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Article

Makgeolli Structures and Its Application in BCK/BCI-Algebras

1
Department of Mathematics Education, Dongguk University, Seoul 04620, Korea
2
Department of Mathematics, Jeju National University, Jeju 63243, Korea
3
Department of Mathematics Education, Gyeongsang National University, Jinju 52828, Korea
4
Research Institute for Natural Science, Department of Mathematics, Hanyang University, Seoul 04763, Korea
*
Author to whom correspondence should be addressed.
Mathematics 2019, 7(9), 784; https://doi.org/10.3390/math7090784
Submission received: 5 August 2019 / Revised: 20 August 2019 / Accepted: 22 August 2019 / Published: 25 August 2019
(This article belongs to the Special Issue Algebra and Discrete Mathematics)

Abstract

:
A fuzzy set is an extension of an existing set using fuzzy logic. Soft set theory is a generalization of fuzzy set theory. Fuzzy and soft set theory are good mathematical tools for dealing with uncertainty in a parametric manner. The aim of this article is to introduce the concept of makgeolli structures using fuzzy and soft set theory and to apply it to BCK/BCI-algebras. The notion of makgeolli algebra and makgeolli ideal in BCK/BCI-algebras is defined, and several properties are investigated. It deals with the relationship between makgeolli algebra and makgeolli ideal, and several examples are given. Characterization of makgeolli algebra and makgeolli ideal are discussed, and a new makgeolli algebra from old one is established. A condition for makgeolli algebra to be makgeolli ideal in BCK-soft universe is considered, and we give example to show that makgeolli ideal is not makgeolli algebra in BCI-soft universe. Conditions for makgeolli ideal to be makgeolli algebra in BCI-soft universe are provided.

1. Introduction

There are many things inherently uncertain, inaccurate, and ambiguous in the real world. Zadeh [1] pointed out: “Various problems in system identification involve characteristics which are essentially nonprobabilistic in nature,” and he introduced fuzzy set theory as an alternative to probability theory (see the work by the authors of [2]). Zadeh [3] outlined the uncertainty, which is an attribute of information, by trying to address it more generally. It is difficult to deal with uncertainties by traditional mathematical tools. However, one can use a wider range of existing theories, such as theory of (intuitionistic) fuzzy sets, theory of interval mathematics, theory of vague sets, probability theory, and theory of rough sets for dealing with uncertainties. However, Molodtsov [4] pointed out all of these theories have their own difficulties. According to Maji et al. [5] and Molodtsov [4], these difficulties can be attributed to the inadequacy of the parametric tools of theory. Molodtsov [4] tried to overcome these difficulties. He introduced the concept of soft set as a new mathematical tool for dealing with uncertainties, and pointed out several directions for its applications. Globally, interest in soft set theory and its application has been growing rapidly in recent years. Soft set theory has been applied to decision making problem (see works by the authors of [5,6,7,8,9,10,11,12]), groups, rings, fields and modules (see works by the authors of [13,14,15,16,17]), BCK/BCI-algebras, etc. (see works by the authors of [18,19,20,21,22,23,24,25,26,27]).
In this paper, we introduce the notion of makgeolli structures using fuzzy and soft set theory and apply it to BCK/BCI-algebras. We define the concept of makgeolli algebra and makgeolli ideal in BCK/BCI-algebras, and investigate several properties. We deal with the relation between makgeolli algebra and makgeolli ideal, and consider several examples. We discuss characterization of makgeolli algebra and makgeolli ideal. We make a new makgeolli algebra from old one. We provide a condition for makgeolli algebra to be makgeolli ideal in BCK-soft universe. We give example to show that makgeolli ideal is not makgeolli algebra in BCI-soft universe, and provide conditions for makgeolli ideal to be makgeolli algebra in BCI-soft universe.

2. Preliminaries

In 1978 and 1980, K. Iséki [28,29] introduced a BCK/BCI-algebra, which is an important class of logical algebras.
By a BCI-algebra, we mean a set X with a a binary operation ∗ and special element 0 which satisfies the following conditions.
