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. 2017 Jun 15;2017(1):137. doi: 10.1186/s13660-017-1416-x

On solving split mixed equilibrium problems and fixed point problems of hybrid-type multivalued mappings in Hilbert spaces

Nawitcha Onjai-uea 1, Withun Phuengrattana 1,2,
PMCID: PMC5487942  PMID: 28680240

Abstract

In this paper, we introduce and study iterative algorithms for solving split mixed equilibrium problems and fixed point problems of λ-hybrid multivalued mappings in real Hilbert spaces and prove that the proposed iterative algorithm converges weakly to a common solution of the considered problems. We also provide an example to illustrate the convergence behavior of the proposed iteration process.

Keywords: split mixed equilibrium problems, hybrid multivalued mappings, weak convergence, Hilbert spaces

Introduction

Let H be a real Hilbert space with inner product , and induced norm . Let C be a nonempty closed convex subset of H, φ:CR be a function, and F:C×CR be a bifunction. The mixed equilibrium problem is to find xC such that

F(x,y)+φ(y)φ(x)0,yC. 1.1

The solution set of mixed equilibrium problem is denoted by MEP(F,φ). In particular, if φ=0, this problem reduces to the equilibrium problem, which is to find xC such that F(x,y)0,yC. The solution set of equilibrium problem is denoted by EP(F).

The mixed equilibrium problem is very general in the sense that it includes, as special cases, optimization problems, variational inequality problems, minimization problems, fixed point problems, Nash equilibrium problems in noncooperative games, and others; see, e.g., [14].

In 1994, Censor and Elfving [5] firstly introduced the following split feasibility problem in finite-dimensional Hilbert spaces: Let H1, H2 be two Hilbert spaces and C, Q be nonempty closed convex subsets of H1 and H2, respectively, and let A:H1H2 be a bounded linear operator. The split feasibility problem is formulated as finding a point x with the property

xCandAxQ.

The split feasibility problem can extensively be applied in fields such as intensity-modulated radiation therapy, signal processing and image reconstruction, then the split feasibility problem has received so much attention by so many scholars; see [69].

In 2013, Kazmi and Rizvi [10] introduced and studied the following split equilibrium problem: let CH1 and QH2. Let F1:C×CR and F2:Q×QR be nonlinear bifunctions and let A:H1H2 be a bounded linear operator. The split equilibrium problem is to find xC such that

F1(x,x)0,xC and such that y=AxQ solves F2(y,y)0,yQ. 1.2

The solution set of the split equilibrium problem is denoted by

SEP(F1,F2):={xC:xEP(F1) and AxEP(F2)}.

The authors gave an iterative algorithm to find the common element of sets of solution of the split equilibrium problem and hierarchical fixed point problem; for more details refer to [11, 12].

In 2016, Suantai et al. [13] proposed the iterative algorithm to solve the problems for finding a common elements the set of solution of the split equilibrium problem and the fixed point of a nonspreading multivalued mapping in Hilbert space, given sequence {xn} by

{x1Carbitrarily,un=TrnF1(IγA(ITrnF2)A)xn,xn+1αnxn+(1αn)Sun,nN, 1.3

where {αn}(0,1), rn(0,) and γ(0,1L) such that L is the spectral radius of AA and A is the adjoint of A, CH1, QH2, S:CK(C) is a 12-nonspreading multivalued mapping, F1:C×CR and F2:Q×QR are two bifunctions. The authors showed that under certain conditions, the sequence {xn} converges weakly to an element of F(S)SEP(F1,F2).

Several iterative algorithms have been developed for solving split feasibility problems and related split equilibrium problems; see, e.g., [1416].

Motivated and inspired by the above results and related literature, we propose an iterative algorithm for finding a common element of the set of solutions of split mixed equilibrium problems and the set of fixed points of λ-hybrid multivalued mappings in real Hilbert spaces. Then we prove some weak convergence theorems which extend and improve the corresponding results of Kazmi and Rizvi [10] and Suantai et al. [13] and many others. We finally provide numerical examples for supporting our main result.

