Abstract
We aim through this paper to achieve two goals: first, we define some types of belong and nonbelong relations between ordinary points and double-framed soft sets. These relations are one of the distinguishing characteristics of double-framed soft sets and are somewhat expression of the degrees of membership and nonmembership. We explore their main properties and determine the conditions under which some of them are equivalent. Also, we introduce the concept of soft mappings between two classes of double-framed soft sets and investigate the relationship between an ordinary point and its image and preimage with respect to the different types of belong and nonbelong relations. By the notions presented herein, many concepts can be studied on double-framed soft topology such as soft separation axioms and cover properties. Second, we give an educational application of optimal choices using the idea of double-framed soft sets. We provide an algorithm of this application with an example to show how this algorithm is carried out.
1. Introduction
The (crisp) set theory is a main mathematical approach to deal with a class of problems that are characterized by precision, exactness, specificity, perfection, and certainty. However, many problems in the real-life inherently involve inconsistency, imprecision, ambiguity, and uncertainties. In particular, such classes of problems arise in engineering, economics, medical sciences, environmental sciences, social sciences, and many different scopes. The crisp (classical) mathematical tools fail to model or solve these types of problems.
In the course of time, mathematicians, engineers, and scientists, particularly those who focus on artificial intelligence, are seeking for alternative mathematical approaches to solve the problems that contain uncertainty or vagueness. They initiated several set theories such as probability theory, fuzzy set [1], intuitionistic fuzzy set [2], and rough set [3].
In 1999, Molodtsov [4] proposed the concept of soft sets as a new mathematical tool to cope with uncertainties. He investigated the efficiency of soft sets to deal with complicated problems compared with the probability theory and fuzzy set theory. After Molodtsov’s work, many researchers have studied several operations and relations between soft sets (see, for example, [5–10]). Soft sets were applied in various domains such as algebraic structures (see, for example, [11–13]), soft topological spaces (see, for example, [14–16]), and decision-making problems (see, for example, [17–25]). Also, the relationship among soft sets, rough sets, and fuzzy sets was the goal of some papers such as [17, 26, 27].
In the last few years, a number of scholars have extensively studied some extensions of soft set. These studies go into two ways: the first one is initiated by giving some generalizations of the structure of soft sets. This leads to define binary soft set [28], N-soft set [29], double-framed soft set [30], and bipolar soft set [31] (several relations between bipolar soft sets and ordinary points were presented in [32]). The second one is coming from the combination of soft set (or its updating forms) with rough set or fuzzy set or both. This leads to define fuzzy soft set [33], fuzzy bipolar soft set [34], bipolar fuzzy soft set [35], soft rough set [26], bipolar soft rough set [36], and modified rough bipolar soft set [37].
Soft set was formulated over an initial universal set by using a map from a set of parameters into the power set of . However, we need sometimes to define two maps from into the power set of ; for example, if we schedule students’ results in n subjects, we define n different maps over the same sets and . For this purpose, Jun and Ahn [30] initiated the notion of double-framed soft sets and applied in BCK/BCI algebras. In 2014, Muhiuddin and Al-Roqi [38] studied the concept of double-framed soft hypervector spaces, and in 2015, Naz [39] revealed some algebraic properties of double-framed soft set. In 2017, Khana et al. [40] introduced the concept of double-framed soft LA-semigroups. In the same year, Shabir and Samreena [41] made use of a double-framed soft set to define a new soft structure called a double-framed soft topological space. They initiated its basic notions such as DFS open and closed sets and DFS neighborhoods. In 2018, Iftikhar and Mahmood [42] presented some results on lattice-ordered double-framed soft semirings; and Park [43] discussed double-framed soft deductive system of subtraction algebras. Bordbar et al. [44] applied double-framed soft set theory to hyper- algebras. Saeed et al. [45] formulated the concepts of N-framed soft set and then defined the soft union and intersection of two double-framed soft sets. They also provided an example to elucidate an application of N-framed soft set.
The motivation for this work is to define new types of belong and nonbelong relations between ordinary points and double-framed soft sets which create new degrees of membership and nonmembership for the ordinary points. In fact, this leads to initiate novel concepts on double-framed soft topology, in particular in the areas of soft separation axioms and cover properties.
