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Perturbed Ishikawa-hybrid quasi-proximal point algorithm with accretive mappings for a fuzzy system
Fixed Point Theory and Applications volume 2013, Article number: 281 (2013)
Abstract
A new class of fuzzy general nonlinear set-valued mixed quasi-variational inclusions frameworks for a perturbed Ishikawa-hybrid quasi-proximal point algorithm using the notion of -accretive is developed. Convergence analysis for the algorithm of solving a fuzzy nonlinear set-valued inclusions problem and existence analysis of a solution for the problem is explored along with some results on the resolvent operator corresponding to an -accretive mapping due to Lan et al. The result that the sequence generated by the perturbed Ishikawa-hybrid quasi-proximal point algorithm converges linearly to a solution of the fuzzy general nonlinear set-valued mixed quasi-variational inclusions with the convergence rate ε is proved.
MSC:49J40, 47H06.
1 Introduction
The set-valued inclusions problem, which was introduced and discussed by Bella [1], Huang et al. [2] and Jeong [3], is a useful extension of the mathematics analysis. And the variational inclusion (inequality) is an important context in the set-valued inclusions problem. It provides us with a unified, natural, novel, innovative and general technique to study a wide class of problems arising in different branches of mathematical and engineering sciences. Various variational inclusions have been intensively studied in recent years. Ding [4], Verma [5], Huang [6], Fang and Huang [7], Lan et al. [8], Fang et al. [9], Zhang et al. [10] introduced the concepts of η-subdifferential operators, maximal η-monotone operators, H-monotone operators, A-monotone operators, -monotone operators, -accretive mappings, -monotone operators and defined resolvent operators associated with them, respectively. Moreover, by using the resolvent operator technique, many authors constructed some approximation algorithms for some nonlinear variational inclusions in Hilbert spaces or Banach spaces. In 2008, Li [11] studied the existence of solutions and the stability of a perturbed Ishikawa iterative algorithm for nonlinear mixed quasi-variational inclusions involving -accretive mappings in Banach spaces by using the resolvent operator technique.
On the other hand, in many scientific and engineering applications, the fuzzy set concept and the variational inequalities with fuzzy mappings play an important role. The fuzziness appears when we need to perform, on manifold, calculations with imprecision variables. The concept of fuzzy sets was introduced initially by Zadeh [12] in 1965. Since then, to use this concept in topology and analysis, many authors have expansively developed the theory of fuzzy sets and application [13, 14]. Various concepts of fuzzy metrics on an ordinary set were considered in [15, 16], and many authors studied fixed point theory for ordinary mappings in such fuzzy metric spaces [17–21]. A number of metrics are used on the subspaces of fuzzy sets. The sendograph metric [22, 23] and the d1-metric induced by the Hausdorff metric [24, 25] were studied most frequently. Some attention was also given to Lp-type metrics [26, 27]. These results have a very important application in quantum particle physics, particularly in connection with both string and e1-theory, which were given and studied by El-Naschie [28, 29].
From 1989, Chang and Zhu [30] introduced and investigated a class of variational inequalities for fuzzy mappings. Afterwards, Chang and Huang [31], Ding and Jong [32], Jin [33], Li [34] and others studied several kinds of variational inequalities (inclusions) for fuzzy mappings.
Recently, Verma has developed a hybrid version of the Eckstein-Bertsekas [35] proximal point algorithm, introduced the algorithm based on the -maximal monotonicity framework [36] and studied convergence of the algorithm. The author showed the general nonlinear set-valued inclusions problem based on an -accretive framework and suggested and discussed an Ishikawa-hybrid proximal point algorithm for solving the inclusions problem. On the other hand, from 1989, the generalized nonlinear quasi-variational inequalities (inclusions) with fuzzy mappings have been studied widely by a number of authors, who have more and more achievements [17–37], and we refer to [1–56] and references contained therein.