Preliminaries

Let C be a nonempty closed convex subset of a real Hilbert space H. We denote the strong convergence and the weak convergence of the sequence {xn} to a point xH by xnx and xnx, respectively. It is also well known [17] that a Hilbert space H satisfies Opial’s condition, that is, for any sequence {xn} with xnx, the inequality

lim supnxnx<lim supnxny

holds for every yH with yx.

The following two lemmas are useful for our main results.

Lemma 2.1

In a real Hilbert space H, the following inequalities hold:

  1. xy2x2y22xy,y,x,yH;

  2. x+y2x2+2y,x+y,x,yH;

  3. tx+(1t)y2=tx2+(1t)y2t(1t)xy2,t[0,1],x,yH;

  4. If {xn} is a sequence in H which converges weakly to zH, then
    lim supnxny2=lim supnxnz2+zy2,yH.

Lemma 2.2

[18]

Let H be a Hilbert space and {xn} be a sequence in H. Let u,vH be such that limnxnu and limnxnv exist. If {xnk} and {xmk} are subsequences of {xn} which converge weakly to u and v, respectively, then u=v.

A single-valued mapping T:CH is called δ-inverse strongly monotone [19] if there exists a positive real number δ such that

xy,TxTyδTxTy2,x,yC.

For each γ(0,2δ], we see that IγT is a nonexpansive single-valued mapping, that is,

(IγT)x(IγT)yxy,x,yC.

We denote by CB(C) and K(C) the collection of all nonempty closed bounded subsets and nonempty compact subsets of C, respectively. The Hausdorff metric H on CB(C) is defined by

H(A,B):=max{supxAdist(x,B),supyBdist(y,A)},A,BCB(C),

where dist(x,B)=inf{d(x,y):yB} is the distance from a point x to a subset B. Let S:CCB(C) be a multivalued mapping. An element xC is called a fixed point of S if xSx. The set of all fixed points of S is denoted by F(S), that is, F(S)={xC:xSx}. Recall that a multivalued mapping S:CCB(C) is called

  • (i)
    nonexpansive if
    H(Sx,Sy)xy,x,yC;
  • (ii)
    quasi-nonexpansive if F(S) and
    H(Sx,Sp)xp,xC,pF(S);
  • (iii)
    nonspreading [13] if
    2H(Sx,Sy)2dist(y,Sx)2+dist(x,Sy)2,x,yC;
  • (iv)
    λ-hybrid [20] if there exists λR such that
    (1+λ)H(Sx,Sp)2(1λ)xy2+λdist(y,Sx)2+λdist(x,Sy)2,x,yC.

We note that 0-hybrid is nonexpansive, 1-hybrid is nonspreading, and if S is λ-hybrid with F(S), then S is quasi-nonexpansive. It is well known [20] that if S is λ-hybrid, then F(S) is closed. In addition, if S satisfies the condition: Sp={p} for all pF(S), then F(S) is also convex.

The following result is a demiclosedness principle for λ-hybrid multivalued mapping in a real Hilbert space.

Lemma 2.3

[20]

Let C be a nonempty closed convex subset of a real Hilbert space H and S:CK(C) be a λ-hybrid multivalued mapping. If {xn} is a sequence in C such that xnx and ynSxn with xnyn0, then xSx.

For solving the mixed equilibrium problem, we assume that the bifunction F1:C×CR satisfies the following assumption:

Assumption 2.4

Let C be a nonempty closed and convex subset of a Hilbert space H1. Let F1:C×CR be the bifunction, φ:CR{+} is convex and lower semicontinuous satisfies the following conditions:

  1. F1(x,x)=0 for all xC;

  2. F1 is monotone, i.e., F1(x,y)+F1(y,x)0,x,yC;

  3. for each x,y,zC, limt0F1(tz+(1t)x,y)F1(x,y);

  4. for each xC, yF1(x,y) is convex and lower semicontinuous;

  5. for each xH1 and fixed r>0, there exist a bounded subset DxC and yxC such that, for any zCDx,
    F1(z,yx)+φ(yx)φ(z)+1ryxz,zx<0;
  6. C is a bounded set.

