Abstract
The symmetric function class interacts heavily with other types of functions. One of these is the convex function class, which is strongly related to symmetry theory. In this study, we define a novel class of convex mappings on planes using a fuzzy inclusion relation, known as coordinated up and down convex fuzzy-number-valued mapping. Several new definitions are introduced by placing some moderate restrictions on the notion of coordinated up and down convex fuzzy-number-valued mapping. Other uncommon examples are also described using these definitions, which can be viewed as applications of the new outcomes. Moreover, Hermite–Hadamard–Fejér inequalities are acquired via fuzzy double Aumann integrals, and the validation of these outcomes is discussed with the help of nontrivial examples and suitable choices of coordinated up and down convex fuzzy-number-valued mappings.
Keywords:
fuzzy-interval-valued function on coordinates; coordinated up and down convex fuzzy-number-valued mapping; fuzzy double integral; Hermite–Hadamard–Fejér-type inequalities MSC:
26A33; 26A51; 26D10
1. Introduction
Convex functions are distinguished from other function classes by their widespread application in mathematics, statistics, optimization theory, and applied sciences. This is due to the analytic inequalities, particularly those of the Hermite–Hadamard, Fejér, Hardy, Simpson, and Ostrowski types, that have been established using this concept [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17]. The concept of a convex function is one of the core theorems of inequality theory, detailed as follows:
Definition 1.
The real-valued mapping is called a convex mapping on convex set if
for all If Equation (1) is reversed, then is called a concave mapping on. is affine if and only if it is both a convex and concave mapping.
The Hermite–Hadamard inequality, which is a key component of the widespread use and geometrical interpretation of convex functions, has piqued the interest of researchers in fundamental mathematics. This inequality has piqued the interest of multiple scholars from around the world due to its numerous applications, particularly in the domains of numerical analysis, engineering, physical science, and chemistry. The idea of inequality has advanced rapidly in recent years. For convex functions, several inequalities can be found; however, Hermite–Hadamard’s inequality is one of the most extensively and intensively studied conclusions. It is worthwhile to consider how closely related the theories of inequality and convexity are. As a result of this reality, the concept of inequality becomes more appealing. Many new expansions, generalizations, and definitions of novel convexity have been given in recent years, as have corresponding advancements in the theory of convexity inequality, particularly integral inequality theory. Formally, the Hermite–Hadamard inequality is as follows:
For a convex mapping on convex set , the HH inequality is written as
for all with . If is concave, then Equation (2) is reversed.
If it is a concave function, the inequality in Equation (2) holds in both directions. Based on geometry, the Hermite–Hadamard inequality provides an upper and lower estimate for the integral mean of any convex function defined in a closed and limited domain that encompasses the function’s ends and midpoint. Because of the importance of this inequality, multiple modifications of it have been studied in the literature for various classes of convexity, including harmonically convex, exponentially convex, s-convex, h-convex, and co-ordinate convex functions [18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33].
Moore [34] was the first to consider interval analysis. Moore [35] researched interval methods for obtaining the upper and lower bounds of accurate values of the integrals of interval-valued functions and studied the integration of interval-valued functions in 1979. Bhurjee and Panda [36] devised a framework for determining effective solutions to a broad multi-objective fractional programming problem whose parameters in the objective functions and constraints are intervals. Zhang et al. [37] expanded the ideas of invexity and pre-invexity to interval-valued functions, resulting in KKT optimality requirements for LU-pre-invex and invex optimization problems with an interval-valued objective function. Zhao et al. [38] defined the interval double integral and provided Chebyshev-type inequalities for interval-valued functions. Interval analysis has practical applications in economics, chemical engineering, beam physics, control circuit design, global optimization, robotics, error analysis, signal processing, and computer graphics (see [39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58]).
Budak et al. [59] defined the interval-valued right-sided Riemann–Liouville fractional integral and derived H-H-type inequalities for such integrals. Sharma et al. [60] proposed interval-valued pre-invex functions and proved fractional H-H-type inequalities for them. Zhao et al. [61,62] recently developed the concept of interval-valued coordinated convex functions on coordinates and proved H-H-type inequalities for these interval-valued coordinated convex functions. Furthermore, Budak et al. [63] introduced a new concept of interval-valued fractional integrals on coordinates and used these fractional integrals to analyze H-H-type inequalities for interval-valued coordinated convex functions. Kara et al. [64] demonstrated that the product of two interval-valued convex functions on coordinates has H-H–Fejér-type inclusions. We refer to [65,66,67,68,69,70,71,72,73,74,75,76] and the references therein for more information on the links between the various types of coordinated fuzzy-number-valued mappings, interval-valued functions, and integral inequalities. Similarly, most of the authors work in the field of fuzzy calculus as well as fuzzy fractional calculus. Therefore, we refer the readers to [77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97] and the references therein, which will help in understanding fuzzy theory.