We organize the rest of this paper as follows. Section 2 recalls some operations between double-framed soft sets. In Section 3, we formulate four types of belong relations between ordinary points and double-framed soft sets called weakly partial belong, strongly partial belong, weakly total belong, and strongly total belong relations and formulate four types of nonbelong relations between ordinary points and double-framed soft sets called weakly partial nonbelong, strongly partial nonbelong, weakly total nonbelong, and strongly total nonbelong relations. Then, we examine their behaviours under the operations of soft intersection and union. Also, we study soft mappings with respect to the classes of double-framed soft sets and prob the relationships between ordinary points and their images and preimages. In Section 4, we propose a method of optimum choice based on double-framed soft sets. We provide an example to illustrate how this method can be applied to model some real-life problems. Finally, we summarize the main obtained results and present some future works in Section 5.
2. Preliminaries
In this part, we mention some definitions and results of double-framed soft sets.
In this article, the sets of parameters are denoted by ; the initial universal sets are denoted by ; and the power set of is denoted by .
Definition 1. (see [4]). A soft set over , denoted by , is a map from to . We call an initial universal set and a set of parameters.
Usually, we write as a set of ordered pairs:
Definition 2. (see [30]). Let be two mappings from to . A double-framed soft set over , determined by and , is the set .
We will denote this double-framed soft set by . The set is called the initial universal set, and the set is called the set of parameters.
A class of all double-framed soft sets defined over with all parameters subsets of is denoted by .
In a similar way, one define the concepts of triple-framed soft set, quadruple-framed soft set, quintuple-framed soft set, sextuple-framed soft set, septuple-framed soft set,…, and N-framed soft set.
Definition 3. (see [45]). is said to be an N-framed soft set over a nonempty set , where is a map from into for , is an initial universal set, and is a set of parameters.
An N-framed soft set is expressed as follows:Henceforth, we assume that the initial universal set of every double-framed soft set in this paper is nonempty.
Example 1. Let be the universal set of third graders and be a set of parameters, where represents the students holding first rank, represents the students holding second rank, represents the students holding third rank, and represents the students holding fourth rank.
Let be a map of ranking students in mathematics subject and be a map of ranking students in physics subject.
Suppose that and are given as follows:Now, we can describe this system using a double-framed soft set as follows:If there are three maps of subjects, a system is described using a triple-framed soft set; and if there are four maps of subjects, a system is described using a quadruple-framed soft set and so on.
Definition 4. (see [41]). Let be a double-framed soft set and . We say that if and for all and if or for some .
Definition 5. (see [39]). A double-framed soft set is said to be a null double-framed soft set (resp., an absolute double-framed soft set) if equals to the empty (resp., universal) set for each .
Henceforth, the null and absolute double-framed soft sets are symbolized by and , respectively.
Definition 6. (see [45]). The intersection of two double-framed soft sets and is a double-framed soft set such that and and are defined by and .
It is symbolized by .
Definition 7. (see [45]). The soft union of two double-framed soft sets and is a double-framed soft set , where and and are defined byIt is symbolized by .
Definition 8. (see [30]). A double-framed soft set is called a subset of a double-framed soft set , denoted by , if , and and holds true for all .
The double-framed soft sets and are called equal if and .
Definition 9. (see [39]). The relative complement of a double-framed soft set is a double-framed soft set , where and are two maps from to defined as follows:
Proposition 1. (see [39]). The operations of soft union and soft intersection of double-framed soft sets are commutative and associative.
Proposition 2. (see [39]). We have the following results for two double-framed soft sets:(i).(ii).
3. Belong and Nonbelong Relations on Double-Framed Soft Sets
We dedicate this section to establish four types of memberships and four types of nonmemberships between an ordinary point and double-framed soft set and lay the foundations of them. We obtain some results that concern the soft intersection and union operators, the product of double-framed soft sets and soft mappings.
Definition 10. Let be a double-framed soft set and . We say that(i), reading as weakly partial belongs to , if or for some .(ii), reading as strongly partial belongs to , if and for some .(iii), reading as weakly total belongs to , if or for all .(iv), reading as strongly total belongs to , if and for all .