Lemma 2.5

[21]

Let C be a nonempty closed and convex subset of a Hilbert space H1. Let F1:C×CR be a bifunction satisfies Assumption  2.4 and let φ:CR{+} be a proper lower semicontinuous and convex function such that Cdomφ. For r>0 and xH1. Define a mapping TrF1:H1C as follows:

TrF1(x)={zC:F1(z,y)+φ(y)φ(z)+1ryz,zx0,yC},

for all xH1. Assume that either (B1) or (B2) holds. Then the following conclusions hold:

  1. for each xH1, TrF1;

  2. TrF1 is single-valued;

  3. TrF1 is firmly nonexpansive, i.e., for any x,yH1,
    TrF1xTrF1y2TrF1xTrF1y,xy;
  4. F(TrF1)=MEP(F1,φ);

  5. MEP(F1,φ) is closed and convex.

Further, assume that F2:Q×QR satisfying Assumption  2.4 and ϕ:QR{+} is a proper lower semicontinuous and convex function such that Qdomϕ, where Q is a nonempty closed and convex subset of a Hilbert space H2. For each s>0 and wH2, define a mapping TsF2:H2Q as follows:

TsF2(v)={wQ:F2(w,d)+ϕ(d)ϕ(w)+1rdw,wv0,dQ}.

Then we have the following:

  • (6)

    for each vH2, TsF2;

  • (7)

    TsF2 is single-valued;

  • (8)

    TsF2 is firmly nonexpansive;

  • (9)

    F(TsF2)=MEP(F2,ϕ);

  • (10)

    MEP(F2,ϕ) is closed and convex.

Main results

In this section, we prove the weak convergence theorems for finding a common element of the set of solutions of split mixed equilibrium problems and the set of fixed points of λ-hybrid multivalued mappings in real Hilbert spaces and give a numerical example to support our main result.

We introduce the definition of split mixed equilibrium problems in real Hilbert spaces as follows.

Definition 3.1

Let C be a nonempty closed convex subset of a real Hilbert space H1 and Q be a nonempty closed convex subset of a real Hilbert space H2. Let F1:C×CR and F2:Q×QR be nonlinear bifunctions, let φ:CR{+} and ϕ:QR{+} be proper lower semicontinuous and convex functions such that Cdomφ and Qdomϕ, and let A:H1H2 be a bounded linear operator. The split mixed equilibrium problem is to find xC such that

F1(x,x)+φ(x)φ(x)0,xC, 3.1

and such that

y=AxQsolvesF2(y,y)+ϕ(y)ϕ(y)0,yQ. 3.2

The solution set of the split mixed equilibrium problem (3.1) and (3.2) is denoted by

SMEP(F1,φ,F2,ϕ):={xC:xMEP(F1,φ) and AxMEP(F2,ϕ)}.

We now get our main result.

Theorem 3.2

Let C be a nonempty closed convex subset of a real Hilbert space H1 and Q be a nonempty closed convex subset of a real Hilbert space H2. Let A:H1H2 be a bounded linear operator and S:CK(C) a λ-hybrid multivalued mapping. Let F1:C×CR, F2:Q×QR be bifunctions satisfying Assumption  2.4, let φ:CR{+} and ϕ:QR{+} be a proper lower semicontinuous and convex functions such that Cdomφ and Qdomϕ, respectively, and F2 is upper semicontinuous in the first argument. Assume that Θ=F(S)SMEP(F1,φ,F2,ϕ) and Sp={p} for all pF(S). Let {xn} be a sequence generated by x1C and

{un=TrnF1(IγA(ITrnF2)A)xn,yn=αnxn+(1αn)wn,wnSun,xn+1=βnwn+(1βn)zn,znSyn,nN, 3.3

where {αn}(0,1), {βn}(0,1), {rn}(0,), and γ(0,1L) such that L is the spectral radius of AA and A is the adjoint of A. Assume that the following conditions hold:

  1. 0<lim infnβnlim supnβn<1;

  2. 0<lim infnαnlim supnαn<1;

  3. 0<lim infnrn.

Then the sequence {xn} generated by (3.3) converges weakly to pΘ.

