1. Introduction
For formal modeling, reasoning, and computing, most traditional tools are characterized by being crisp, deterministic, and precise. However, many complex problems exist in the domains of economics, engineering, the environment, social science, medical science, and so on. Therefore, traditional methods based on cases may not be suitable for solving or modeling these issues. Based on this, a set of theories has been proposed to tackle these problems. Molodtsov [
1] introduced a new concept, namely soft set. In [
1,
2], Molodtsov successfully applied the soft theory in several directions, such as smoothness of functions, game theory, operations research, Riemann integration, Perron integration, probability, theory of measurement, etc.
In 2013, Shabir and Naz [
3] explained that the bipolar soft set structure has clearer and more general results than the soft set structure. They came up with the fuzzy bipolar soft sets and bipolar fuzzy soft sets and established some algebraic structures of these two classes of bipolar soft sets. They presented an application of fuzzy bipolar soft sets in decision-making problems [
4]. Based on Dubois and Prada [
5], decision making is constructed on two sides, namely positive and negative. Bipolarity is significant for characterization between positive and negative information to differentiate between reasonable and unreasonable events. Shabir and Bakhtawar [
6] introduced the concept of bipolar soft topological spaces and studied some of their properties. Fadel and Dzul-Kifli [
7] defined the concept of bipolar soft topological spaces via bipolar soft sets and some properties. Öztürk [
8,
9] presented more properties and operations on bipolar soft sets, and the bipolar soft points are introduced.
Subsequently, a number of definitions, operations, and applications on bipolar soft sets and bipolar soft structures have been investigated. For instance, Dizman and Öztürk [
10] introduced fuzzy bipolar soft topological spaces via fuzzy bipolar soft sets. Abdullah et al. [
11] proposed a bipolar fuzzy soft set, which is a new idea of bipolar soft set and they introduced some basic operations and an application of bipolar fuzzy soft set into decision-making problems. They gave an algorithm to solve decision-making problems by using a bipolar fuzzy soft set. Al-Shami [
12] defined some ordinary points on bipolar soft sets and presented an application of optimal choices by applying the idea of bipolar soft sets. Karaaslan and Karataş [
13] redefined the concept of the bipolar soft set and bipolar soft set operations and presented a decision-making method with application. Karaaslana et al. [
14] defined normal bipolar soft subgroups. Mahmood [
15] defined a novel approach towards bipolar soft sets and discussed an application on decision-making problems. Wang et al. [
16], and Rehman and Mahmood [
17] combined some generalizations of fuzzy sets and bipolar soft sets. They investigated applications in decision-making problems. Hussain [
18] defined and discussed binary soft connected spaces in binary soft topological spaces. He proposed an application of a decision-making problem by using the approach of rough sets. Sathiyaseelan et al. [
19] presented symmetric matrices on inverse soft expert sets and investigated their applications.
Yet, studies conducted on the limit point concept were required by mathematicians to bring about more developments in mathematics. Musa and Asaad [
20] introduced the concept of the bipolar hypersoft set as a combination of a hypersoft set with a bipolarity setting and investigated some of its basic operations. They also discussed some topological notions in the frame of bipolar hypersoft setting [
21]. In 2022, Saleh et al. [
22,
23] studied bipolar soft generalized topological spaces and defined the basic notions of bipolar soft topological properties with the investigation of a number of their symmetric properties.
Correspondingly, in 2016, the concept of the binary soft set was first defined by Açıkgöz and Taş in [
24], where they introduced the binary soft set on two initial universal sets and proposed some of their properties. After that, Benchalli et al. [
25] presented some related basic properties, which are defined over two initial universal sets with suitable parameters, and they defined the binary soft topological spaces with some of their properties. Recently, in 2023, Naime and Orhan [
26] defined a new concept of bipolar soft sets over two universal sets and a parameter set, namely binary bipolar soft sets, which is an extension of bipolar soft sets and binary soft sets. They presented some operations on binary bipolar soft sets, such as complement, union, intersection, AND, and OR, and they investigated their basic properties.
The following sections in our work are organized in the following manner:
Section 2 provides the essential conceptual framework concerning symmetry categories of sets, including soft sets, bipolar soft sets, and binary soft sets, to familiarize the reader with the underlying principles. After that, in
Section 3, our main idea is to define the binary bipolar soft points using binary bipolar soft sets and some of their properties.
Section 4 introduces the binary bipolar soft topological spaces using binary bipolar soft sets, which is an extension of the bipolar soft topological spaces and binary soft topological spaces, accompanied by an exploration of the associated topological operators binary bipolar soft closure, binary bipolar soft interior and binary bipolar soft boundary. Some results and counterexamples are given to explain this work.
Section 5 serves as the concluding section of our presentation.