Motivated and inspired by the above ongoing research, this manuscript is divided into four sections. In the second section, we recall some classical and preliminary notions and results which will be helpful in discussing the main outcomes. In the third section, some new estimates of integral inequalities via fuzzy double Aumann integrals and a newly defined coordinated class of convex fuzzy-number mappings on up and down fuzzy relations are presented. Some interesting examples are also given to illustrate the main outcomes. In the final section, some conclusions and future plans are discussed.
2. Preliminaries
First, we will review the fundamental notions of fuzzy mathematics. Additional information can be found in the following references: Anastassiou [77]; Anastassiou and Gal [78]; Gal [79]; Goetschel and Voxman [82]; Gal [83]; and Wu and Zengtai [84].
Let be a fuzzy number. Then, this fuzzy number is also represented as -level sets defined as
which is a bounded and closed interval of and denoted as
For and , the sum , product , scalar product , and sum with the scalar are uniquely defined as, for all we obtain
For , such that via this result, we then determine the existence of Hukuhara difference between and , and we can say that is the H-difference between and and is denoted as . If H-difference exists, then
For where is the space of all closed and bounded intervals of real numbers , the Hausdorff–Pompeiu distance between the intervals and is defined as
It is a known fact that is a complete metric space [82].
Theorem 1
([82]). The space dealing with a supremum metric, i.e., for
is a complete metric space, where denotes the well-known Hausdorff metric in the space of intervals.
Remark 1
([86,87]). Let be the space of all closed and bounded intervals of real numbers . The relation is defined in as
for all and it is known as the left and right relation.
The inclusion means that
It is known as the up and down relation.
Proposition 1
([86]). If , then relation is defined in as
and this relation is known as the left and right fuzzy relation.
Proposition 2
([80]). If , then relation is defined in as
and this relation is known as the up and down fuzzy relation.
Definition 2
([90]). The IVM is said to be a coordinated convex function on if
for all and If inequality Equation (11) is reversed, then is called a coordinated concave IVM on.
Definition 3
([87]). The FN-V-M is said to be an up and down convex FN-V-M on if
for all where. If is an up and down concave FN-V-M on, then inequality Equation (12) is reversed.
Theorem 2
([85]). Let be two up and down convex FN-V-Ms. Then, from the -levels, we obtain the collection of IVMs given as and for all and for all . If is a fuzzy Riemann integrable, then
and
where and and
Theorem 3
([85]). Let be an up and down convex FN-V-M with . Then, from the -levels, we obtain the collection of IVMs given as for all and for all . If and symmetric with respect to and , then
If is an up and down concave FN-V-M, then inequality Equation (15) is reversed.
If , then via Equation (15) we obtain following inequality:
Theorem 4
([36]). If is an IVM given as , then is Riemann-integrable on if and only if and are both Riemann-integrable on , such that
The collection of all Riemann-integrable real-valued functions and Riemann-integrable IVMs is denoted as and respectively.
Note that Theorem 5 is also true for interval double integrals. The collection of all double-integrable IVMs is denoted as respectively.
Theorem 5
([38]). Let . If is -integrable on , then we obtain
Definition 4
([91]). A fuzzy-interval-valued map is called an FN-V-M on coordinates. Then, from the -levels, we obtain the collection of IVMs on coordinates given as for all Herein, for each the end-point real-valued functions are called the lower and upper functions of .
Definition 5
([91]). Let be a coordinated FN-V-M. Then, is said to be continuous at if for each both the end-point functions and are continuous at
Definition 6
([91]). Let be an FN-V-M on coordinates. Then, the fuzzy double integral of on denoted as , is defined level-wise as
for all and
is
-integrable on
if
Note that if the end-point functions are Lebesgue-integrable, then
is a fuzzy double-Aumann-integrable function on
.
Theorem 6
([91]). Let be an FN-V- M on coordinates. Then, from the -levels, we obtain the collection of IVMs given as for all and for all Then, is -integrable on if and only if and are both -integrable on Moreover, if is -integrable on then
for all
3. Main Results
In this section, we will first propose the new class of coordinated convex functions with the up and down fuzzy relation, which are known as coordinated UD-convex FN-V-Ms. Secondly, we will present 𝐻𝐻–Fejér inequalities with the help of this new class and double fuzzy integrals as well as verify them with the support of some useful examples.
Definition 7.
The FN-V-M is said to be a coordinated UD-convex FN-V-M on if
for all and
where
If inequality Equation (21) is reversed, then
is called a coordinated concave FN-V-M on
.
The straightforward proof of Lemma 1 will be omitted herein.
Lemma 1.
Let be a coordinated FN-V-M on . Then, is a coordinated UD-convex FN-V-M on if and only if two coordinated UD-convex FN-V-Ms exist, , and ,
Proof.