Proof

First, we show that A(ITrnF2)A is a 1L-inverse strongly monotone mapping. Since TrnF2 is firmly nonexpansive and ITrnF2 is 1-inverse strongly monotone, we see that

A(ITrnF2)AxA(ITrnF2)Ay2=A(ITrnF2)(AxAy),A(ITrnF2)(AxAy)=(ITrnF2)(AxAy),AA(ITrnF2)(AxAy)L(ITrnF2)(AxAy),(ITrnF2)(AxAy)=L(ITrnF2)(AxAy)2LAxAy,(ITrnF2)(AxAy)=Lxy,A(ITrnF2)AxA(ITrnF2)Ay

for all x,yH1. This implies that A(ITrnF2)A is a 1L-inverse strongly monotone mapping. Since γ(0,1L), it follows that IγA(ITrnF2)A is a nonexpansive mapping.

Now, we divide the proof into five steps as follows:

Step 1. Show that {xn} is bounded.

Let qΘ. Then we have q=TrnF1q and q=(IγA(ITrnF2)A)q. By nonexpansiveness of IγA(ITrnF2)A, it implies that

unq=TrnF1(IγA(ITrnF2)A)xnTrnF1(IγA(ITrnF2)A)q(IγA(ITrnF2)A)xn(IγA(ITrnF2)A)qxnq. 3.4

This implies that

wnq=dist(wn,Sq)H(Sun,Sq)unqxnq, 3.5

and so

ynq=αnxn+(1αn)wnqαnxnq+(1αn)wnq=xnq. 3.6

It follows that

znq=dist(zn,Sq)H(Syn,Sq)ynqxnq. 3.7

By (3.5) and (3.7), we have

xn+1q=βnwn+(1βn)znqβnwnq+(1βn)znq=xnq. 3.8

This implies that {xnq} is decreasing and bounded below, thus limnxnq exists for all qΘ.

Step 2. Show that limnwnzn=0.

From Lemma 2.1(3), (3.5), (3.7), and Sq={q}, we have

xn+1q2=βnwn+(1βn)znq2βnwnq2+(1βn)znq2βn(1βn)wnzn2xnq2βn(1βn)wnzn2. 3.9

This implies that

βn(1βn)wnzn2xnq2xn+1q2.

From Condition (C1) and limnxnq exists, we have

limnwnzn=0. 3.10

Step 3. Show that limnunxn=0 and limnwnun=0.

For qΘ, we see that

unq2=TrnF1(IγA(ITrnF2)A)xnTrnF1q2(IγA(ITrnF2)A)xnq2xnq2+γ2A(ITrnF2)Axn2+2γqxn,A(ITrnF2)Axnxnq2+γ2AxnTrnF2Axn,AA(ITrnF2)Axn+2γA(qxn),AxnTrnF2Axnxnq2+Lγ2AxnTrnF2Axn,AxnTrnF2Axn+2γA(qxn)+(AxnTrnF2Axn)(AxnTrnF2Axn),AxnTrnF2Axnxnq2+Lγ2AxnTrnF2Axn2+2γ(ApTrnF2Axn,AxnTrnF2AxnAxnTrnF2Axn2)xnq2+Lγ2AxnTrnF2Axn2+2γ(12AxnTrnF2Axn2AxnTrnF2Axn2)=xnq2+γ(Lγ1)AxnTrnF2Axn2.

Thus, by (3.5) and (3.7), we have

xn+1q2βnwnq2+(1βn)znq2βnunq2+(1βn)xnq2βn(xnq2+γ(Lγ1)AxnTrnF2Axn2)+(1βn)xnq2xnq2+γ(Lγ1)βnAxnTrnF2Axn2. 3.11

Therefore, we have

γ(Lγ1)βnAxnTrnF2Axn2xnq2xn+1q2.