Inspired and motivated by recent research work in this field, in this paper, a fuzzy general nonlinear set-valued mixed quasi-variational inclusions framework for a perturbed Ishikawa-hybrid quasi-proximal point algorithm using the notion of -accretive is developed. Convergence analysis for the algorithm of solving a fuzzy nonlinear set-valued inclusions problem and existence analysis of a solution for the problem are explored along with some results on the resolvent operator corresponding to an -accretive mapping due to Lan et al. [8]. The result that the sequence generated by the perturbed Ishikawa-hybrid quasi-proximal point algorithm converges linearly to a solution of the fuzzy general nonlinear set-valued mixed quasi-variational inclusions with the convergence rate ε is proved.
2 Preliminaries
Let X be a real Banach space with the dual space , be the dual pair between X and , denote the family of all the nonempty subsets of X, and denote the family of all nonempty closed bounded subsets of X. The generalized duality mapping is defined by
where is a constant.
The modulus of smoothness of X is the function defined by
A Banach space X is called uniformly smooth if
X is called q-uniformly smooth if there exists a constant such that
Remark 2.1 In particular, is the usual normalized duality mapping, and (for all ). If is strictly convex [41], or X is a uniformly smooth Banach space, then is single-valued. In what follows, we always denote the single-valued generalized duality mapping by in a real uniformly smooth Banach space X unless otherwise stated.
Let us recall the following results and concepts.
Definition 2.2 A single-valued mapping is said to be τ-Lipschitz continuous if there exists a constant such that
Definition 2.3 A single-valued mapping is said to be
-
(i)
accretive if
-
(ii)
strictly accretive if A is accretive and if and only if ;
-
(iii)
r-strongly η-accretive if there exists a constant such that
-
(iv)
α-Lipschitz continuous if there exists a constant such that
-
(v)
A single-valued mapping is said to be -Lipschitz continuous if there exist constants such that
-
(vi)
Let be single-valued mappings, be a set-valued mapping. g is said to be -S-relaxed cocoercive with respect to A mapping, if there exist two constants such that for any , the following holds:
Definition 2.4 Let and be single-valued mappings. A set-valued mapping is said to be:
-
(i)
accretive if
-
(ii)
η-accretive if
-
(iii)
r-strongly accretive if there exists a constant such that
-
(iv)
m-relaxed η-accretive if there exists a constant such that
-
(v)
A-accretive if M is accretive and for all ;
-
(vi)
-accretive if M is m-relaxed η-accretive and for all .
-
(vii)
h-Lipschitz continuous with constants ξ if
where is the Hausdorff metric in .
Based on the literature [8], we can define the resolvent operator as follows.
Definition 2.5 ([8])
Let be a single-valued mapping, be a strictly η-accretive single-valued mapping and be an -accretive mapping. The resolvent operator is defined by
where is a constant.
Remark 2.6 The -accretive mappings are more general than the -monotone mappings and m-accretive mappings in a Banach space or a Hilbert space, and the resolvent operators associated with -accretive mappings include as special cases the corresponding resolvent operators associated with -monotone operators, m-accretive mappings, A-monotone operators, η-subdifferential operators [3–11, 30–34].
Lemma 2.7 ([8])
Let be a τ-Lipschitz continuous mapping, be an r-strongly η-accretive mapping, and be an -accretive mapping. Then the generalized resolvent operator is -Lipschitz continuous, that is,
where .
In the study of characteristic inequalities in q-uniformly smooth Banach spaces, Xu [38] proved the following result.
Lemma 2.8 ([38])
Let X be a real uniformly smooth Banach space. Then X is q-uniformly smooth if and only if there exists a constant such that for all ,
3 Fuzzy general nonlinear set-valued mixed quasi variational inclusions with -accretive mappings
Let X be a real q-uniformly smooth Banach space with the dual space , be the dual pair between X and , denote the family of all the nonempty subsets of X, and denote the family of all nonempty closed bounded subsets of X.