Definition 11. Let be a double-framed soft set and . We say that(i), reading as weakly partial belong to , if or for some .(ii), reading as strongly partial belong to , if and for some .(iii), reading as does not weakly total belong to , if or for all .(iv), reading as does not strongly total belong to , if and for all .
Remark 1. The relations of strongly total belong and weakly partial nonbelong were introduced in [41] (see Definition 4).
Proposition 3. For a double-framed soft set and , we have the following results:(i) iff .(ii) iff .(iii) iff .(iv) iff .
Proof. We will just prove (i) and (iv).(i) or for some or for some .(ii) and for all and for all .The following proposition is a direct result of Definition 10.
Proposition 4. Let be a double-framed soft set and . Then,(i).(ii).(iii).(iv).Example below is given to clarify that the converse of Proposition 4 fails. Also, it shows that the relations of strongly partial belong and weakly total belong (the relations of weakly total nonbelong and strongly partial nonbelong) are independent of each other.
Example 2. Let be a set of parameters and double-framed soft set over be defined as follows:We find the next relations:(i), but and do not hold.(ii), but does not hold.(iii), but does not hold.(iv), but and do not hold.(v), but does not hold. Also, , but does not hold.(vi), but does not hold.
Remark 2. It is well-known in the Quantum physics the possibility of existence and nonexistence of an electron in the same place. This matter also occurs here with respect to weakly partial belong and weakly partial nonbelong relations; strongly partial belong and strongly partial nonbelong relations; and weakly total belong and weakly total nonbelong relations. To illustrate that it can be seen from Example 2 that
Proposition 5. Let and be double-framed soft sets such that . Then,(i)If (resp., , , ), then (resp., , , ).(ii)If (resp., , , ), then (resp., , , ).
Proof. Straightforward.
Remark 3. Note that satisfying the two conditions (i) and (ii) of the above proposition does not imply . To illustrate this fact, consider Example 2 and let . It is clear that (resp., , , ) if and only if (resp., , , ). However, and .
Proposition 6. For two double-framed soft sets and and , we have the following results:(i) or .(ii) or .(iii) or .(iv) or .(v) and .(vi) and .(vii) and .(viii) and .
Proof. Since and are subsets of , then the necessary parts of (i) to (iv) hold; and since are subsets of and , then the necessary parts of (v) to (viii) hold.
To prove the sufficient part of (i), let . Then, or for some . Say for some . Therefore, or for some , and hence, or .
To prove the sufficient part of (viii), let and . Then, for all , we have and and and . Therefore, and for all , and hence, .
Example below is given to clarify that the converse of the results (ii) to (iv) and (v) to (vii) of Proposition 6 fails.
Example 3. Let be a set of parameters and double-framed soft sets over defined as follows:Then, and .
We note the following:(i), but or does not hold.(ii), but or does not hold.(iii), but or does not hold.(iv) and , but does not hold.(v) and , but does not hold.(vi) and , but does not hold.Similarly, it can be proved the following result.
Proposition 7. For two double-framed soft sets and over and , we have the following results:(i) and .(ii) and .(iii) and .(iv) and .(v) or .(vi) or .(vii) or .(viii) or .
Definition 12. A double-framed soft set is said to be 2-stable if and for each . If , then is said to be 1-stable.
Obviously, a 1-stable double-framed soft set is 2-stable, but the converse is not always true.
Proposition 8. Let be a 1-stable double-framed soft set. Then, .
Proof. Since is a 1-stable double-framed soft set, there is a subset of such that for each . This means that or for some iff and for each . Hence, the desired result is proved.
Corollary 1. Let be a 1-stable double-framed soft set. Then, .
Proposition 9. Let be a 2-stable double-framed soft set. Then,(i).(ii).
Proof. Since is a 2-stable double-framed soft set, there exist two subsets of such that and for each . Now, we have the following two cases: Case 1: or for some if and only if or for all . Case 2: and for some if and only if and for all .Hence, the desired results are proved.
Corollary 2. Let be a 2-stable double-framed soft set. Then,(i).(ii).
Definition 14. The Cartesian product of two double-framed soft sets and , denoted by , is defined as and for each .