From the definition of the coordinated FN-V-M, it can be easily proved. □
From Lemma 1, we can easily note that each UD-convex FN-V-M is a coordinated UD-convex FN-V-M. However, the converse is not true (see Example 1).
Theorem 7.
Let be an FN-V-M on . Then, from the -levels, we obtain the collection of IVMs given as
for all and for all
. Then,
is a coordinated UD-convex FN-V-M on
if and only if for all
and
are coordinated UD-convex and concave functions, respectively.
Proof.
Assume that for each and are coordinated UD-convex on Then, from Equation (21), for all and we obtain
and
Then, via Equations (4), (6) and (22), we obtain
That is,
Hence, is a coordinated UD-convex FN-V-M on .
Conversely, let be a coordinated UD-convex FN-V-M on Then, for all and we obtain
Therefore, from Equation (22), for each , we obtain
Again, via Equation (22), we obtain
for all and Then, via the coordinated UD-convexity of , for all and we obtain
and
for each Hence, the result follows. □
Example 1.
We consider the FN-V-Ms defined as
and then, for each
we obtain
. The end-point functions
and
are coordinated convex and concave functions for each
. Hence,
is an up and down coordinated convex FN-V-M.
From Example 1, it can be easily seen that each coordinated UD-convex FN-V-M is not a UD-convex FN-V-M.
Corollary 1.
Let be an FN-V-M on . Then, from the -levels, we obtain the collection of IVMs given as
for all
and for all
. Then,
is a coordinated left-UD-convex (concave) FN-V-M on
if and only if for all
and
are coordinated convex (concave) and affine functions on
, respectively.
Corollary 2.
Let be an FN-V-M on . Then, from the -levels, we obtain the collection of IVMs given as
for all and for all
. Then,
is a coordinated right-UD-convex (concave) FN-V-M on
if and only if for all
and
are coordinated affine and convex (concave) functions on
, respectively.
Theorem 8.
Let be a coordinated convex set, and let be an FN-V- M. Then, from the -levels, we obtain the collection of IVMs given as
for all
and for all
. Then,
is a coordinated UD-concave FN-V-M on
if and only if for all
and
are coordinated concave and convex functions, respectively.
Proof.
The demonstration of the proof of Theorem 8 is similar to the demonstration of the proof of Theorem 7. □
Example 2.
We consider the FN-V-Ms defined as
Then, for each we obtain . The end-point functions are coordinated concave and convex functions for each . Hence, is a coordinated up and down concave FN-V-M.
In the next results, to avoid confusion, we will not include the symbols , , , , and before the integral sign.
Theorem 9.
Let be a coordinated UD-convex FN-V-M on . Then, from the -levels, we obtain the collection of IVMs given as for all and for all . Then, the following inequality holds:
If
is a concave FN-V-M, then
Proof.
Let be a coordinated UD-convex FN-V-M. Then, via hypothesis, we obtain
By using Theorem 7, for every , we obtain
By using Lemma 1, we obtain
and
From Equations (30) and (31), we obtain
and
It follows that
and
Since and are both coordinated UD-convex-IVMs, from Theorem 7 and inequality Equation (6), for every , and inequality Equations (32) and (33), we then obtain
and
Dividing double inequality Equation (34) by and integrating with respect to on we obtain
Similarly, dividing double inequality Equation (35) by and integrating with respect to on we obtain
By adding Equations (36) and (37), we obtain
Since is an FN-V-M, via inequality Equation (38), we then obtain
From Theorem 7 and the left side of inequality Equation (16), for each , we obtain
Adding inequality Equation (40) and inequality Equation (41), we obtain
Since is an FN-V-M, it follows that
Now, from Theorem 7 and the right side of inequality Equation (16), for every , we obtain
By adding inequalities Equations (43)–(46), we obtain
Since is an FN-V-M, it follows that
By combining inequalities Equations (41), (42), and (47), we obtain the desired result. □
Remark 2.
From inequality Equation (28), the following exceptional results can be acquired:
Let
with
. Then, we can derive the following inclusion (see [61]):
Let
with
. Then, we can derive the following inclusion (see [90]):
Example 3.
We consider the FN-V-Ms defined as
and then, for each
we obtain
. The end-point functions
are coordinated concave functions for each
. Hence,
is a coordinated concave FN-V-M.
That is
Hence, Theorem 9 has been verified.
We will now obtain some 𝐻𝐻 inequalities to produce coordinated UD-convex FN-V-Ms. These inequalities are refinements of some Pachpatte-type inequalities on coordinates.
Theorem 10.
Let be two coordinated UD-convex FN-V-Ms on whose -levels are defined as and for all and for all . Then, the following inequality holds:
where
and for each
, and
are defined as follows:
Proof.