(I)
( u , v , w X ) ( ( ( u v ) ( u w ) ) ( w v ) = 0 ) ,
(II)
( u , v X ) ( ( u ( u v ) ) v = 0 ) ,
(III)
( u X ) ( u u = 0 ) ,
(IV)
( u , v X ) ( u v = 0 , v u = 0 u = v ) .
If a BCI-algebra X satisfies the following identity,
(V)
( u X ) ( 0 u = 0 ) ,
then X is called a BCK-algebra. Any BCK/BCI-algebra X satisfies the following conditions.
( u X ) u 0 = u ,
( u , v , w X ) u v u w v w , w v w u ,
( u , v , w X ) ( u v ) w = ( u w ) v
where u v if, and only if, u v = 0 . A subset S of a BCK/BCI-algebra X is called a subalgebra of X if u v S for all u , v S . A subset I of a BCK/BCI-algebra X is called an ideal of X if it satisfies
0 I ,
( u X ) v I u v I u I .
We refer the reader to the books by the authors of [30,31] for further information regarding BCK/BCI-algebras.
Let U be a universal set and E a set of parameters, respectively. A pair ( α , E ) is called a soft set over a universe U (see [4]) where α is a mapping given by
α : E P ( U ) .
In other words, a soft set over U is a parameterized family of subsets of the universe U . For ε A , α ( ε ) may be considered as the set of ε -approximate elements of the soft set ( α , A ) . Clearly, a soft set is not a set. For illustration, Molodtsov considered several examples in the work by the authors of [4].
Given a nonempty subset A of E, denote by ( α , A ) a soft set ( α , E ) over U satisfying the following condition.
α ( x ) = for all x A .

3. Makgeolli Structures

In what follows, let E be a set of parameters and U a universal set unless otherwise specified. We say that the pair ( U , E ) is a soft universe.
Definition 1.
Let A and B be subsets of E. A makgeolli structure on U (related to A and B) is a structure of the form
M ( A , B , U ) : = { ( a , b , x ) ; M A ( a ) , G B ( b ) , ( x ) ( a , b , x ) A × B × U }
where M A : = ( M , A ) and G B : = ( G , B ) are soft sets over U and ℓ is a fuzzy set in U.
For the sake of simplicity, the makgeolli structure in (7) will be denoted by M ( A , B , U ) = ( M A , G B , ) . The makgeolli structure M ( A , A , U ) = ( M A , G A , ) on U related to a subset A of E is simply denoted by M ( A , U ) = ( M A , G A , ) .
Example 1.
Miss K (say) and Mr. J (say) are going to buy a house to live in after marriage. They are looking for the most reasonable house, considering its price, environment, and distance from the neighborhood (for example, hospital). There are six houses U = { h i i = 1 , 2 , 3 , 4 , 5 , 6 } . They are considering two parameter sets A = { ε 1 , ε 2 , ε 3 } and B = { δ 1 , δ 2 , δ 3 } where each parameter ε i and δ i , i = 1 , 2 , 3 , stands for
ε 1 : expensive , ε 2 : intermediate price , ε 3 : cheap , δ 1 : beautiful , δ 2 : green surround , δ 3 : pristine area ,
and consider the distance from the neighborhood given by
: U [ 0 , 1 ] , x 0.4 if x = h 1 , 0.7 if x = h 2 , 0.6 if x = h 3 , 0.2 if x = h 4 , 0.5 if x = h 5 , 0.1 if x = h 6 .
Here, for example, ( h 1 ) = 0.4 means that the distance from house to the neighborhood is 4 km. Suppose that M A ( ε 1 ) = { h 1 , h 2 } , M A ( ε 2 ) = { h 2 , h 3 , h 4 } , M A ( ε 3 ) = { h 1 , h 4 , h 6 } , G B ( δ 1 ) = { h 2 , h 4 , h 6 } , G B ( δ 2 ) = { h 3 , h 4 , h 5 } and G B ( δ 3 ) = { h 3 , h 4 , h 5 , h 6 } Then the makgeolli structure M ( A , B , U ) = ( M A , G B , ) on U is given by Table 1.
