An Algebraic Approach to Modular Inequalities Based on Interval-Valued Fuzzy Hypersoft Sets via Hypersoft Set-Inclusions
Abstract
Interval-valued fuzzy hypersoft set is an emerging field of study which is projected to address the limitations of interval-valued fuzzy soft set for the entitlement of multiargument approximate function. This kind of function maps the subparametric tuples to power set of universe. It emphasizes on the partitioning of attributes into their respective subattribute values in the form of disjoint sets. These features make it a completely new mathematical tool for solving problems dealing with uncertainties. In this study, after characterization of essential properties, operations, and set-inclusions (-inclusion and -inclusion) of interval-valued fuzzy hypersoft set, some of its modular inequalities are discussed via set-inclusions. It is proved that all set-inclusion-based properties and inequalities are preserved when ordinary approximate function of interval-valued fuzzy soft set is replaced with multiargument approximate function of interval-valued fuzzy hypersoft set.
1. Introduction
Molodtsov [1] initiated the concept of soft set (s-set) to equip fuzzy set-like models [2–4] with parameterization tool. This set employs the concept of approximate function which maps single set of parameters to initial set of alternatives. This function is also known as single-argument approximate function (SAAF) due to consideration of single set of parameters as its domain. Many researchers contributed towards the characterization of rudiments of s-sets but works of Maji et al. [5], Ali et al. [6], and Ge and Yang [7] for the investigation on set-theoretic operations and Babitha and Sunil [8, 9] for the introduction of relations and functions are more significant. Pei and Miao [10] introduced information system based on s-sets to handle the informational vagueness. Li [11] extended the previous work on soft operations and introduced some new operations. Feng and Li [12] investigated in detail the soft subset and soft product operations. Liu et al. [13] made discussion on generalized soft equal relations. Maji et al. [14] developed fuzzy soft set (fs-set) by combining fuzzy set (f-set) and s-set to deal uncertainties with parameterization tools. Yang et al. [15] hybridized interval-valued fuzzy set (ivf-set) [16] with s-set and developed interval-valued fuzzy soft set (ivfs-set) to tackle uncertain scenarios having interval nature of information and data. Jun and Yang [17] rectified some results on ivfs-sets presented by Yang et al. Chetia and Das [18] applied the notions of ivfs-sets in decision-making for medical diagnosis, Jiang et al. [19] calculated the entropy of ivfs-sets, and Feng et al. [20] characterized level soft sets based on ivfs-sets and applied them in decision-making. Liu et al. [21, 22] discussed some nonclassical properties of ivfs-sets and their modular inequalities based on soft -inclusion.
In many real-world decision-making scenarios, the classification of parameters into their respective subparametric-valued disjoint sets is considered necessary for having reliable and precise decisions. Soft set-like structures (hybridized structures of soft set) are inadequate to tackle such scenarios. Smarandache [23] conceptualized hypersoft set (hs-set) to address the limitations of soft set-like models. In hs-set, set of parameters is further partitioned into disjoint sets having subparametric values. It employs an approximate function which maps the cartesian product of attribute-valued nonoverlapping sets to collection of alternatives. In this way, this function is also called multiargument approximate function (MAAF). Saeed et al. [24] discussed some elementary properties and set-theoretic operations of hs-set with numerical examples. Abbas et al. [25] characterized the notions of hs-points and hs-function for their utilization in the development of hs-function spaces. Ihsan et al. [26] and Rahman et al. [27] developed hs-expert set and bijective hs-set respectively and discussed their applications in multiattribute decision-making (MADM). Rahman et al. [28] introduced a conceptual framework for classical convexity cum concavity under hs-set environment. The researchers Yolcu and Ozturk [29], Jafar and Saeed [30], and Debnath [31] discussed decision-making applications based on fuzzy hypersoft set (fhs-set) (a hybridized structure of f-set and hs-set). Rahman et al. [32] investigated the parameterization of hs-set under fuzzy setting and discussed its utilization in decision-making. The authors Saeed et al. [33] and Rahman et al. [34, 35] developed hybridized structures of fhs-set with complex set in order to tackle periodic nature of data.