Proposition 10. (i) if and only if and .(ii)If , then and .(iii) if and only if and .(iv)If , then and .
Proof. (i) . and for some . and for some and and and for some and . and for some and and for some . and .The other cases can be achieved similarly.
The following example explains that the converses of (ii) and (iv) of the above proposition fail.
Example 4. Let be a set of parameters and double-framed soft sets over defined as follows:Then, .
We find the following relations:(i) and ; however, does not hold true.(ii) and ; however, does not hold true.
Definition 15. A soft mapping from into is a pair of crisp mappings such that and and is defined as follows: the image of a double-framed soft set in is a double-framed soft set in such that and and are two maps defined asfor each and .
Definition 16. A soft map is said to be injective (resp., surjective and bijective) if and are injective (resp., surjective and bijective).
Definition 17. Let be a soft mapping. Then, the preimage of a double-framed soft set in is a double-framed soft set in such that and and are two maps defined asfor each and .
Proposition 11. Let be a soft mapping, and let and be two double-framed soft sets in . Then,(i). The equality holds if is surjective.(ii). The equality holds if and are surjective.(iii)If , then .(iv).(v).The equality holds if and are injective.
Proof. To prove (i), let , where for each and . Then, for each . Therefore, . Since , then .
If is surjective, then . Hence, .
To prove (ii), let , where for each and . Then, for each . Therefore, .
If and are surjective, then and . Hence, .
One can prove (iii) easily.
To prove (iv), first, let , where . Now, for each , we have . SincethenSecond, let , where . Now, for each , we haveSince , then . Thus, for each . Hence, we obtain the desired result.
One can prove (v) similarly.
By using a similar technique, one can prove the following result.
Proposition 12. Let be a soft mapping and let and be two double-framed soft sets in . Then, we have the following results:(i).(ii).(iii)If , then .(iv).(v).
Proposition 13. Let be a soft mapping, and let be a double-framed soft set in . Then, we have the following results:(i)If , then .(ii)If , then .(iii)If, then.(iv)If , then .(v)If and is injective, then .(vi)If and is injective, then .(vii)If , then .(viii)If , then .
Proof. We only prove (i), (ii), (v), and (viii). The other cases can be made similarly.
To prove (i), let , then there exist parameters such that or . Without loss of generality, consider . Now, there is a parameter such that . Obviously, , so that it follows from Definition 15 that . Therefore, , as required.
To prove (ii), let . Then, there exist parameters such that and . Without loss of generality, suppose that there exist two distinct parameters such that and . Obviously, and so that it follows from Definition 15 that and . Therefore, , as required.
To prove (v), let . Then, there exist parameters such that or . Say . Then, there is a parameter such that . Since is injective, then . This means that . Therefore, . Therefore, , as required.
To prove (viii), let . Then, and for all . Therefore, for each parameter , there is such that . Thus, for each , we obtain and . Hence, , as required.
Proposition 14. Let be a soft mapping and let be a double-framed soft set in . If is surjective, then we have the following results:(i)If , then for each .(ii)If , then for each .(iii)If , then for each .(iv)If , then for each .(v)If such that is injective, then .(vi)If such that is injective, then .(vii)If such that is injective, then .(viii)If such that is injective, then .
Proof. We only prove (i), (ii), (v), and (viii). The other cases can be made similarly.
To prove (i), let . Then, there exist parameters such that or . Without loss of generality, consider . Since is surjective, then there is a parameter such that . It follows from Definition 17 that . Now, for each , we obtain , as required.
To prove (ii), let . Then, there exist parameters such that and . Since is surjective, then there are two parameters such that and . It follows from Definition 17 that and . Now, for each , we obtain , as required.
To prove (v), let . Then, there exist parameters such that or . Say . Since is surjective, then there exists a parameter such that . It follows from Definition 17 that . Since is injective, then , as required.
To prove (viii), let . Then, and for all . Since is surjective, then there exists a parameter such that . It follows from Definition 17 that and . Since is injective, then , as required.
Proposition 15. Let be a soft mapping and let and be two double-framed soft sets in and , respectively. Then, the following holds:(i)If is bijective, then .(ii).
Proof. We only prove (i).