The Gothic component ( 1 , 1 , 0.2 ) in Table 1 means that the house h 4 is intermediate price, beautiful, and it is 2 km away from the neighborhood (for example, hospital).
Definition 2.
Let ( U , E ) be a soft universe and let M ( A , B , U ) = ( M A , G B , ) and N ( A , B , U ) = ( N A , H B , ȷ ) be makgeolli structures on U. The intersection of M ( A , B , U ) and N ( A , B , U ) is defined to be a makgeolli structure ( M N ) ( A , B , U ) = ( M A ˜ N A , G B ˜ H B , ȷ ) on U in which
M A ˜ N A : A P ( U ) , a M A ( a ) N A ( a ) , G B ˜ H B : B P ( U ) , b G B ( b ) H B ( b ) , ȷ : U [ 0 , 1 ] , x min { ( x ) , ȷ ( x ) } .

4. Applications in BCK/BCI-Algebras

A BCK/BCI-soft universe is defined as a soft universe ( U , E ) in which U and E are BCK/BCI-algebras with binary operations “∗” and “ ”, respectively.
Definition 3.
Let ( U , E ) be a BCK/BCI-soft universe and let A and B be subsets of E. A makgeolli structure M ( A , B , U ) =   ( M A , G B , ) on U is called a makgeolli algebra over U if it satisfies:
( a 1 , a 2 A ) a 1 a 2 A M A ( a 1 a 2 ) M A ( a 1 ) M A ( a 2 ) , ( b 1 , b 2 B ) b 1 b 2 B G B ( b 1 b 2 ) G B ( b 1 ) G B ( b 2 ) , ( x , y U ) ( t , r ( 0 , 1 ] ) x t , y r x y min { t , r }
where x t means ( x ) t .
Example 2.
Assume that there are five houses in the universal set U, which is given by
U = { h i i = 0 , 1 , 2 , 3 , 4 } .
Then ( U , , h 0 ) is a BCK-algebra in which the operation is given by Table 2.
Let E = { ε 0 , ε 1 , ε 2 , ε 3 } be a set of parameters in which each element ε i , i = 0 , 1 , 2 , 3 , stands for
ε 0 : beautiful , ε 1 : in good location , ε 2 : cheap , ε 3 : pristine area .
If we give a binary operation to E by Table 3,
Then ( E , , ε 0 ) is a BCK-algebra. If we take two sets, A = { ε 0 , ε 2 , ε 3 } and B = { ε 0 , ε 3 } of E, then A and B are subalgebras of E. Let M ( A , B , U ) =   ( M A , G B , ) be a makgeolli structure on U given as follows:
M A : A P ( U ) , x { h i i = 0 , 1 , 2 , 3 , 4 } if x = ε 0 , { h i i = 0 , 2 , 3 } if x = ε 2 , { h i i = 1 , 2 , 4 } if x = ε 3 , G B : B P ( U ) , x { h 3 } if x = ε 0 , { h 3 , h 4 } if x = ε 3 , : U [ 0 , 1 ] , x 0.8 if x = h 0 , 0.5 if x = h 1 , 0.5 if x = h 2 , 0.6 if x = h 3 , 0.3 if x = h 4 .
It is routine to check that M ( A , B , U ) =   ( M A , G B , ) is a makgeolli algebra over U.
Proposition 1.
Let ( U , E ) be a BCK/BCI-soft universe. For any subalgebras A and B of E, every makgeolli algebra M ( A , B , U ) =   ( M A , G B , ) over U satisfies the following conditions.
( ( a , b , x ) A × B × U ) M A ( a ) M A ( 0 ) , G B ( b ) G B ( 0 ) , 0 ( x ) .
Proof. 
If we take a 1 = a 2 = a and b 1 = b 2 = b in (8), then a a = 0 A and b b = 0 B . Hence
M A ( 0 ) = M A ( a a ) M A ( a ) M A ( a ) = M A ( a ) , G B ( 0 ) = G B ( b b ) G B ( b ) G B ( b ) = G B ( b ) .