Let and be two coordinated UD-convex FN-V- Ms on . Then,
and
Since and are both coordinated UD-convex FN-V-Ms, then via Lemma 1, the following exist:
and
Since , and are FN-V-Ms, then via inequality Equation (13), we obtain
and
For each we obtain
and
The above inequalities can be written as
and
Firstly, we will solve inequality Equation (52). Integrating both sides of the inequality with respect to on the interval and dividing both sides by , we obtain
Now, via inequality Equation (13), for each we obtain
From Equations (55)–(58) and inequality Equation (54), we obtain
That is,
Hence, this concludes the proof of the theorem. □
Theorem 11.
Let be two UD-convex FN-V-Ms. Then, from the -levels, we obtain the collection of IVMs given as and for all and for all . Then, the following inequality holds:
where
,
and
are given in Theorem 10.
Proof.
Since are two UD-convex FN-V-Ms, then from inequality Equation (14) and for each we obtain
and
Summing inequalities Equations (60) and (61) and then multiplying the result by 2, we obtain
Now, with the help of integral inequality Equation (14), for each integral on the right-hand side of Equation (62), we obtain
From Equations (63)–(70), we obtain
Now, with the help of integral inequality Equation (14) for the first two integrals on the right-hand side of Equation (71), we obtain the following relation:
From Equations (72) and (73), we obtain
It follows that
Now, using integral inequality Equation (13) for the integrals on the right-hand side of Equation (74), we obtain the following relation
From Equations (75)–(82) and inequality Equation (74), we obtain
That is,
We will now obtain the 𝐻𝐻–Fejér inequality for coordinated UD-convex FN-V-Ms by means of FOR in the following result. □
Theorem 12.
Let be a coordinated UD-convex FN-V-M with and Then, from the -levels, we obtain the collection of IVMs given as for all and for all . Let with and with be two symmetric functions with respect to and , respectively. Then, the following inequality holds:
Proof.
Since is a coordinated UD-convex FN-V-M on , and it follows those functions, then via Lemma 1, the following exist:
Thus, from inequality Equation (15), for each we obtain
and
The above inequalities can be written as
and
Multiplying Equation (84) by and then integrating the result with respect to on , we obtain
Now, multiplying Equation (85) by and then integrating the result with respect to on , we obtain
Since and then by dividing Equations (86) and (87) by and , respectively, we obtain
Now, from the left part of double inequalities Equations (84) and (85), we obtain
and
Summing inequalities Equations (89) and (90), we obtain
Similarly, from the right part of Equations (84) and (85), we obtain
and
Adding Equations (92)–(95) and dividing by 4, we obtain
Combining inequalities Equations (88), (91), and (96), we obtain
That is,
Hence, this concludes the proof. □
Remark 3.
From inequality Equation (56), the following exceptional results can be acquired:
If
, one can then obtain inequality Equation (36).
Let
with
. Then, one can derive following inclusion [61]:
Let
be a left coordinated UD-convex FN-V-M. Then, we can achieve the following outcome (see [91]):
Let
be a left coordinated UD-convex FN-V-M and
. Then, we can achieve the following outcome (see [91]):
Let
with
and Then, we acquire following inequality (see [90]):
Let
with
. Then, we can derive the following inclusion:
4. Conclusions
In this paper, we introduced and studied a new class of generalized convex fuzzy mappings on coordinates involving the up and down fuzzy relation, which are known as coordinated up and down convex fuzzy mappings. Several new versions of integral inequalities for this class of functions were obtained. It is interesting to note that most of the classes and other results are also exceptional cases of our defined class and main results, and these exceptional cases of our results are discussed as applications. For the validation of our main outcomes in this paper, some examples were also proved. In future, this concept will be explored in the field of quantum calculus.
Author Contributions
Conceptualization, M.B.K.; methodology, M.B.K.; validation, M.B.K. and M.S.S.; formal analysis, C.-T.L. and C.-C.L.; investigation, M.B.K.; resources, M.B.K. and C.-C.L.; data curation, M.B.K. and A.A.; writing—original draft preparation, M.B.K.; writing—review and editing, M.B.K.; visualization, M.S.S., C.-T.L., C.-C.L. and A.A.; supervision, M.B.K.; project administration, M.S.S.; funding acquisition, M.B.K. and C.-T.L. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported in part by the National Science and Technology Council in Taiwan under contract no. NSTC 110-2410-H-165-001-MY2. Also, the researchers also would like to acknowledge Deanship of Scientific Research, Taif University for funding this work.
Data Availability Statement
Not applicable.
Acknowledgments
The authors would like to thank the Rector of COMSATS University Islamabad, Islamabad, Pakistan, for providing excellent research. The researchers would like to acknowledge Deanship of Scientific Research, Taif University for funding this work.
Conflicts of Interest
The authors declare no conflict of interest.
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