Let be a collection of all fuzzy sets over X. A mapping is called a fuzzy mapping. For each , (denote it by in the sequel) is a fuzzy set on X and is the membership function of y in . For , , the set is called a q-cut set of .
Let for any , be a fuzzy mapping satisfying the condition :
there exists a function such that for all , , where denotes the family of all nonempty bounded closed subsets of X.
By using the fuzzy mapping , we can define a set-valued mapping by for each , and is called the set-valued mapping induced by the fuzzy mapping for any in the sequel, respectively.
Let ; be single-valued mappings. Let be a set-valued -accretive mapping and for each . We consider the fuzzy general nonlinear set-valued mixed quasi-variational inclusions with -accretive mappings (FGNSVMQVI):
Find and () such that and
where problem (3.1) is called fuzzy general nonlinear set-valued mixed quasi-variational inclusions with -accretive mappings.
If for any , is a set-valued mapping, we can define the fuzzy mapping by , where is the characteristic function of . Taking () for all , problem (3.1) is equivalent to the following problem:
Find and () such that
which is called a new class of general nonlinear set-valued mixed quasi-variational inclusions with -accretive mappings (GNSVMQVI).
Remark 3.1
-
(1)
A special case of problem (3.1) is the following:
-
(i)
If X is a Hilbert space, an -accretive mapping , , , , , , , and and , then problem (3.1) becomes problem (2.1) in [53], which was studied by Li [53].
-
(ii)
For a suitable choice of A, f, g, η, F, G, () and the space X, a number of known classes of fuzzy variational inclusions and fuzzy variational inequalities in [30–32, 37] can be obtained as special cases of the fuzzy general nonlinear set-valued mixed quasi-variational inclusions (3.1).
-
(i)
-
(2)
A special case of problem (3.2) is the following:
-
(i)
Comparing problem (2.2) in [55] and letting be a constant in X, be single-valued mappings, and and , , then we can see that (3.2) becomes problem (2.2) in [55] as follows:
For any , find and such that
(3.3) -
(ii)
If is a Hilbert space, is the zero operator in X, are the identity operators in X, , and , then problem (3.2) becomes the parametric usual variational inclusion with an -maximal monotone mapping M, which was studied by Verma [36].
-
(iii)
If X is a real Banach space, is the identity operator in X, and , then problem (3.3) becomes the parametric usual variational inclusion with an -accretive mapping, which was studied by Li [54].
-
(i)
Furthermore, these types of fuzzy variational inclusions and variational inclusions can enable us to study many important nonlinear problems arising in mechanics, physics, optimization and control, nonlinear programming, economics, finance, regional, structural, transportation, elasticity and applied sciences in a general and unified framework.
4 The existence of solutions
Now, we study the existence of solutions for problem (3.1).
Lemma 4.1 Let X be a Banach space. Let be the set-valued mapping induced by the fuzzy mapping for any , let be a τ-Lipschitz continuous mapping, be an r-strongly η-accretive mapping, be a single-valued mapping, and be an -accretive mapping for any . Then the following statements are mutually equivalent:
-
(i)
is a solution of problem (3.1), where , that is, ().
-
(ii)
For and any , the following relation holds:
(4.1)where , that is, ().
-
(iii)
For and any , the following relation holds:
(4.2)where is a constant, and , that is, ().
Proof This directly follows from the definition of . □
Theorem 4.2 Let X be a q-uniformly smooth Banach space. Let ; be single-valued mappings, and let η be a τ-Lipschitz continuous mapping, A be an r-strongly η-accretive and α-Lipschitz continuous mapping, f be a χ-Lipschitz continuous mapping, and g be a φ-Lipschitz continuous and --relaxed cocoercive with respect to A mapping, respectively. For , let be a fuzzy mapping satisfying condition and be a set-valued mapping induced by the fuzzy mapping , and suppose that is D-Lipschitz continuous with constants and that is γ-strongly accretive. Let be -Lipschitz continuous. Let be a set-valued -accretive mapping for any and , and for any ,
If there exists a constant such that the following condition holds:
where is the same as in Lemma 2.8, and , then problem (3.1) has a solution , which ().