Since x ( x ) for all x U , we have 0 ( x ) = x x min { ( x ) , ( x ) } for all x U . □
Theorem 1.
Let ( U , E ) be a BCK/BCI-soft universe and let A and B be subsets of E. Then a makgeolli structure M ( A , B , U ) =   ( M A , G B , ) on U is an makgeolli algebra over U if and only if the following assertions are valid.
( a 1 , a 2 A ) a 1 a 2 A M A ( a 1 a 2 ) M A ( a 1 ) M A ( a 2 ) , ( b 1 , b 2 B ) b 1 b 2 B G B ( b 1 b 2 ) G B ( b 1 ) G B ( b 2 ) , ( x , y U ) ( x y ) min { ( x ) , ( y ) } .
Proof. 
Assume that
x t , y r x y min { t , r }
for all x , y U and t , r ( 0 , 1 ] . Since x ( x ) and y ( y ) for all x , y U , it follows from (11) that x y min { ( x ) , ( y ) } . Thus ( x y ) min { ( x ) , ( y ) } .
Conversely, let x , y U and t , r ( 0 , 1 ] be such that x t and y r . Then ( x ) t and ( y ) r . Hence ( x y ) min { ( x ) , ( y ) } min { t , r } , and so x y min { t , r } . This completes the proof. □
Proposition 2.
Let ( U , E ) be a BCK/BCI-soft universe. For any makgeolli algebra M ( A , B , U ) =   ( M A , G B , ) over U related to subalgebras A and B of E, the following are equivalent.
(1)
( a A ) M A ( a ) = M A ( 0 ) , ( b B ) G B ( b ) = G B ( 0 ) , ( x U ) ( x ) = ( 0 ) .
(2)
( a 1 , a 2 A ) M A ( a 2 ) M A ( a 1 a 2 ) , ( b 1 , b 2 B ) G B ( b 2 ) G B ( b 1 b 2 ) , ( x , y U ) ( x y ) ( y ) .
Proof. 
Suppose that (1) is true. Using (10), we have
( a 1 , a 2 A ) M A ( a 2 ) = M A ( 0 ) M A ( a 2 ) = M A ( a 1 ) M A ( a 2 ) M A ( a 1 a 2 ) , ( b 1 , b 2 B ) G B ( b 2 ) = G B ( 0 ) G B ( b 2 ) = G B ( b 1 ) G B ( b 2 ) G B ( b 1 b 2 ) , ( x , y U ) ( y ) = min { ( 0 ) , ( y ) } = min { ( x ) , ( y ) } ( x y ) .
Assume that (2) is valid. Since a 0 = a for all a E , we have M A ( 0 ) M A ( a 0 ) = M A ( a ) for all a A and G B ( 0 ) G B ( b 0 ) = G B ( b ) for all b B . Since x 0 = x for all x U , we have ( 0 ) ( x 0 ) = ( x ) for all x U . It follows from (9) that we have (1). □
Proposition 3.
Let ( U , E ) be a BCI-soft universe. Then every makgeolli algebra M ( A , B , U ) =   ( M A , G B , ) over U related to subalgebras A and B of E satisfies the following conditions.
( a 1 , a 2 A ) M A ( a 1 ( 0 a 2 ) ) M A ( a 1 ) M A ( a 2 ) , ( b 1 , b 2 B ) G B ( b 1 ( 0 b 2 ) ) G B ( b 1 ) G B ( b 2 ) , ( x , y U ) ( x ( 0 y ) ) min { ( x ) , ( y ) } .
Proof. 
Using Proposition 1, we have
M A ( a 1 ( 0 a 2 ) ) M A ( a 1 ) M A ( 0 a 2 ) M A ( a 1 ) M A ( 0 ) M A ( a 2 ) = M A ( a 1 ) M A ( a 2 ) ,
G B ( b 1 ( 0 b 2 ) ) G B ( b 1 ) G B ( 0 b 2 ) G B ( b 1 ) G B ( 0 ) G B ( b 2 ) = G B ( b 1 ) G B ( b 2 ) ,
( x ( 0 y ) ) min { ( x ) , ( 0 y ) } min { ( x ) , min { ( 0 ) , ( y ) } } = min { ( x ) , ( y ) }
for all a 1 , a 2 A , b 1 , b 2 B and x , y U . □
Theorem 2.