- (1)
The situation where uncertain nature of alternatives (entities in universal set) is required to be judged by assigning fuzzy membership grades to each entity corresponding to each parameter
- (2)
The scenarios where classification of parameters into their respective parametric valued subcollections is necessary to be considered
- (3)
The scenarios which has a big collection of interval-base information which is required to be tackled with the help of its interval-valued approximate setting
Therefore, motivating from the above described shortcoming of literature, this study is aimed at developing a new structure ivfhs-sets which is more flexible as compared to existing models because it is capable to manage their limitations and is useful for having reliable and unbiased decisions due to deep focusing on parameters and their sub-parametric tuples. Some contributions of this research are (i) basic notions of ivfhs-set are characterized; (ii) the notions of soft inclusions discussed in [13, 17] are generalized for ivfhs-sets; and (iii) modular inequalities for ivfhs-sets based on hs-inclusions are explored by extending the concepts of Liu et al. [21, 22] and Jun and Yang [17]. The rest of the paper is structured as follows: Section 2 recalls some essential basic definitions, properties, and results relating to ivfs-set, hs-set, and fhs-set to support the main results. Section 3 presents the basic notions, properties, and inclusions of ivfhs-sets with discussion on some particular cases of ivfhs-sets. In Section 4, modular inequalities of ivfhs-sets via -inclusion are discussed. In Section 5, modular inequalities of ivfhs-sets via -inclusion are discussed. Section 6 summarizes the paper with some future directions.
2. Preliminaries
This section reviews few elementary terminologies and properties from literature for proper understanding of main results. Throughout the paper, , and denote initial universe, power set of , unit closed interval, and set of parameters, respectively.
Definition 1 (see [16].)Assume the set and the order relation stated by if and only if for all , then forms a complete lattice. An ivf-set over is characterized by mapping , where is called membership function of . The collection of all ivf-sets over is represented by Ωivfs.
Definition 2 (see [1].)Let be an initial universe and be a set of parameters then a SAAF is a mapping and defined as , where denotes the power set of , with k ≤ n. The pair is known as s-set and represented by . The subsets are known as -approximate sets having all -approximate elements. The pair is called soft-universe. The collection of s-sets is denoted by Ωss.
Definition 3 (see [17].)For any soft-universe with , an ivfs-set is characterized by mapping , where is the same as stated in Definition 2, and is known as SAAF of . The collection of ivfs-sets is denoted by Ωivfss.
Definition 4 (see [15].)Let , then their soft product operations, i.e., ∧&∨ are given as:
- (1)
The ∧-product (AND-operation) of and is an ivfs-set defined by
- (2)
The ∨-product (OR-operation) of and is an ivfs-set defined by
The following two soft-inclusions relations Jun’s inclusion in [17] and Liu’s inclusion in [13] are prominent in literature for understanding the set-theoretic operations of ivfs-sets.
Definition 5 (see [17].)Let , then
- (1)
is said to be ivfs -subset of , denoted by , if for every such that
- (2)
and are said to be ivfs -equal, denoted by , if and
Liu et al. [13] introduced the following soft inclusions by modifying the soft inclusion of Jun and Yang [17].
Definition 6 (see [13].)Let , then
- (1)
is said to be ivfs -subset of , denoted by , if for every such that
- (2)
and are said to be ivfs -equal, denoted by , if and
Note: both and are termed as ivfs -inclusion and ivfs -inclusion respectively.
Proposition 7. If , then it implies .
Definition 8 (see [13].) is said to be identical to , denoted by , if and for every .
Proposition 9. If , then it implies which further implies .
Propositions 7 and 9 are not valid in general. Please refer to [12, 13] for detailed discussion regarding the generalization of these results.
Definition 10 (see [23].)Let be an initial universe and be a set of parameters. The respective attribute-valued nonoverlapping sets of each element of are , , , ….., and , where each is a n-tuple element of and , |•| denotes set cardinality, then a MAAF is a mapping and defined as , where denotes the power set of , with k ≤ r. The pair is known as hs-set and represented by . The collection of all hs-sets is symbolized as Ωhss.
3. Properties of ivfhs-Sets
In this section, novel notions of ivfhs-sets are characterized. During this characterization, focus is laid on those operations and properties which are essential to proceed further for the development of modular inequalities.
Definition 12. Let be an initial universe and be a set of parameters. The respective subparametric-valued disjoint sets are , , ,….., ,and , where each is a n-tuple element of and , |•| denotes set cardinality then the pair is known as ivfhs-set, where and defined as , and with k ≤ s. The collection of all ivfhs-sets is symbolized as .
