | [ Θ 1 β A 1 x 1 ( n ) x 1 + Θ 1 λ 1 ( γ P 1 f 1 x 1 ( n ) x 1 + ξ P 1 g 2 x 2 ( n ) x 2 ) + 1 Λ 2 { ( 1 + 1 n + 1 ) λ H M 1 x 1 ( n ) x 1 + ( 1 + 1 n + 1 ) λ H N 2 x 2 ( n ) x 2 } ]
( 1 β n ) x 1 ( n ) x 1 + | β n | [ { Θ 1 β A 1 + Θ 1 λ 1 γ P 1 f 1 + 1 Λ 2 ( 1 + 1 n + 1 ) λ H M 1 } x 1 ( n ) x 1 + { Θ 1 λ 1 ξ P 1 g 2 + 1 Λ 2 ( 1 + 1 n + 1 ) λ H N 2 } x 2 ( n ) x 2 ] .
Using (31) and (32), we have
y 1 ( n ) y 1 ( 1 β n ) x 1 ( n ) x 1 + β n [ Ω 1 ( n ) x 1 ( n ) x 1 + δ 1 ( n ) x 2 ( n ) x 2 ] .
Similarly, we may obtain
y 2 ( n ) y 2 ( 1 β n ) x 2 ( n ) x 2 + β n [ { Θ 2 β A 2 + Θ 2 λ 2 γ P 2 f 2 + 2 Λ 3 ( 1 + 1 n + 1 ) λ H M 2 } x 2 ( n ) x 2 + { Θ 2 λ 2 ξ P 2 g 3 + 2 Λ 3 ( 1 + 1 n + 1 ) λ H N 3 } x 3 ( n ) x 3 ] .
That is,
y 2 ( n ) y 2 ( 1 β n ) x 2 ( n ) x 2 + β n [ Ω 2 ( n ) x 2 ( n ) x 2 + δ 2 ( n ) x 3 ( n ) x 3 ] .
Using (44) and (46) in (40), we get
x 1 ( n + 1 ) x 1 Ω 1 ( n ) ( 1 α n β n + α n β n Ω 1 ( n ) ) x 1 ( n ) x 1 + δ 1 ( n ) ( 1 α n β n + α n β n Ω 1 ( n ) + α n β n Ω 2 ( n ) ) x 2 ( n ) x 2 + α n β n δ 1 ( n ) δ 2 ( n ) x 3 ( n ) x 3 .
Since the cone P is normal, by Proposition 1, we have
x 1 ( n + 1 ) x 1 λ P x 1 ( n + 1 ) x 1 λ P [ Ω 1 ( n ) ( 1 α n β n + α n β n Ω 1 ( n ) ) x 1 ( n ) x 1 + δ 1 ( n ) ( 1 α n β n + α n β n Ω 1 ( n ) + α n β n Ω 2 ( n ) ) x 2 ( n ) x 2 + α n β n δ 1 ( n ) δ 2 ( n ) x 3 ( n ) x 3 ] .
Using the Proposition 1 and Algorithm 1, we calculate
0 x 2 ( n + 1 ) x 2 = ( ( 1 α n ) R λ 2 , F 2 ( u 2 ( n ) , v 2 ( n ) ) A 2 [ A 2 ( x 2 ( n ) ) + λ 2 { ω 2 P 2 ( f 2 ( x 2 ( n ) ) , g 3 ( x 3 ( n ) ) ) } ] + α n R λ 2 , F 2 ( u 2 ( n ) , v 2 ( n ) ) A 2 [ A 2 ( y 2 ( n ) ) + λ 2 { ω 2 P 2 ( f 2 ( y 2 ( n ) ) , g 3 ( y 3 ( n ) ) ) } ] ) ( ( 1 α n ) R λ 2 , F 2 ( u 2 , v 2 ) A 2 [ A 2 ( x 2 ) + λ 2 { ω 2 P 2 ( f 2 ( x 2 ) , g 3 ( x 3 ) ) } ] + α n R λ 2 , F 2 ( u 2 , v 3 ) A 2 A 2 ( y 2 ) + λ 2 { ω 2 P 2 ( f 2 ( y 2 ) , g 3 ( y 3 ) ) } )
Applying the same logic as in (35) for (38), we obtain
x 2 ( n + 1 ) x 2 = ( 1 α n ) [ { Θ 2 β A 2 + Θ 2 λ 2 γ P 2 f 2 + 2 Λ 3 ( 1 + 1 n + 1 ) λ H M 2 } x 2 ( n ) x 2 + { Θ 2 λ 2 ξ P 2 g 3 + 2 Λ 3 ( 1 + 1 n + 1 ) λ H N 3 } x 3 ( n ) x 3 ] + α n [ { Θ 1 β A 2 + Θ 2 λ 2 γ P 2 f 2 + 2 Λ 3 ( 1 + 1 n + 1 ) λ H M 2 } y 2 ( n ) y 2 + { Θ 2 λ 2 ξ P 2 g 3 + 2 Λ 3 ( 1 + 1 n + 1 ) λ H N 3 } y 3 ( n ) y 3 ] .
Using (31) and (32), we have
x 2 ( n + 1 ) x 2 ( 1 α n ) [ Ω 2 ( n ) x 2 ( n ) x 2 + δ 2 ( n ) x 3 ( n ) x 3 ] + α n [ Ω 2 ( n ) y 2 ( n ) y 2 + δ 2 ( n ) y 3 ( n ) y 3 ] .
Furthermore, by iterative Algorithm (1), we calculate