Let ( U , E ) be a BCK/BCI-soft universe and let M ( A , B , U ) = ( M A , G B , ) and N ( A , B , U ) = ( N A , H B , ȷ ) be makgeolli algebras over U related to subalgebras A and B of E. Then the intersection of M ( A , B , U ) and N ( A , B , U ) is a makgeolli algebra over U.
Proof. 
For any a 1 , a 2 A , b 1 , b 2 B and x , y U , we have
( M A ˜ N A ) ( a 1 a 2 ) = M A ( a 1 a 2 ) N A ( a 1 a 2 ) ( M A ( a 1 ) M A ( a 2 ) ) ( N A ( a 1 ) N A ( a 2 ) ) = ( M A ( a 1 ) N A ( a 1 ) ) ( M A ( a 2 ) N A ( a 2 ) ) = ( M A ˜ N A ) ( a 1 ) ( M A ˜ N A ) ( a 2 ) ,
( G B ˜ H B ) ( b 1 b 2 ) = G B ( b 1 b 2 ) H B ( b 1 b 2 ) ( G B ( b 1 ) G B ( b 2 ) ) ( H B ( b 1 ) H B ( b 2 ) ) = ( G B ( b 1 ) H B ( b 1 ) ) ( G B ( b 2 ) H B ( b 2 ) ) = ( G B ˜ H B ) ( b 1 ) ( G B ˜ H B ) ( b 2 ) ,
( ȷ ) ( x y ) = min { ( x y ) , ȷ ( x y ) } min { min { ( x ) , ( y ) } , min { ȷ ( x ) , ȷ ( y ) } } min { min { ( x ) , ȷ ( x ) } , min { ( y ) , ȷ ( y ) } } min { ( ȷ ) ( x ) , ( ȷ ) ( y ) } .
Therefore ( M N ) ( A , B , U ) = ( M A ˜ N A , G B ˜ H B , ȷ ) is a makgeolli algebra over U. □
Let ( U , E ) be a BCK/BCI-soft universe. Gin a makgeolli structure M ( A , B , U ) = ( M A , G B , ) on U related to A and B, consider the following sets.
E A ( M A ; α ) = { a A M A ( a ) α } , E B ( G B ; β ) = { b B G B ( b ) β } , U ( ; t ) = { x U ( x ) t }
where α and β are subsets of U and t [ 0 , 1 ] .
Theorem 3.
Let ( U , E ) be a BCK/BCI-soft universe. Then a makgeolli structure M ( A , B , U ) = ( M A , G B , ) on U related to subalgebras A and B of E is a makgeolli algebra over U if and only if the nonempty sets E A ( M A ; α ) and E B ( G B ; β ) are subalgebras of E, and the nonempty set U ( ; t ) is a subalgebra of U for all α , β P ( U ) and t [ 0 , 1 ] .
Proof. 
Suppose that M ( A , B , U ) = ( M A , G B , ) is a makgeolli algebra over U. Let a 1 , a 2 E A ( M A ; α ) , b 1 , b 2 E B ( G B ; β ) and x , y U ( ; t ) for all α , β P ( U ) and t [ 0 , 1 ] . Then M A ( a 1 ) α , M A ( a 2 ) α , G B ( b 1 ) β , G B ( b 2 ) β , ( x ) t and ( y ) t . It follows from (10) that
M A ( a 1 a 2 ) M A ( a 1 ) M A ( a 2 ) α , G B ( b 1 b 2 ) G B ( b 1 ) G B ( b 2 ) β , ( x y ) min { ( x ) , ( y ) } t .
Hence a 1 a 2 E A ( M A ; α ) , b 1 b 2 E B ( G B ; β ) and x y U ( ; t ) . Therefore, E A ( M A ; α ) , E B ( G B ; β ) and U ( ; t ) are subalgebras of U.