Proof For , define a mapping as follows:
For elements , if for , letting or and
then by (4.1), (4.2), (4.4), Lemma 2.7 and Lemma 2.8, we have
where
Since g is φ-Lipschitz continuous and --relaxed cocoercive with respect to A and A is α-Lipschitz continuous, we obtain
Since is -Lipschitz continuous and f is χ-Lipschitz continuous, the following holds:
By using γ-strong accretion of , we obtain
Combining(4.5), (4.6), (4.7) and (4.8), we can get
where
It follows from (4.3) and (4.9) that H has a fixed point in X, i.e., there exists a point such that
where (). This completes the proof. □
5 Perturbed Ishikawa-hybrid quasi-proximal point algorithm and solvability of problem (3.1)
Based on Lemma 4.1, we develop a perturbed Ishikawa-hybrid quasi-proximal point algorithm for finding iterative sequence solving problem (3.1) as follows.
Algorithm 5.1 Let X be a q-uniformly smooth Banach space, let be a fuzzy mapping satisfying condition and be the set-valued mapping induced by the fuzzy mapping (). Let , be single-valued mappings, and let be such that for each fixed , is an -accretive mapping and . Let , , , , , and be five nonnegative sequences such that
Step 1: For an arbitrarily initial point , we choose suitable (), , and , letting
where (), and are errors to take into account a possible inexact computation of the proximal point.
Step 2: The sequences and are generated by an iterative procedure
where and (), and are errors to take into account a possible inexact computation of the proximal point and
By using Nadler [39], we can choose suitable such that
where is the Hausdorff metric in , .
Remark 5.2 For a suitable choice of the mappings A, η, f, g, F, G, , , space X, and nonnegative sequences , , , , , and , Algorithm 5.1 can be degenerated to a number of algorithms involving many known algorithms which are due to classes of variational inequalities and variational inclusions [10, 11, 30–34, 45, 47, 50, 56].
Theorem 5.3 Let X be a q-uniformly smooth Banach space. Let ; be single-valued mappings, and η be a τ-Lipschitz continuous mapping, A be an r-strongly η-accretive and α-Lipschitz continuous mapping, f be a χ-Lipschitz continuous mapping, and g be a φ-Lipschitz continuous and --relaxed cocoercive with respect to A mapping, respectively. For , let be a fuzzy mapping satisfying condition and be a set-valued mapping induced by the fuzzy mapping , and suppose that is h-Lipschitz continuous with constants and that is γ-strongly accretive. Let be -Lipschitz continuous. Let be a set-valued -accretive mapping for any and , and for any ,
If nonnegative sequences , , , , , and are the same as in Algorithm 5.1 and , where
then the sequence generated by perturbed Ishikawa-hybrid quasi-proximal point Algorithm 5.1 converges linearly to as
where is the same as in Lemma 2.8, , and the convergence rate is , and problem (3.1) has a solution , where ().
Proof Suppose that the sequence is the sequence generated by perturbed Ishikawa-hybrid quasi-proximal point Algorithm 5.1, and that is a solution of problem (3.1). From Lemma 4.1 and condition , we can get
where ().
For all and (), set
By using (4.9), we find the estimation
where
Since , (5.1) and (4.8)-(4.9) so that and
Next, we calculate
This implies that
Let
For all , set
For the same reason,
and by using in (5.1), the following holds:
Furthermore,
Combining (5.7)-(5.10), we have
By (5.4) and the conditions
we can see
where for ; and
and the convergence rate is ε.
Therefore, the sequence generated by Algorithm 5.1 converges linearly to a solution with convergence rate ε in a Banach space.
Let as . For any , by the h-Lipschitz continuity of () with constants , we obtain
It follows that are also Cauchy sequences in X. We can assume that . Note that , we have
Hence and therefore .