y 2 ( n ) y 2 { ( 1 β n ) x 2 ( n ) + β n R λ 2 , F 2 ( u 2 ( n ) , v 3 ( n ) ) A 2 [ A 2 ( x 2 ( n ) ) + λ 2 { ω 2 P 2 ( f 2 ( x 2 ( n ) ) , g 3 ( x 3 ( n ) ) ) } ] } { ( 1 β n ) x 2 + β n R λ 2 , F 2 ( u 2 , v 3 ) A 2 [ A 2 ( x 2 ) + λ 2 { ω 2 P 2 ( f 2 ( x 2 ) , g 3 ( x 3 ) ) } ] } .
Importing the same logic as in (42) for (43), we have
y 2 ( n ) y 2 ( 1 β n ) x 2 ( n ) x 2 + β n [ { Θ 2 β A 2 + Θ 2 λ 2 γ P 2 f 2 + 2 Λ 3 ( 1 + 1 n + 1 ) λ H M 2 } x 2 ( n ) x 2 + { Θ 2 λ 2 ξ P 2 g 3 + 2 Λ 3 ( 1 + 1 n + 1 ) λ H N 3 } x 3 ( n ) x 3 ] .
Using (31) and (32), we have
y 2 ( n ) y 2 ( 1 β n ) x 2 ( n ) x 2 + β n [ Ω 2 ( n ) x 2 ( n ) x 2 + δ 2 ( n ) x 3 ( n ) x 3 ] .
Similarly, we get
y 3 ( n ) y 3 ( 1 β n ) x 3 ( n ) x 3 + β n [ { Θ 3 β A 3 + Θ 3 λ 3 γ P 3 f 3 + 3 Λ 4 ( 1 + 1 n + 1 ) λ H M 3 } x 3 ( n ) x 3 + { Θ 3 λ 3 ξ P 3 g 4 + 3 Λ 4 ( 1 + 1 n + 1 ) λ H N 4 } x 4 ( n ) x 4 ] .
That is,
y 3 ( n ) y 3 ( 1 β n ) x 3 ( n ) x 3 + β n [ Ω 3 ( n ) x 2 ( n ) x 3 + δ 3 ( n ) x 4 ( n ) x 4 ] .
By applying the definition of normal cone, (54) and (56) in Equation (51), we have
x 2 ( n + 1 ) x 2 λ P [ Ω 2 ( n ) ( 1 α n β n + α n β n Ω 2 ( n ) ) x 2 ( n ) x 2 + δ 2 ( n ) ( 1 α n β n + α n β n Ω 2 ( n ) + α n β n Ω 3 ( n ) ) x 3 ( n ) x 3 + α n β n δ 2 ( n ) δ 3 ( n ) x 4 ( n ) x 4 ] .
Continuing in this way, we have from Algorithm 1 that
0 x κ ( n + 1 ) x κ = ( ( 1 α n ) R λ κ , F κ ( u κ ( n ) , v κ ( n ) ) A κ [ A κ ( x κ ( n ) ) + λ κ { ω κ P κ ( f κ ( x κ ( n ) ) , g 1 ( x 1 ( n ) ) ) } ] + α n R λ κ , F κ ( u κ ( n ) , v κ ( n ) ) A κ [ A κ ( y κ ( n ) ) + λ κ { ω κ P κ ( f κ ( y κ ( n ) ) , g 1 ( y 1 ( n ) ) ) } ] ) ( ( 1 α n ) R λ κ , F κ ( u κ , v κ ) A κ [ A κ ( x κ ) + λ κ { ω κ P κ ( f κ ( x κ ) , g 1 ( x 1 ) ) } ] + α n R λ κ , F κ ( u κ , v 1 ) A κ [ A κ ( y κ ) + λ κ { ω κ P κ ( f κ ( y κ ) , g 1 ( y 1 ) ) } ] ) .
Applying the same logic as in (34) for (38), we obtain
x κ ( n + 1 ) x κ ( 1 α n ) [ { Θ κ β A κ + Θ κ λ κ γ P κ f κ + κ Λ 1 ( 1 + 1 n + 1 ) λ H M κ } x κ ( n ) x κ + { Θ κ λ κ ξ P κ g 1 + κ Λ 1 ( 1 + 1 n + 1 ) λ H N 1 } x 1 ( n ) x 1 ] + α n [ { Θ κ β A κ + Θ κ λ κ γ P κ f κ + κ Λ 1 ( 1 + 1 n + 1 ) λ H M κ } y κ ( n ) y κ + { Θ κ λ κ ξ P κ g 1 + κ Λ 1 ( 1 + 1 n + 1 ) λ H N 1 } y 1 ( n ) y 1 ] .
Using (31) and (32), we have
x κ ( n + 1 ) x κ ( 1 α n ) [ Ω κ ( n ) x κ ( n ) x κ + δ κ ( n ) x 1 ( n ) x 1 ] + α n [ Ω κ ( n ) y κ ( n ) y κ + δ κ ( n ) y 1 ( n ) y 1 ] .
Furthermore, by using Algorithm 1, we calculate
y κ ( n ) y κ { ( 1 β n ) x κ ( n ) + β n R λ κ , F κ ( u κ ( n ) , v 1 ( n ) ) A κ [ A κ ( x κ ( n ) ) + λ κ { ω κ P κ ( f κ ( x κ ( n ) ) , g 1 ( x 1 ( n ) ) ) } ] } { ( 1 β n ) x κ + β n R λ κ , F κ ( u κ , v 1 ) A κ [ A κ ( x κ ) + λ κ { ω κ P κ ( f κ ( x κ ) , g 1 ( x 1 ) ) } ] } .