Conversely, let M ( A , B , U ) = ( M A , G B , ) be a makgeolli structure on U such that the nonempty sets E A ( M A ; α ) and E B ( G B ; β ) are subalgebras of E, and the nonempty set U ( ; t ) is a subalgebra of U for all α , β P ( U ) and t [ 0 , 1 ] . Let a 1 , a 2 A , b 1 , b 2 B and x , y U be such that M A ( a 1 ) = α a 1 , M A ( a 2 ) = α a 2 , G B ( b 1 ) = β b 1 , G B ( b 2 ) = β b 2 , ( x ) = t x and ( y ) = t y . Taking α = α a 1 α a 2 , β = β b 1 β b 2 and t = min { t x , t y } imply that a 1 , a 2 E A ( M A ; α ) , b 1 , b 2 E B ( G B ; β ) and x , y U ( ; t ) . Thus a 1 a 2 E A ( M A ; α ) , b 1 b 2 E B ( G B ; β ) , and x y U ( ; t ) , which imply that
M A ( a 1 a 2 ) α = α a 1 α a 2 = M A ( a 1 ) M A ( a 2 ) , G B ( b 1 b 2 ) β = β b 1 β b 2 = G B ( b 1 ) G B ( b 2 ) , ( x y ) t = min { t x , t y } = min { ( x ) , ( y ) } .
Therefore M ( A , B , U ) = ( M A , G B , ) is a makgeolli algebra over U by Theorem 1. □
Let ( U , E ) be a soft universe. Given a makgeolli structure M ( A , B , U ) = ( M A , G B , ) on U related to subsets A and B of E, let M ( A , B , U ) = ( M A , G B , ) be a makgeolli structure related to A and B where
M A : A P ( U ) , x M A ( x ) if x E A ( M A ; α ) , η otherwise , G B : B P ( U ) , x G B ( x ) if x E B ( G B ; β ) , ρ otherwise : U [ 0 , 1 ] , x ( x ) if x U ( ; t ) , k otherwise
where α , β , η , ρ P ( U ) and t , k [ 0 , 1 ] with η M A ( x ) , ρ G B ( x ) and k < ( x ) .
Theorem 4.
Let ( U , E ) be a BCK/BCI-soft universe. If a makgeolli structure M ( A , B , U ) = ( M A , G B , ) on U related to subalgebras A and B of E is a makgeolli algebra over U, then so is M ( A , B , U ) = ( M A , G B , ) .
Proof. 
Assume that M ( A , B , U ) = ( M A , G B , ) is a makgeolli algebra over U. Then the nonempty sets E A ( M A ; α ) and E B ( G B ; β ) are subalgebras of E, and the nonempty set U ( ; t ) is a subalgebra of U for all α , β P ( U ) and t [ 0 , 1 ] by Theorem 3. Let a 1 , a 2 A . If a 1 , a 2 E A ( M A ; α ) , then a 1 a 2 E A ( M A ; α ) , and so
M A ( a 1 a 2 ) = M A ( a 1 a 2 ) M A ( a 1 ) M A ( a 2 ) = M A ( a 1 ) M A ( a 2 ) .
If a 1 E A ( M A ; α ) or a 2 E A ( M A ; α ) , then M A ( a 1 ) = η or M A ( a 2 ) = η . Hence M A ( a 1 a 2 ) η = M A ( a 1 ) M A ( a 2 ) . Let b 1 , b 2 B . If b 1 , b 2 E B ( G B ; β ) , then b 1 b 2 E B ( G B ; β ) , which implies that
G B ( b 1 b 2 ) = G B ( b 1 b 2 ) G B ( b 1 ) G B ( b 2 ) = G B ( b 1 ) G B ( b 2 ) .
If b 1 E B ( G B ; β ) or b 2 E B ( G B ; β ) , then G B ( b 1 ) = ρ or G B ( b 2 ) = ρ . Hence G B ( b 1 b 2 ) ρ = G B ( b 1 ) G B ( b 2 ) . Let x , y U . If x , y U ( ; t ) , then x y U ( ; t ) , and so ( x y ) = ( x y ) min { ( x ) , ( y ) } = min { ( x ) , ( y ) } . If x U ( ; t ) of y U ( ; t ) , then ( x ) = k or ( y ) = k . Hence ( x y ) k = min { ( x ) , ( y ) } . Therefore M ( A , B , U ) = ( M A , G B , ) is a makgeolli algebra over U. □
The following example shows that the converse of Theorem 4 is not true in general.