Example 1. Suppose an organization plans to recruit a candidate to fill a vacant post of assistant manager. There are six candidates forming an initial universe of discourse and have been scrutinized by recruitment committee. The committee further requires evaluation to select one of these candidates. The evaluation indicators are qualification , relevant experience in years , and computer skill . Their subparametric disjoint sets are , , and respectively such that . Then, an ivfhs-set is structured as , where
Its tabular representation is given in Table 1.
Definition 13. The complement of an ivfhs-set , denoted by , is defined by where and stands for "not .
Example 2. Considering data from Example 1, we have
Its tabular representation is given in Table 2.
Definition 14. Let be two ivfhs-sets then their hypersoft aggregation operations, i.e., are given as:
- (1)
Their union is an ivfhs-set defined by such that with maximum interval-valued fuzzy degrees respective to and
- (2)
Their intersection is an ivfhs-set defined by such that with minimum interval-valued fuzzy degrees respective to and
Definition 15. Let be two ivfhs-sets, then their hypersoft product operations, i.e., are given as:
- (1)
The -product (AND-operation) is an ivfhs-set defined by such that
- (2)
The -product (OR-operation) is an ivfhs-set defined by such that
Example 4. Considering the values of two ivfhs-sets from Example 3, then
Their tabular representations are presented in Tables 3 and 4.
|
[0.2,0.4] | [0.3,0.5] | [0.4,0.6] | [0.5,0.7] |
|
[0.3,0.6] | [0.4,0.7] | [0.5,0.8] | [0.6,0.9] |
|
[0.1,0.5] | [0.2,0.6] | [0.3,0.7] | [0.4,0.8] |
|
[0.6,0.8] | [0.5,0.7] | [0.4,0.6] | [0.3,0.5] |
|
[0.4,0.7] | [0.3,0.6] | [0.2,0.5] | [0.1,0.4] |
|
[0.5,0.9] | [0.4,0.8] | [0.3,0.7] | [0.2,0.6] |
|
[0.2,0.4] | [0.3,0.5] | [0.4,0.6] | [0.5,0.7] |
|
[0.3,0.6] | [0.4,0.7] | [0.5,0.8] | [0.6,0.9] |
|
[0.1,0.5] | [0.2,0.6] | [0.3,0.7] | [0.4,0.8] |
|
[0.3,0.4] | [0.4,0.5] | [0.5,0.6] | [0.6,0.7] |
|
[0.3,0.6] | [0.4,0.7] | [0.5,0.8] | [0.6,0.9] |
|
[0.2,0.5] | [0.3,0.6] | [0.4,0.7] | [0.5,0.8] |
|
[0.1,0.4] | [0.2,0.5] | [0.3,0.6] | [0.4,0.7] |
|
[0.1,0.5] | [0.2,0.6] | [0.3,0.7] | [0.4,0.8] |
|
[0.1,0.5] | [0.2,0.6] | [0.3,0.7] | [0.4,0.8] |
|
[0.3,0.4] | [0.4,0.5] | [0.5,0.6] | [0.6,0.7] |
|
[0.4,0.6] | [0.5,0.7] | [0.6,0.8] | [0.7,0.9] |
|
[0.2,0.5] | [0.3,0.6] | [0.4,0.7] | [0.5,0.8] |
|
[0.3,0.6] | [0.4,0.7] | [0.5,0.8] | [0.6,0.9] |
|
[0.4,0.6] | [0.5,0.7] | [0.6,0.8] | [0.7,0.9] |
|
[0.2,0.5] | [0.3,0.6] | [0.4,0.7] | [0.5,0.8] |
|
[0.3,0.5] | [0.4,0.6] | [0.5,0.7] | [0.6,0.8] |
|
[0.4,0.6] | [0.5,0.7] | [0.6,0.8] | [0.7,0.9] |
|
[0.2,0.5] | [0.3,0.6] | [0.4,0.7] | [0.5,0.8] |
Now, we present the generalized version of -inclusion and -inclusion for ivfhs-sets with entitlement of multiargument approximate functions.
Definition 16. Let be two ivfhs-sets then
- (1)
is said to be ivfhs -subset of , denoted by , if for every such that
- (2)
and are said to be ivfhs -equal, denoted by , if and
Definition 17. Let be two ivfhs-sets, then
- (1)
is said to be ivfs -subset of , denoted by , if for every such that
- (2)
and are said to be ivfs -equal, denoted by , if and
Note: both and are named as ivfhs -inclusion and ivfhs -inclusion, respectively.
Proposition 18. If , then it implies .
Definition 19. Let be two ivfhs-sets then is said to be identical to , denoted by , if and for every .