By the Lipschitz continuity of and Lemma 2.7, condition (5.4), we have
for any . By Lemma 4.1, we know that problem (3.1) has a solution , where (). This completes the proof. □
Remark 5.4 For a suitable choice of the mappings A, η, f, g, F, G, (), we can obtain several known results [1, 3–11, 30–34, 45, 47, 56] as special cases of Theorem 5.3.
References
Di Bella B: An existence theorem for a class of inclusions. Appl. Math. Lett. 2000, 13(3):15–19. 10.1016/S0893-9659(99)00179-2
Huang NJ, Tang YY, Liu YP: Some new existence theorems for nonlinear inclusion with an application. Nonlinear Funct. Anal. Appl. 2001, 6: 341–350.
Jeong JU: Generalized set-valued variational inclusions and resolvent equations in Banach spaces. Comput. Math. Appl. 2004, 47: 1241–1247. 10.1016/S0898-1221(04)90118-6
Ding XP, Luo CL: Perturbed proximal point algorithms for generalized quasi-variational-like inclusions. J. Comput. Appl. Math. 2000, 210: 153–165.
Verma RU: Approximation-solvability of a class of A-monotone variational inclusion problems. J. KSIAM 2004, 8(1):55–66.
Huang NJ: Nonlinear implicit quasi-variational inclusions involving generalized m -accretive mappings. Arch. Inequal. Appl. 2004, 2(4):413–425.
Fang YP, Huang NJ: H -accretive operators and resolvent operator technique for solving variational inclusions in Banach spaces. Appl. Math. Lett. 2004, 17(6):647–653. 10.1016/S0893-9659(04)90099-7
Lan HY, Cho YJ, Verma RU:On nonlinear relaxed cocoercive inclusions involving -accretive mappings in Banach spaces. Comput. Math. Appl. 2006, 51: 1529–1538. 10.1016/j.camwa.2005.11.036
Fang YP, Huang NJ, Thompson HB:A new system of variational inclusions with -monotone operators in Hilbert spaces. Comput. Math. Appl. 2005, 49: 365–374. 10.1016/j.camwa.2004.04.037
Zhang QB, Zhanging XP, Cheng CZ: Resolvent operator technique for solving generalized implicit variational-like inclusions in Banach space. J. Math. Anal. Appl. 2007, 20: 216–221.
Li HG:Perturbed Ishikawa iterative algorithm and stability for nonlinear mixed quasi-variational inclusions involving -accretive mappings. Adv. Nonlinear Var. Inequal. 2008, 11(1):41–50.
Zadeh LA: Fuzzy sets. Inf. Control 1965, 8: 338–353. 10.1016/S0019-9958(65)90241-X
El Ghoul M, EI-Zohny H, Radwan S: Fuzzy incidence matrix of fuzzy simplicial complexes and its folding. Chaos Solitons Fractals 2002, 13: 33–1827.
El Sayied HK: Study on generalized convex fuzzy bodies. Appl. Math. Comput. 2004, 152: 1–8. 10.1016/S0096-3003(03)00527-7
Kaleva O, Seikkala S: On fuzzy metric spaces. Fuzzy Sets Syst. 1984, 12: 29–215.
Park JH: Intuitionistic fuzzy metric spaces. Chaos Solitons Fractals 2004, 22: 46–1039.
Adibi H, Cho YJ, O’Regan D, Saadati R: Common fixed point theorems in L-fuzzy metric spaces. Appl. Math. Comput. 2006, 182: 8–820.
Alaca C, Turkoglu D, Yildiz C: Fixed points in intuitionistic fuzzy metric spaces. Chaos Solitons Fractals 2006, 29: 8–1073.
Chang SS, Cho YJ, Lee BS, Jung JS, Kang SM: Coincidence point and minimization theorems in fuzzy metric spaces. Fuzzy Sets Syst. 1997, 88: 28–119.