Importing the same logic as in (42) for (43), we have
y κ ( n ) y κ ( 1 β n ) x κ ( n ) x κ + | β n | [ { Θ κ β A κ + Θ κ λ κ γ P κ f κ + κ Λ 1 ( 1 + 1 n + 1 ) λ H M κ } x κ ( n ) x κ + { Θ κ λ κ ξ P κ g 1 + κ Λ 1 ( 1 + 1 n + 1 ) λ H N 1 } x 1 ( n ) x 1 ] .
By (31) and (32), we have
y κ ( n ) y κ ( 1 β n ) x κ ( n ) x κ + | β n | [ Ω κ ( n ) x κ ( n ) x κ + δ κ ( n ) x 1 ( n ) x 1 ] .
By using definition of normal cone, Equations (63) and (44) in Equation (60), we get
x κ ( n + 1 ) x κ λ P [ Ω κ ( n ) ( 1 α n β n + α n β n Ω κ ( n ) ) x κ ( n ) x κ + δ κ ( n ) ( 1 α n β n + α n β n Ω κ ( n ) + α n β n Ω 1 ( n ) ) x 1 ( n ) x 1 + α n β n δ κ ( n ) δ 1 ( n ) x 2 ( n ) x 2 ] .
From (48), (57) and (64), we have
x 1 ( n + 1 ) x 1 + x 2 ( n + 1 ) x 2 + + x κ ( n + 1 ) x κ λ P [ ( Ω 1 ( n ) + δ κ ( n ) ) α n β n { Ω 1 ( n ) ( 1 Ω 1 ( n ) δ κ ( n ) ) + δ κ ( n ) ( 1 Ω κ ( n ) δ κ 1 ( n ) ) } ] x 1 ( n ) x 1 + λ P [ ( Ω 2 ( n ) + δ 1 ( n ) ) α n β n { Ω 2 ( n ) ( 1 Ω 2 ( n ) δ 1 ( n ) ) + δ 1 ( n ) ( 1 Ω 1 ( n ) δ κ ( n ) ) } ] x 2 ( n ) x 2 + + + λ P [ ( Ω κ ( n ) + δ κ 1 ( n ) ) α n β n { Ω κ ( n ) ( 1 Ω κ ( n ) δ κ 1 ( n ) ) + δ κ 1 ( n ) ( 1 Ω κ 1 ( n ) δ κ 2 ( n ) ) } ] x κ ( n ) x κ = λ P [ 1 ( n ) x 1 ( n ) x 1 + 2 ( n ) x 2 ( n ) x 2 + + κ ( n ) x κ ( n ) x κ ] ,
where
1 ( n ) = [ ( Ω 1 ( n ) + δ κ ( n ) ) α n β n { Ω 1 ( n ) ( 1 Ω 1 ( n ) δ κ ( n ) ) + δ κ ( n ) ( 1 Ω κ ( n ) δ κ 1 ( n ) ) } ] 2 ( n ) = [ ( Ω 2 ( n ) + δ 1 ( n ) ) α n β n { Ω 2 ( n ) ( 1 Ω 2 ( n ) δ 1 ( n ) ) + δ 1 ( n ) ( 1 Ω 1 ( n ) δ κ ( n ) ) } ] κ ( n ) = [ ( Ω κ ( n ) + δ κ 1 ( n ) ) α n β n { Ω κ ( n ) ( 1 Ω κ ( n ) δ κ 1 ( n ) ) + δ κ 1 ( n ) ( 1 Ω κ 1 ( n ) δ κ 2 ( n ) ) } ] .
Let Φ ( n ) = 1 λ P [ max { 1 ( n ) , 2 ( n ) , , κ ( n ) } ] . From (31) and (32), Ω i ( n ) Ω i and δ i ( n ) δ i , i as n . Where
Ω i = Θ i β A i + Θ i λ i γ P i f i + i Λ i + 1 λ H M i δ i = Θ i λ i ξ P i g i + 1 + i Λ i + 1 λ H N i + 1 .
By algebra of convergence of sequences Ω i ( n ) and δ i ( n ) , we may say that i such that i ( n ) i as n . Therefore, Φ ( n ) Φ , as n , where Φ = max 1 , 2 , , κ . Condition (33) implies that Φ < 1 , so Φ ( n ) < 1 , for sufficiently large n.
Let v n = ( x 1 ( n + 1 ) x 1 + x 2 ( n + 1 ) x 2 + + x κ ( n + 1 ) x κ ) . Then, (65) can be written as
v n + 1 Φ ( n ) v n , n = 0 , 1 , 2 , .
Choosing Φ ( n ) < 1 such that l i m sup n 1 Φ ( n ) < 1 . As a result of Lemma 2 that 0 Φ n < 1 . Therefore, { ( x i ( n ) , u i ( n ) , v i ( n ) ) } converge strongly to the solution { ( x i , u i , v i ) } of system (3). □