Proposition 20. If , then it implies which further implies .
Proof. Let , then by Definition 19, we have and for every . By Definition 17 part (1), we get . Now, applying Proposition 18, we obtain .
It is pertinent to mention here that the results presented in Propositions 18 and 20 are not legitimate in general. Both and are preorder for .
Proposition 21. The relations and satisfy the properties of equivalence relation on .
Proof. Applying the concept stated in Definitions 16 and Definitions 17, it is clear that both and satisfy reflexive property as and . Their symmetric and transitive nature can also be deduced from these mentioned definitions. These properties collectively conclude that both and are equivalence relations.
We know from classical set theory, for a set D ≠ ∅ with a preorder ≤, an upward directed set is a set (D, ≤) in which every pair of elements in D has an upper bound, i.e., for d1, d2 ∈ D, there exists d3 such that d1 ≤ d3 and d2 ≤ d3. The following definition is the generalized set theoretic version of upward directed set under hypersoft set environment.
Definition 22. An ivfhs-set with is called an upward directed ivfhs-set (UD-ivfhss) if for , there exists such that
Example 5. Considering data from Example 1, we have ivfhs-set as given below
Proposition 23. An ivfhs-set with is an UD-ivfhss if and only if is an UD-ivfhss.
Proof. Let be an UD-ivfhss then by definition of UD-ivfhss, then following conditions hold:
- (i)
and
- (ii)
for such that
The second condition implies that and which proves that is an UD-ivfhss.
Conversely, let is an UD-ivfhss, then the below given clauses hold due to definition of UD-ivfhss:
- (i)
both and are nonempty sets
- (ii)
for , there exists an upper bound for and in which means such that and
The clause (ii) further implies which shows that is an UD-ivfhss.
Proposition 24. An ivfhs-set with is an UD-ivfhss if and only if .
Proof. Let with be an UD-ivfhss. Therefore, there exists corresponding to pair s.t.
Combining above equations, we obtain which shows that but we know that ; hence, .
Conversely, let then implies , that is, there exists corresponding to pair s.t.
Corollary 25. Let be an ivfhs-set with , then the given below statements are equivalent:
- (1)
is an UD-ivfhss over
- (2)
is an UD-ivfhss w.r.t ⊆
Proof. These can easily be verified by considering the consequences of Proposition 23 and Proposition 24.
|
[0.2,0.4] | [0.3,0.5] | [0.4,0.6] | [0.5,0.7] |
|
[0.1,0.5] | [0.2,0.6] | [0.3,0.7] | [0.4,0.8] |
|
[0.3,0.6] | [0.4,0.7] | [0.5,0.8] | [0.6,0.9] |
4. Modular Inequalities of ivfhs-Sets via -Inclusion
Liu et al. [22] discussed some modular inequalities for ivfs-sets which employs approximate function that is unable to tackle multiargument settings (i.e., cartesian product of sub-parametric valued disjoint sets); therefore, in this section, such modular inequalities are generalized to manage such kind of settings.
Let be an initial universe and be a set of parameters. The respective subparametric-valued disjoint sets are , , ,….., ,and , where each is a n-tuple element of , and , |•| denotes set cardinality, then the pair is known as ivfhs-set, where and defined as , and with p ≤ α.
Theorem 26. Let be two ivfhs-sets, then
Theorem 27 (Generalized commutativity of ivfhs-sets). Let be two ivfhs-sets, then
Theorem 28. Let be three ivfhs-sets with , then
Proof.
- (1)
Let and . Since given that which implies that there exists for every such that
Let , then by definition of , we have
By combining Equation (22) and Equation (23), we get
Similarly for , we get
From Equation (24) and Equation (25), we get , which shows that .
- (2)
According to second part of Theorem 27, we have which implies that
Therefore, from Equations (24), (25), and (26), it is vivid that which shows that .
Part 3 and part 4 can easily be verified with the help of Theorem 27(2) and above results.
Theorem 29. Let be two ivfhs-sets with and , then
Theorem 30. Let be three ivfhs-sets with then
Proof.
- (1)
Let and . Since given that which implies that there exists for every such that
Let , then by definition of , we have
By combining Equation (29) and Equation (30), we get
Similarly, for , we get
From Equation (31) and Equation (32), we get which shows that .
- (2)
According to Theorem 27, we have which implies that
Therefore from Equations (31), (32), and (33), it is vivid that which shows that .