Gregori V, Sapena A: On fixed point theorem in fuzzy metric spaces. Fuzzy Sets Syst. 2002, 125: 52–245.
Saadati R, Razani A, Adibi H: A common fixed point theorems in L-fuzzy metric spaces. Chaos Solitons Fractals 2007, 33: 63–358.
Diamond P, Kloeden P, Pokrovskii A: Absolute retracts and a general fixed point theorem for fuzzy sets. Fuzzy Sets Syst. 1997, 86: 80–377.
Kaleva O: On the convergence of fuzzy sets. Fuzzy Sets Syst. 1985, 17: 53–65. 10.1016/0165-0114(85)90006-5
Diamond P, Kloeden P: Characterization of compact subsets of fuzzy sets. Fuzzy Sets Syst. 1989, 29: 8–341.
Puri ML, Ralescu DA: The concept of normality for fuzzy random variables. Ann. Probab. 1985, 13: 9–1373.
Diamond P, Kloeden P: Metric spaces of fuzzy sets. Fuzzy Sets Syst. 1990, 35: 9–241.
Klement EP, Puri ML, Ralescu DA: Limit theorems for fuzzy random variables. Proc. R. Soc. Lond. Ser. A 1986, 407: 82–171.
El Naschie MS: On the uncertainty of Cantorian geometry and two-slit experiment. Chaos Solitons Fractals 1998, 9: 29–517. 10.1016/S0960-0779(97)00046-5
El Naschie MS: On an eleven dimensional E-infinity fractal spacetime theory. Int. J. Nonlinear Sci. Numer. Simul. 2006, 7: 9–407.
Chang SS, Zhou HY: On variational inequalities for fuzzy mappings. Fuzzy Sets Syst. 1989, 32: 359–367. 10.1016/0165-0114(89)90268-6
Chang SS, Huang NJ: Generalized complementarity problem for fuzzy mappings. Fuzzy Sets Syst. 1993, 55: 227–234. 10.1016/0165-0114(93)90135-5
Ding XP, Jong YP: A new class of generalized nonlinear implicit quasivariational inclusions with fuzzy mappings. J. Comput. Appl. Math. 2002, 138: 243–257. 10.1016/S0377-0427(01)00379-X
Jin MM: Perturbed proximal point algorithm for general quasi-variational inclusions with fuzzy set-valued mappings. OR Trans. 2005, 9(3):31–38.
Li HG:Iterative algorithm for a new class of generalized nonlinear fuzzy set-valued variational inclusions involving -monotone mappings. Adv. Nonlinear Var. Inequal. 2007, 10(1):89–100.
Eckstein J, Bertsekas DP: On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators. Math. Program. 1992, 55: 293–318. 10.1007/BF01581204
Verma RU:A hybrid proximal point algorithm based on the -maximal monotonicity framework. Appl. Math. Lett. 2008, 21: 142–147. 10.1016/j.aml.2007.02.017
Li HG:Approximate algorithm of solutions for general nonlinear fuzzy multivalued quasi-variational inclusions with -monotone mappings. Nonlinear Funct. Anal. Appl. 2008, 13(2):277–289.
Xu HK: Inequalities in Banach spaces with applications. Nonlinear Anal. 1991, 16(12):1127–1138. 10.1016/0362-546X(91)90200-K
Nadler SB: Multivalued contraction mappings. Pac. J. Math. 1969, 30: 475–488. 10.2140/pjm.1969.30.475
Agarwal RP, Huang NJ, Cho YJ: Generalized nonlinear mixed implicit quasi-variational inclusions. Appl. Math. Lett. 2000, 13(6):19–24. 10.1016/S0893-9659(00)00048-3
Weng XL: Fixed point iteration for local strictly pseudo-contractive mapping. Proc. Am. Math. Soc. 1991, 113: 727–732. 10.1090/S0002-9939-1991-1086345-8
Jin MM: Perturbed algorithm and stability for strongly nonlinear quasi-variational inclusion involving H -accretive operators. Math. Inequal. Appl. 2006, 9(4):771–779.