Since γ(Lγ1)<0, it follows by Condition (C1) and the existence of limnxnq that

limnAxnTrnF2Axn=0. 3.12

Since TrnF1 is firmly nonexpansive and IγA(ITrnF2)A is nonexpansive, we have

unq2=TrnF1(IγA(ITrnF2)A)xnTrnF1q2TrnF1(IγA(ITrnF2)A)xnTrnF1q,(IγA(ITrnF2)A)xnq=unq,(IγA(ITrnF2)A)xnq=12(unq2+(IγA(ITrnF2)A)xnq2unxnγA(ITrnF2)Axn2)12(unq2+xnq2(unxn2+γ2A(ITrnF2)Axn22γunxn,A(ITrnF2)Axn)),

which implies that

unq2xnq2unxn2+2γunxn,A(ITrnF2)Axnxnq2unxn2+2γunxnA(ITrnF2)Axn. 3.13

This implies by (3.5) and (3.7) that

xn+1q2βnwnq2+(1βn)znq2βnunq2+(1βn)xnq2βn(xnq2unxn2+2γunxnA(ITrnF2)Axn)+(1βn)xnq2.

Therefore, we have

βnunxn2xnq2xn+1q2+2γβnunxnA(ITrnF2)Axnxnq2xn+1q2+2γβnMA(ITrnF2)Axn,

where M=sup{unxn:nN}. This implies by Condition (C1), (3.12), and the existence of limnxnq that

limnunxn=0. 3.14

From (3.5), (3.7), and the definition of {yn}, we obtain

xn+1q2βnwnq2+(1βn)znq2βnxnq2+(1βn)ynq2=βnxnq2+(1βn)(αnxnq2+(1αn)wnq2αn(1αn)xnwn2)βnxnq2+(1βn)(xnq2αn(1αn)xnwn2)=xnq2αn(1αn)(1βn)xnwn2.

This implies that

αn(1αn)(1βn)xnwn2xnq2xn+1q2.

From Conditions (C1), (C2), and the existence of limnxnq, we have

limnwnxn=0. 3.15

By (3.14) and (3.15), we get

wnunwnxn+xnun0as n. 3.16

Step 4. Show that ωw(xn)Θ, where ωw(xn)={xH1:xnix,{xni}{xn}}. Since {xn} is bounded and H1 is reflexive, ωw(xn) is nonempty. Let pωw(xn) be an arbitrary element. Then there exists a subsequence {xni}{xn} converging weakly to p. From (3.14), it implies that unip as i. By (3.16) and Lemma 2.3, we have pF(S).

Next, we show that pMEP(F1,φ). Since un=TrnF1(IγA(ITrnF2)A)xn, we have

F1(un,y)+φ(y)φ(un)+1rnyun,unxnγA(ITrnF2)Axn0,yC,

which implies that

F1(un,y)+φ(y)φ(un)+1rnyun,unxn1rnyun,γA(ITrnF2)Axn0,yC.

From Assumption 2.4(A2), we have

φ(y)φ(un)+1rnyun,unxn1rnyun,γA(ITrnF2)AxnF1(un,y)F1(y,un),yC,

and hence

φ(y)φ(uni)+1rniyuni,unixni1rniyuni,γA(ITrniF2)AxniF1(y,uni),yC.

This implies by unip, Condition (C3), (3.12), (3.14), Assumption 2.4(A2), and the proper lower semicontinuity of φ that

F1(y,p)+φ(p)φ(y)0,yC.

Put yt=ty+(1t)p for all t(0,1] and yC. Consequently, we get ytC and hence F1(yt,p)+φ(p)φ(yt)0. So, by Assumption 2.4(A1)-(A4), we have

0=F1(yt,yt)φ(yt)+φ(yt)tF1(yt,y)+(1t)F1(yt,p)+tφ(y)+(1t)φ(p)φ(yt)t(F1(yt,y)+φ(y)φ(yt)).

Hence, we have

F1(yt,y)+φ(y)φ(yt)0,yC.

Letting t0, by Assumption 2.4(A3) and the proper lower semicontinuity of φ, we have

F1(p,y)+φ(y)φ(p)0,yC.

This implies that pMEP(F1,φ).

Since A is a bounded linear operator, we have AxniAp. Then it follows from (3.12) that

TrniF2AxniApas i. 3.17

By the definition of TrniF2Axni, we have

F2(TrniF2Axni,y)+ϕ(y)ϕ(TrniF2Axni)+1rniyTrniF2Axni,TrniF2AxniAxni0,yQ.