4. Topology on Binary Bipolar Soft Sets
In this section, we introduce the concept of binary bipolar soft topological spaces over two universal sets and a set of parameters. We investigate some topological structures of binary bipolar soft sets such as binary bipolar soft open, binary bipolar soft closed, binary bipolar soft closure, binary bipolar soft interior, and binary bipolar soft boundary.
Definition 25. Let be a collection of s over and , then is said to be a binary bipolar soft topology, denoted by , on and if
- Ax.1.
, .
- Ax.2.
The union of any member of s in belongs to .
- Ax.3.
The intersection of any two s in belongs to .
The quintuple is called a binary bipolar soft topological space () over and .
Example 2. Let and be two universe sets and be a set of parameters. Let , whereTherefore, is a over and . Example 3. Let and be two universe sets and be a set of parameters. Let , whereHence, is not a over and because . Definition 26. Let be a over and , then the members of are said to be open sets in and . The is said to be closed in and if its relative complement is belong to .
Definition 27. Let and be the two initial universe sets and Ψ be a set of parameters. If , , then is called the indiscrete space over and . If is the collection of all s, which can be defined over and , then is called the discrete space over and .
Proposition 5. Let be a over and . Then, the following properties hold:
- 1.
and are closed sets.
- 2.
The union of any two closed sets is closed.
- 3.
The arbitrary intersection of closed sets is closed.
Theorem 1. Let and be over and , then is a over and .
Proof. Let and be a over and
- Ax.1.
Clearly , .
- Ax.2.
Let be a family of s in , Then, and for each , so and . Thus, .
- Ax.3.
Let and be two s in . Then, , and , . Since and . Therefore, . Hence, is a over and .
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Remark 1. Let and be over and , then may not be over and in general.
Example 4. Let and be two universe sets and be a set of parameters. Let and , , where and , , are s over and defined asThen, and are over and . Now, , , , is not because , , , , . Theorem 2. Let be a over and , then is over and .
Proof. Suppose that is a over and . Then,
- Ax.1.
implies that , also implies that .
- Ax.2.
Let belong to . Since for all , then . Thus, .
- Ax.3.
Let , . Since , , . Therefore,
Hence, defines a over and . □
Theorem 3. Let be a over and , then is over and .
Proof. Similar to Theorem 2. □
Remark 2. The following example shows that the converse of Theorems 2 and 3 are not true.
Example 5. Let , and . Suppose thatare two defined on and , whereandThus, , , , , , where , and defined as follows:
Hence, ,, . Therefore, is not over and . However, the following theorem shows that the converse of Theorem 2 is true under some conditions.
Theorem 4. Let be a over and . Then, the collection consisting of s such that and for all defines a topology on and .
Proof. - Ax.1.
Since , , then and hence . Also, , thus .
- Ax.2.
Let . Then, and . Now, since is a topology, then . Let , thus . Therefore, .
- Ax.3.
Let , . Then, , and so . Now, since is a topology, . Let , hence . Therefore, . The proof is completed.
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Theorem 5. If is a over and , then and are over and , respectively.
Proof. Let be a over and and by Definition 4, we have , in with , then , in and , in . So, let and , where , then , from is a over and , thus . Therefore, and . Now, let , . Then, , thus and . Hence, and are over and , respectively. □
Definition 28. Let be a over and be a over universe sets and . Then, the closure of , denoted by -, is the intersection of all closed sets, which contains . Thus, - is the smallest closed set over and , which contains .
Theorem 6. Let be a over and , and be over universe sets and . Then
- 1.
- and - .
- 2.
- implies - is a closed set and contains .
- 3.
is a closed set if and only if =-.
- 4.
--=-.
- 5.
implies - -.
- 6.
- =- -.
- 7.
- - -.
Proof. Follows directly from Definitions 26 and 28.
Let
be a family of
closed sets containing
-
. Then, from Definition 28,
Since is a closed set for each , it implies that is also closed set by Proposition 5. Thus, - is a closed set by (i). Now, to prove that -, we have for each , , implying , using (i) to obtain - . Therefore, - contains . Hence, - is a closed set and contains .
Let be a closed set, to prove =-. Since a closed and from Part (2), -. Thus, is a closed set containing , and is the smallest closed set containing . Therefore, - is smaller than that is - . Conversely, if is closed, then -=.
Since - is a closed set, by Part (3), it implies that --=-.
Suppose , then - and -, Since - is a closed set containing . But, - is the smallest closed containing . Therefore, - is smaller than -. Hence, - -.
Since and .
Then, - - and
- - , by Part (5). Therefore,
- - - .
Also, from the closure property, we obtain - -. But, - is the smallest closed set containing . Thus, - is the smallest than - -. Hence, - =- -.
Since and , by Part (5) - - and - -. Hence, - - -.
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Remark 3. The next example shows that the equality of Part (7) in Theorem 6 does not hold in general.