Part 3 and part 4 can easily be verified with the help of Theorem 27(2) and above results.
Theorem 31. Let be two ivfhs-sets with and , then .
Theorem 32 (Generalized distributive inequalities of ivfhs-sets). Let be three ivfhs-sets then
5. Modular Inequalities of ivfhs-Sets via -Inclusion
Jun and Yang [17] discussed some modular inequalities for ivfs-sets by extending the concept presented by Liu et al. [22], and this concept too shows inadequacy regarding multiargument approximate settings (i.e., cartesian product of subparametric valued disjoint sets); therefore, in this section, such modular inequalities are generalized to manage such kind of settings.
Let be an initial universe and be a set of parameters. The respective subparametric-valued disjoint sets are , , ,….., ,and , where each is an n-tuple element of and , |•| denotes set cardinality, then the pair is known as ivfhs-set where and defined as , and with k ≤ s.
Theorem 33. Let be two ivfhs-sets, then
Theorem 34. Let be three ivfhs-sets with , then
Theorem 35. Let be two ivfhs-sets with and , then
Theorem 36. Let be three ivfhs-sets with , then
Theorem 37. Let be two ivfhs-sets with
Theorem 38. Let be three ivfhs-sets, then .
Proof. From Theorem 32(1), we have
Corollary 39. Let be three ivfhs-sets then
Proof. From Theorem 27(2), we have
Taking on both sides of above inequality with , we have
Other parts can easily be validated in the similar manner.
Corollary 40. Let be three ivfhs-sets then
Corollary 41. Let be three ivfhs-sets, then
Corollary 42. Let be three ivfhs-sets, then
Theorem 43. Let be three ivfhs-sets. If , then
Proof. From Theorem 32(2), we have
Taking on both sides of above inequality with , we have
Example 6. Let be an initial universe and be a set of attributes. The respective attribute-valued disjoint sets are , , , , and . Let us take , and as subsets of , then we have three ivfhs-sets with
It is clear that , , and ; therefore, .
Consider or with
Now, let or
Now, we find with
Similarly, with
Lastly, with
It can be seen that
is not valid in general.
Corollary 44. Let be three ivfhs-sets. If , then
Proof. From Theorem 27(2), we have
Taking on both sides of above inequality with , we have
Other parts can easily be validated in the similar manner.
Corollary 45. Let be three ivfhs-sets. If , then
Corollary 46. Let be three ivfhs-sets. If , then
Corollary 47. Let be three ivfhs-sets. If , then
Theorem 48. Let be three ivfhs-sets. If and is an UD-ivfhss, then we have
Proof. Since we know from Theorem 43 that
As given that is an UD-ivfhss, therefore, which implies such that
Corollary 49. Let be three ivfhs-sets. If and is an UD-ivfhss, then
Proof. Since we know from Theorem 27 that which further implies that , i.e.,
By applying Theorem 36, we have
Hence,
Corollary 50. Let be three ivfhs-sets. If and is an UD-ivfhss, then
Corollary 51. Let be three ivfhs-sets. If and is an UD-ivfhss, then
Corollary 52. Let be three ivfhs-sets. If and is an UD-ivfhss, then
5.1. Discussion
- (1)
It is capable to manage the uncertain nature of alternatives (entities in universal set) by assigning fuzzy membership grades to each entity corresponding to each parameter
- (2)
It has ability to tackle the scenarios where classification of parameters into their respective parametric-valued subcollections is necessary to be considered
- (3)
It is useful to manage big collection of interval-base information with the help of its interval-valued approximate setting
In short, the ivfhs-set tackle all the above three situations collectively in one model.
6. Conclusion
In this research, some essential elementary rudiments (i.e., properties, set-theoretic operations, and set-inclusions) of ivfhs-set are conceptualized, and then, some modular inequalities of ivfhs-set are established by employing the concept of -inclusion and -inclusion. It is observed that the transformation of approximate function from ivfs-set to ivfhs-set preserve all set-inclusion-based properties and inequalities. As this paper focuses on the fuzzy membership with interval setting under hs-set environment, so it is inadequate for the scenarios where the consideration of falsity degree and indeterminacy degree is mandatory. Therefore, the future work may include the extension of this study to tackle above said scenarios. This can also be extended to the development of algebraic structures based on fuzzy hypersoft set with interval-valued setting.
Conflicts of Interest
The authors declare that there are no conflicts of interest.
Open Research
Data Availability
No data were used to support this study.