Since F2 is upper semicontinuous in the first argument, it implies by (3.17) that

F2(Ap,y)+ϕ(y)ϕ(Ap)0,yQ.

This shows that ApMEP(F2,ϕ). Therefore, pSMEP(F1,φ,F2,ϕ) and hence pΘ.

Step 5. Show that {xn} converges weakly to an element of Θ. It is sufficient to show that ωw(xn) is a singleton set. Let p,qωw(xn) and {xnk}, {xnm} be two subsequences of {xn} such that xnkp and xnmq. From (3.14), we also have unkp and unmq. By (3.16) and Lemma 2.3, we see that p,qF(S). Applying Lemma 2.2, we obtain p=q. This completes the proof. □

If φ=ϕ=0 in (3.1) and (3.2), then the split mixed equilibrium problem reduces to split equilibrium problem. So, the following result can be obtained from Theorem 3.2 immediately.

Theorem 3.3

Let C be a nonempty closed convex subset of a real Hilbert space H1 and Q be a nonempty closed convex subset of a real Hilbert space H2. Let A:H1H2 be a bounded linear operator and S:CK(C) a λ-hybrid multivalued mapping. Let F1:C×CR, F2:Q×QR be bifunctions satisfying Assumption  2.4, and F2 is upper semicontinuous in the first argument. Assume that Θ=F(S)SEP(F1,F2) and Sp={p} for all pF(S). Let {xn} be a sequence generated by x1C and

{un=TrnF1(IγA(ITrnF2)A)xn,yn=αnxn+(1αn)wn,wnSun,xn+1=βnwn+(1βn)zn,znSyn,nN, 3.18

where {αn}(0,1), {βn}(0,1), {rn}(0,), and γ(0,1L) such that L is the spectral radius of AA and A is the adjoint of A. Assume that the following conditions hold:

  1. 0<lim infnβnlim supnβn<1;

  2. 0<lim infnαnlim supnαn<1;

  3. 0<lim infnrn.

Then the sequence {xn} generated by (3.18) converges weakly to pΘ.

Remark 3.4

  • (i)

    Theorems 3.2 and 3.3 extend the corresponding one of Suantai et al. [13] and Kazmi and Rizvi [10] to λ-hybrid multivalued mapping and to a split mixed equilibrium problem. In fact, we present a new iterative algorithm for finding a common element of the set of solutions of split mixed equilibrium problems and the set of fixed points of λ-hybrid multivalued mappings in a real Hilbert space.

  • (ii)

    It is well known that the class of λ-hybrid multivalued mappings contains the classes of nonexpansive multivalued mappings, nonspreading multivalued mappings. Thus, Theorems 3.2 and 3.3 can be applied to these classes of mappings.

We give an example to illustrate Theorem 3.2 as follows.

Example 3.5

Let H1=R, H2=R, C=[3,0], and Q=(,0]. Let A:H1H2 defined by Ax=x2 for each xH1. Then Ay=y2 for each yH2. So, L=12 is the spectral radius of AA. Define a multivalued mapping S:CK(C) by

Sx={[|x||x|+1,0],x[3,2);{0},x[2,0].

It easy to see that S is 1-hybrid multivalued mapping with F(S)={0} and S(0)={0}. For each x,yC, define the bifunction F1:C×CR by F1(x,y)=xy+yxx2 and define φ(x)=0 for each xC. For each u,vQ, define the bifunction F2:Q×QR by F2(u,v)=uv+10v10uu2 and define ϕ(u)=0 for each uQ.

Choose αn=n5n+1, βn=n9n+1, rn=nn+1, and γ=115. It is easy to check that F1, F2, {αn}, {βn}, {rn} satisfy all conditions in Theorem 3.2.