Example 3.
Consider a soft universe ( U , E ) in which U = Z 10 = { a ¯ a = 0 , 1 , 2 , , 9 } and E = { ε 0 , ε 1 , ε 2 , ε 3 } . Define a binary operations “∗” on U by
a ¯ b ¯ = a b + 10 ¯
for all a ¯ , b ¯ U . Then ( U , , 0 ¯ ) is a BCI-algebra. Let be a binary operation on E defined by Table 4.
Then ( E , , ε 0 ) is a BCI-algebra. Let M ( E , U ) =   ( M E , G E , ) be a makgeolli structure on U defined by
M E : E P ( U ) , x U if x = ε 0 , { 0 ¯ , 2 ¯ , 4 ¯ , 6 ¯ , 8 ¯ } if x = ε 1 , { 2 ¯ , 5 ¯ , 6 ¯ , 8 ¯ } if x = ε 2 , { 4 ¯ } if x = ε 3 , G E : E P ( U ) , x { 0 ¯ } if x = ε 0 , { 0 ¯ , 5 ¯ } if x = ε 1 , { 0 ¯ , 4 ¯ , 6 ¯ , 8 ¯ } if x = ε 2 , U if x = ε 3 , : U [ 0 , 1 ] , x 0.9 if x = 0 ¯ , 0.7 if x { 2 ¯ , 4 ¯ , 6 ¯ , 8 ¯ } , 0.6 if x { 1 ¯ , 3 ¯ } , 0.4 if x { 5 ¯ , 7 ¯ } , 0.3 if x = 9 ¯ .
Then E E ( M E ; γ ) = { ε 0 , ε 1 } = E E ( G E ; η ) and U ( ; r ) = { 0 ¯ , 2 ¯ , 4 ¯ , 6 ¯ , 8 ¯ } for γ = { 0 ¯ , 6 ¯ , 8 ¯ } , η = { 0 ¯ , 5 ¯ , 6 ¯ } and r ( 0.6 , 0.7 ] . Let M ( E , U ) = ( M E , G E , ) be a makgeolli structure on U given as follows.
M E : E P ( U ) , x M E ( x ) if x E E ( M E ; γ ) , otherwise , G E : E P ( U ) , x G E ( x ) if x E E ( G E ; η ) , U otherwise , : U [ 0 , 1 ] , x ( x ) if x U ( ; r ) , 0 otherwise ,
that is,
M E : E P ( U ) , x U if x = ε 0 , { 0 ¯ , 2 ¯ , 4 ¯ , 6 ¯ , 8 ¯ } if x = ε 1 , if x { ε 2 , ε 3 } , G E : E P ( U ) , x { 0 ¯ } if x = ε 0 , { 0 ¯ , 5 ¯ } if x = ε 1 , U if x { ε 2 , ε 3 } , : U [ 0 , 1 ] , x 0.9 if x = 0 ¯ , 0.7 if x { 2 ¯ , 4 ¯ , 6 ¯ , 8 ¯ } , 0 otherwise ,
It is routine to verify that M ( E , U ) = ( M E , G E , ) is a makgeolli algebra over U. But M ( E , U ) =   ( M E , G E , ) is not a makgeolli algebra over U since
M E ( ε 1 ) M E ( ε 2 ) = { 2 ¯ , 6 ¯ , 8 ¯ } { 2 ¯ } = M E ( ε 3 ) = M E ( ε 1 ε 2 ) ,
G E ( ε 1 ) G E ( ε 2 ) = { 0 ¯ , 4 ¯ , 5 ¯ , 6 ¯ , 8 ¯ } U = G E ( ε 3 ) = G E ( ε 1 ε 2 ) ,
and/or
( 1 ¯ 2 ¯ ) = ( 9 ¯ ) = 0.3 < 0.6 = min { ( 1 ¯ ) , ( 2 ¯ ) } .