Huang NJ, Fang YP: Generalized m -accretive mappings in Banach spaces. J. Sichuan Univ. 2001, 38(4):591–592.
Shim SH, Kang SM, Huang NJ, Yao JC: Perturbed iterative algorithms with errors for completely generalized strongly nonlinear implicit variational-like inclusions. J. Inequal. Appl. 2000, 5(4):381–395.
Chang SS, Cho YJ, Zhou HY: Iterative Methods for Nonlinear Operator Equations in Banach Spaces. Nova Sci. Publ., New York; 2002.
Agarwal RP, Cho YJ, Huang NJ: Sensitivity analysis for strongly nonlinear quasi-variations. Appl. Math. Lett. 2000, 13: 19–24.
Li HG, Xu AJ, Jin MM:A Ishikawa-hybrid proximal point algorithm for nonlinear set-valued inclusions problem based on -accretive framework. Fixed Point Theory Appl. 2010., 2010: Article ID 501293 10.1155/2010/501293
Alimohammady M, Balooee J, Cho YJ, Roohi M: New perturbed finite step iterative algorithms for a system of extended generalized nonlinear mixed-quasi variational inclusions. Comput. Math. Appl. 2010, 60: 2953–2970. 10.1016/j.camwa.2010.09.055
Yao Y, Cho YJ, Liou Y: Iterative algorithms for variational inclusions, mixed equilibrium problems and fixed point problems approach to optimization problems. Cent. Eur. J. Math. 2011, 9: 640–656. 10.2478/s11533-011-0021-3
Yao Y, Cho YJ, Liou Y: Algorithms of common solutions for variational inclusions, mixed equilibrium problems and fixed point problems. Eur. J. Oper. Res. 2011, 212: 242–250. 10.1016/j.ejor.2011.01.042
Cho YJ, Reza S, Damjanovi B: On convergence of Ishikawa’s type iteration to a common fixed point in L -fuzzy metric spaces. J. Comput. Anal. Appl. 2010, 12(1A):76–82.
Li HG: Nonlinear inclusion problems for ordered RME set-valued mappings in ordered Hilbert spaces. Nonlinear Funct. Anal. Appl. 2011, 16(1):1–8.
Li HG:Nonlinear inclusion problem involving -NODM set-valued mappings in ordered Hilbert space. Appl. Math. Lett. 2012, 25: 1384–1388. 10.1016/j.aml.2011.12.007
Pan XB, Li HG, Xu AJ: The over-relaxed a-proximal point algorithm for general nonlinear mixed set-valued inclusion framework. Fixed Point Theory Appl. 2011., 2011: Article ID 840978 10.1155/2011/840978
Li H-G, Xu A-J: A new class of generalized nonlinear random set-valued quasi-variational inclusion system with random nonlinear -accretive mappings in q -uniformly smooth Banach spaces. Nonlinear Anal. Forum 2010, 15: 001–020.
Li HG, Qiu M: Ishikawa-hybrid proximal point algorithm for NSVI system. Fixed Point Theory Appl. 2012., 2012: Article ID 195 10.1186/1687-1812-2012-195
Acknowledgements
This work was supported by the Mathematical Tianyuan Foundation of China (Grant No. 11126087), the National Natural Science Foundation of China (Grant No. 11201512) and the Natural Science Foundation Project of CQ CSTC (cstc2012jjA00001).
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Li, H.G., Qiu, D., Zheng, J.M. et al. Perturbed Ishikawa-hybrid quasi-proximal point algorithm with accretive mappings for a fuzzy system. Fixed Point Theory Appl 2013, 281 (2013). https://doi.org/10.1186/1687-1812-2013-281
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DOI: https://doi.org/10.1186/1687-1812-2013-281