For each xC, we compute TrF2Ax. Find z such that

0F2(z,y)+φ(y)φ(z)+1ryz,zAx=zy+10y10zz2+1ryz,zx2=(z+10)(yz)+1r(yz)(zx2)=(yz)((z+10)+1r(zx2))

for all yQ. Thus, by Lemma 2.5(2), it follows that z=x20r2(1+r). That is, TrF2Ax=x20r2(1+r) for each xC. Furthermore, we get

(IγA(ITrF2)A)x=x115A(AxTrF2Ax)=x115A(x2x20r2(1+r))=x115(x4x20r4(1+r))=x(1γ60)γ(x20r)60(1+r).

Next, we find uC such that F1(u,v)+φ(y)φ(z)+1rvu,us0 for all vC, where s=(IγA(ITrF2)A)x. Note that

0F1(u,v)+φ(y)φ(z)+1rvu,us=uv+vuu2+1rvu,us=(u+1)(vu)+1r(vu)(us)=(vu)((u+1)+1r(us)).

Thus, by Lemma 2.5(2), it follows that

u=sr1+r=59x60r60(1+r)x20r60(1+r)2.

Then the algorithm (3.3) becomes

{un=59xn60rn60(1+rn)xn20rn60(1+rn)2,rn=nn+1,yn=n5n+1xn+(1n5n+1)wn,xn+1=n9n+1wn+(1n9n+1)zn,nN, 3.19

where

wn={[|un||un|+1,0],un[3,2);{0},un[2,0],zn={[|yn||yn|+1,0],yn[3,2);{0},yn[2,0].

We choose wn=|un||un|+1 if un[3,2) and zn=|yn||yn|+1 if yn[3,2). By using SciLab, we compute the iterates of (3.19) for the initial point x1=3. The numerical experiment’s results of our iteration for approximating the point 0 are given in Table 1.

Table 1.

Numerical results of Example 3.5 for the algorithm (3.19)

n xn xnxn1
1 −3.0000000e + 00 -
2 −6.8786127e − 02 2.9312139e + 00
3 0.0000000e + 00 6.8786127e − 02
4 0.0000000e + 00 0.0000000e + 00

Conclusions

The results presented in this paper extend and generalize the work of Suantai et al. [13] and Kazmi and Rizvi [10]. The main aim of this paper is to propose an iterative algorithm to find an element for solving a class of split mixed equilibrium problems and fixed point problems for λ-hybrid multivalued mappings under weaker conditions. Some sufficient conditions for the weak convergence of such proposed algorithm are given. Also, in order to show the significance of the considered problem, some important applications are discussed.

Acknowledgements

The authors are thankful to the referees for careful reading and the useful comments and suggestions.

Footnotes

Funding

This work was supported by the Research Center for Pure and Applied Mathematics, Research and Development Institute, Nakhon Pathom Rajabhat University, Nakhon Pathom, Thailand. The second author was also supported by the Thailand Research Fund under the project RTA5780007.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

All authors contributed equally and significantly in writing this paper. All authors read and approved the final manuscript.

Publisher’s Note

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Contributor Information

Nawitcha Onjai-uea, Email: nawitcha@hotmail.com.

Withun Phuengrattana, Email: withun_ph@yahoo.com.