It is clear that , where and for each . Since is bijective, then and
4. Application of Double-Framed Soft Sets
In this section, we present an application of optimal choices using the idea of double-framed soft sets. The idea of this application is based on the evaluation of rank of the applicants in the different disciplines under study, not on the total summation of marks obtained by the applicant. The philosophy of this method is based on comprehensive evaluation, in other words, confirming the ability of applicants of satisfying high levels for all testing criteria.
Now, we provide an example to demonstrate: how we make optimal choices? Then, we construct an algorithm of this method.
Example 5. Ministry of education advertises of five scholarships supported from the government for the students who finished secondary stage. The trade-off between applicants is based on the examinations of two subjects: maths and physics.
Twenty students applied to compete with each other to gain one of these scholarships. They carried out the examination of the two subjects. Then, we input subjects’ marks of all students in Table 1.
Now, we determine the ranks of the students for each subject. In fact, this step will depend on the content of the application or the desire of those in charge of work. Regarding our example, we put a set expressing ten levels of ranks: stands for the students with the first rank. stands for the students with the second rank. ⋮ stands for the students with the n-th rank.From Table 1, we complete Table 2 by constructing a double-framed soft set over , where the maps and from into the power set of are given by the set of students who rank are in maths subject and the set of students who rank are in physics subject.
Finally, we give each rank a standard score. Regarding our example, we consider the following standard score of each rank : Rank takes 10 standard scores of each subject. Rank takes 9 standard scores of each subject. ⋮ Rank takes 1 standard score of each subject.Any rank such that takes standard zero score of each subject.
For each map of a double-framed soft set and each student , we calculate the value of each pair of Table 3 by the following rule:We sum the standard scores of all subjects for each student and then decide the student’s rank depending on the summation of his/her standard scores.
Table 3 illustrates this step.
One can note from the above table that we can decide four wining students: is the first, and are the second, and is the third. However, the last wining student is chosen from the set . The method of choosing them can be done by ways such as interview, total marks, or random lottery.
In the following, we present an algorithm of determining the wining students.
On the contrary, if the subjects are not of equal significance, that is, Ministry of education imposes weights on the subjects, i.e., corresponding to each subject , there is a weight .
In this case, we modify the previous algorithm to be convenient for weighted selection.
With respect to our example (Algorithm 2), suppose that the weights and are, respectively, corresponding to maths and physics subjects. Then, we update Table 3 to be as follows.
Now, one can note from the above table that the five wining students are as follows: is the first, is the second, is the third, is the fourth, and is the fifth.
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5. Conclusions
In this article, we have initiated four types of belong relations and four types of nonbelong relations between an ordinary point and double-framed soft sets. These relations are primary indicator of the degree of membership and nonmembership of an element. Then, we have defined soft mappings between two classes of double-framed soft sets and determine the conditions under which an ordinary point and its image and preimage are preserved with respect to the different types of belong and nonbelong relations. In the end, we have exploited the idea of double-framed soft sets to investigate an educational application of choosing the best students in terms of their performance rank in all testing criteria. An algorithm of the application was explained with the aid of an illustrative example.
We draw attention to that the different types of belong and nonbelong relations classify the relationships between elements and double-framed soft sets into eight levels as well as classify the stability into two levels. One of the unique properties of these relations is the possibility of belonging and nonbelonging of the element to the same double-framed soft sets with respect to weakly partial belong and weakly partial nonbelong relations, strongly partial belong and strongly partial nonbelong relations, and weakly total belong and weakly total nonbelong relations. This matter leads to new relations between belonging and nonbelonging of the ordinary points and the soft intersection and union of double-framed soft sets.
As future works, we shall apply the relations presented in this work to formulate several types of soft separation axioms and compact spaces on double-framed soft topological spaces. To simplify and clarify this idea, we define four types of covers of a double-framed soft topological space using weakly partial belong, strongly partial belong, weakly total belong, and strongly total belong relations. In addition, we try to model some natural phenomena using the idea of N-framed soft set. It is worthy to note that one can extend this work by studying the belong and nonbelong relations introduced herein with respect to N-framed soft sets, where .
Data Availability
No data were used to support this study.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
Acknowledgments
This study did not receive any funding from any institution.