Example 6. Let be defined as in Example 2. If and are two defined asThus, -=-=, while - , . Hence, - - - Definition 29. Let be a of a , , over and . Then, we associate pointwise the closure of over and is denoted by - and defined as - -, where - is the closure of in , , for each .
Theorem 7. Let be a over and , be a over universe sets on and , then - -
Proof. For any parameter , - is the smallest closed set in , which contains . Then, if - , is a closed set in containing . This implies that - - . Therefore, -, -. □
Theorem 8. Let be a and be a over and , then - -.
Proof. Let be a over and , if - -, then - is a closed set, thus - . Conversely, if - , then - is a closed set containing . By Theorem 7, and from the definition of closure of , any closed set, which contains will contains -. Thus, - -. Hence, -=-. □
Definition 30. Let be a over and . Let , , the is said to be binary bipolar soft neighborhood set of , denoted by the neighborhood of if there exists a open set such that That is ∈ ⊆ and ∈ ⊆ , for each and .
Theorem 9. Let be a over and . Then
- 1.
Each has a neighborhood set.
- 2.
The intersection of two neighborhood sets of is a neighborhood.
- 3.
Every superset of a neighborhood set of is a neighborhood of .
Proof. Clearly from .
Let , if and are neighborhood sets of . Then, there exist two open sets , such that and . Since . Therefore, . Hence, is a neighborhood of .
Let and . Since is neighborhood of , then with . Therefore, . Hence, is a neighborhood of .
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Definition 31. Let be a over and . A is said to be binary bipolar soft interior point of , denoted by the interior point if there exists a open set such that for each and .
The interior set of , denoted by -, is the union of all open sets contained in .
Theorem 10. Let be a over and , and be . Then, the following properties hold:
- 1.
- is a open set contained in .
- 2.
- is the largest open set over and , which contained in .
- 3.
is open if and only if -.
Proof. Obvious from Definition 31.
From Part (1) and Definition 31.
Suppose that is open. Then, is a open set contained in but from Part (2), - is the largest open set contained in . Therefore, -. Conversely, if -, then is a open set from Part (1).
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Theorem 11. Let be a over and , and and be . Then, the following properties hold:
- 1.
- and -
- 2.
--=-.
- 3.
implies - -.
- 4.
- =- -.
- 5.
- - - .
Proof. Obvious.
Since - is a open set. Then, by Theorem 10 (3), --=-.
Suppose , then - , thus - and from - is the largest open contained in . Hence, - -.
Since and . From (3), - - and - -. Implies - - -. Also, from - and - , then - - , which implies
- - is a open set contained in . But - - is the largest open set contained in . Therefore, - - - . Hence, - =- -.
Since and . Then, by (3), - - and - - . Hence, - - - .
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Remark 4. The following example shows the equality of Theorem 11 (5) does not hold in general.
Example 7. Let be defined as in Example 2. If and are defined asTherefore, -=-=, while - , . Hence, - -, - . Theorem 12. Let be a and be a over and . Then
- 1.
-=-.
- 2.
-=-.
Proof. Let
,
,
, then
Similar to Part (1).
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Definition 32. Let be a over and . A binary bipolar soft boundary set of , denoted by boundary and defined as -=- -.
Remark 5. Let be a over and . For any , we have
- 1.
-=-.
- 2.
- -.
Theorem 13. Let be a over and . For any , we have
- 1.
-=- -.
- 2.
- -.
Proof. We start the proof by using Definition 32
By using Remark 5, we have
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Remark 6. Let be a over and . Then, in general
- 1.
-≠ -.
- 2.
≠- - -.
Example 8. Let and be two universe sets and be a set of parameters. Let , whereIf we take a asThen, - and - , so - and - , then - . Therefore, - = -. Also, ≠ , , , - - -. Theorem 14. Let be a over and . If is a open set, then and - are disjoint .
Proof. Suppose that is a open set. By Theorem 13 (2), - - and - . Therefore, -. Hence, and - are disjoint . □
Theorem 15. Let be a over and . If is a closed set, then - .
Proof. Suppose that is a closed set. Then, - - and - . Therefore, - . □
Theorem 16. Let be a over and , and is a . If is both a open and closed set, then - .
Proof. Suppose that is a open set. By Theorem 14, and - are disjoint . So, - . Now, is a closed set. By Theorem 14, - . Therefore, -=-. Hence, - . □
Remark 7. The converse of Theorems 14–16 in general is not hold.
Example 9. Consider and in Example 8. Clearly, - and are disjoint , but is not open.
If we take , then - but is not closed.
Again, if we take , then - , but is neither closed nor open.
Theorem 17. Let be a over and , and be a . Then,
- 1.
- - .
- 2.
- - .
Proof. We start the proof by using Definition 32
Similar to Part (1).
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