References

  • 1.Ceng LC, Yao JC. A hybrid iterative scheme for mixed equilibrium problems and fixed point problems. J. Comput. Appl. Math. 2008;214:186–201. doi: 10.1016/j.cam.2007.02.022. [DOI] [Google Scholar]
  • 2.Blum E, Oettli W. From optimization and variational inequalities to equilibrium problems. Math. Stud. 1994;63:123–145. [Google Scholar]
  • 3.Combettes PI, Hirstoaga SA. Equilibrium programming in Hilbert spaces. J. Nonlinear Convex Anal. 2005;6:117–136. [Google Scholar]
  • 4.Flam SD, Antipin AS. Equilibrium programming using proximal-like algorithm. Math. Program. 1997;78:29–41. doi: 10.1007/BF02614504. [DOI] [Google Scholar]
  • 5.Censor Y, Elfving T. A multiprojection algorithm using Bregman projections in a product space. Numer. Algorithms. 1994;8:221–239. doi: 10.1007/BF02142692. [DOI] [Google Scholar]
  • 6.Censor Y, Bortfeld T, Martin B, Trofimov A. A unified approach for inversion problems in intensity-modulated radiation therapy. Phys. Med. Biol. 2006;51:2353–2365. doi: 10.1088/0031-9155/51/10/001. [DOI] [PubMed] [Google Scholar]
  • 7.Censor Y, Elfving T, Kopf N, Bortfeld T. The multiple-sets split feasibility problem and its applications for inverse problems. Inverse Probl. 2005;21:2071–2084. doi: 10.1088/0266-5611/21/6/017. [DOI] [Google Scholar]
  • 8.Censor Y, Motova A, Segal A. Perturbed projections and subgradient projections for the multiple-sets split feasibility problem. J. Math. Anal. Appl. 2007;327:1244–1256. doi: 10.1016/j.jmaa.2006.05.010. [DOI] [Google Scholar]
  • 9.Chan T, Shen J. Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic Methods. Philadelphia: SIAM; 2005. [Google Scholar]
  • 10.Kazmi KR, Rizvi SH. Iterative approximation of a common solution of a split equilibrium problem, a variational inequality problem and a fixed point problem. J. Egypt. Math. Soc. 2013;21:44–51. doi: 10.1016/j.joems.2012.10.009. [DOI] [Google Scholar]
  • 11.Bnouhachem A. Algorithms of common solutions for a variational inequality, a split equilibrium problem and a hierarchical fixed point problem. Fixed Point Theory Appl. 2013;2013 doi: 10.1186/1687-1812-2013-278. [DOI] [Google Scholar]
  • 12.Bnouhachem A. Strong convergence algorithm for split equilibrium problems and hierarchical fixed point problems. Sci. World J. 2014;2014 doi: 10.1155/2014/390956. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Suantai S, Cholamjiak P, Cho YJ, Cholamjiak W. On solving split equilibrium problems and fixed point problems of nonspreading multi-valued mappings in Hilbert spaces. Fixed Point Theory Appl. 2016;2016 doi: 10.1186/s13663-016-0509-4. [DOI] [Google Scholar]
  • 14.Deepho J, Kumam W, Kumam P. A new hybrid projection algorithm for solving the split generalized equilibrium problems and the system of variational inequality problems. J. Math. Model. Algorithms Oper. Res. 2014;13(4):405–423. doi: 10.1007/s10852-014-9261-0. [DOI] [Google Scholar]
  • 15.Kumam W, Deepho J, Kumam P. Hybrid extragradient method for finding a common solution of the split feasibility and system of equilibrium problems. Dyn. Contin. Discrete Impuls. Syst., Ser. B, Appl. Algorithms. 2014;21(6):367–388. [Google Scholar]
  • 16.Deepho J, Martinez-Moreno J, Kumam P. A viscosity of Cesaro mean approximation method for split generalized equilibrium, variational inequality and fixed point problems. J. Nonlinear Sci. Appl. 2016;9:1475–1496. [Google Scholar]
  • 17.Opial Z. Weak convergence of the sequence of successive approximation for nonexpansive mappings. Bull. Am. Math. Soc. 1967;73:591–597. doi: 10.1090/S0002-9904-1967-11761-0. [DOI] [Google Scholar]
  • 18.Suantai S. Weak and strong convergence criteria of Noor iterations for asymptotically nonexpansive mappings. J. Math. Anal. Appl. 2005;311:506–517. doi: 10.1016/j.jmaa.2005.03.002. [DOI] [Google Scholar]
  • 19.Iiduka H, Takahashi W. Weak convergence theorem by Cesaro means for nonexpansive mappings and inverse-strongly monotone mappings. J. Nonlinear Convex Anal. 2006;7:105–113. [Google Scholar]
  • 20.Suantai S, Phuengrattana W. Existence and convergence theorems for λ-hybrid mappings in Hilbert spaces. Dyn. Contin. Discrete Impuls. Syst. Ser. A, Math. Anal. 2015;22:177–188. [Google Scholar]
  • 21.Ma Z, Wang L, Chang SS, Duan W. Convergence theorems for split equality mixed equilibrium problems with applications. Fixed Point Theory Appl. 2015;2015 doi: 10.1186/s13663-015-0281-x. [DOI] [Google Scholar]

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