5. Conclusions

In this article, a nonlinear system of generalized ordered XOR- inclusion problem is studied in Hilbert space, which is more general than the problems studied in [21,25]. We analyze suitable conditions to prove the existence and convergence result of the considered system by using the theory of strong compression mappings, the resolvent operator, the Banach contraction theorem and the theory of converging sequences. Our results are new and easy to understand.

Author Contributions

Conceptualization, I.A.; Software, H.A.R. and R.G.; Formal analysis, Y.W.; Resources, H.A.R.; Writing—review & editing, I.A.; Visualization, Y.W.; Funding acquisition, Y.W. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by National Natural Science Foundation of China (Grant number 12171435).

Data Availability Statement

Not applicable.

Acknowledgments

The authors are thankful to anonymous referees and the editor for their valuable suggestions and comments which improve the manuscript a lot.

Conflicts of Interest

The authors declare no conflict of interest.

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Ali, I.; Rizvi, H.A.; Geetha, R.; Wang, Y. A Nonlinear System of Generalized Ordered XOR-Inclusion Problem in Hilbert Space with S-Iterative Algorithm. Mathematics 2023, 11, 1434. https://doi.org/10.3390/math11061434

AMA Style

Ali I, Rizvi HA, Geetha R, Wang Y. A Nonlinear System of Generalized Ordered XOR-Inclusion Problem in Hilbert Space with S-Iterative Algorithm. Mathematics. 2023; 11(6):1434. https://doi.org/10.3390/math11061434

Chicago/Turabian Style

Ali, Imran, Haider Abbas Rizvi, Ramakrishnan Geetha, and Yuanheng Wang. 2023. "A Nonlinear System of Generalized Ordered XOR-Inclusion Problem in Hilbert Space with S-Iterative Algorithm" Mathematics 11, no. 6: 1434. https://doi.org/10.3390/math11061434

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