Definition 4.
Let ( U , E ) be a BCK/BCI-soft universe. A makgeolli structure M ( E , U ) =   ( M E , G E , ) on U is called a makgeolli ideal over U if it satisfies
( e E ) ( M E ( 0 ) M E ( e ) , G E ( 0 ) G E ( e ) ) ,
( x U ) 0 ( x ) ,
( a , b E ) M E ( a ) M E ( a b ) M E ( b ) G E ( a ) G E ( a b ) G E ( b ) .
( x , y U ) ( t , r ( 0 , 1 ] ) x y t , y r x min { t , r } .
Example 4.
There are five woman patients in a hospital which is given by
U = { w 1 , w 2 , w 3 , w 4 , w 5 } .
Communication between two patients w i and w j for i , j { 1 , 2 , 3 , 4 , 5 } in the hospital is expressed as w i w j and the result is w k , i.e., w i w j = w k for k = 1 , 2 , 3 , 4 , 5 ; this is what w i informs w j that the health condition of w k is serious. In this case “∗” is a binary operation given to U, where it is given as shown in Table 5.
Then ( U , , w 1 ) is a BCI-algebra. Let a set of parameters E = { ε 1 , ε 2 , ε 3 , ε 4 , ε 5 } be a set of status of patients in which each parameter means
ε1: “chest pain”; ε2: “headache”; ε3: “toothache”; ε4: “mental depression”; ε5: “neurosis”
with the binary operation “ ” in Table 6.
Then ( E , , ε 1 ) is a BCI-algebra. Hence ( U , E ) is a BCI-soft universe. Let M ( E , U ) =   ( M E , G E , ) be a makgeolli structure on U defined by
M E : E P ( U ) , x U if x = ε 1 , { w 1 , w 2 , w 3 , w 5 } if x = ε 2 , { w 1 , w 3 , w 5 } if x = ε 3 , { w 3 , w 5 } if x { ε 4 , ε 5 } , G E : E P ( U ) , x { w 1 } if x = ε 1 , { w 1 , w 2 , w 3 } if x = ε 2 , { w 1 , w 2 , w 5 } if x = ε 3 , { w 1 , w 2 , w 4 , w 5 } if x = ε 4 , U if x = ε 5 , : U [ 0 , 1 ] , x 0.8 if x = w 1 , 0.7 if x = w 2 , 0.3 if x = w 3 , 0.3 if x = w 4 , 0.5 if x = w 5 ,
It is routine to verify that M ( E , U ) =   ( M E , G E , ) is a makgeolli ideal over U.
Assume that (17) is true. Since x y ( x y ) and y ( y ) for all x , y U , it follows from (17) that x min { ( x y ) , ( y ) } , that is,
( x , y U ) ( x ) min { ( x y ) , ( y ) } .
Now, let x , y U and t , r ( 0 , 1 ] such that x y t and y r . Then ( x y ) t and ( y ) r . If (18) holds, then
( x ) min { ( x y ) , ( y ) } min { t , r } ,
and so x min { t , r } . Therefore we have the following theorem.
Theorem 5.
Let ( U , E ) be a BCK/BCI-soft universe. A makgeolli structure M ( E , U ) =   ( M E , G E , ) on U is an makgeolli ideal over U if, and only if, it satisfies (14), (16), (18), and
( x U ) ( 0 ) ( x ) .
Proposition 4.
Let ( U , E ) be a BCK/BCI-soft universe. Every makgeolli ideal M ( E , U ) =   ( M E , G E , ) over U satisfies the following assertions.
(1)
( a , b E ) a b M E ( a ) M E ( b ) , G E ( a ) G E ( b ) .
(2)
( x , y U ) x y ( x ) ( y ) .
(3)
( a , b , c E ) a b c M E ( a ) M E ( b ) M E ( c ) G E ( a ) G E ( b ) G E ( c ) .
(4)
( x , y , z U ) x y z ( x ) min { ( y ) , ( z ) } .
Proof. 
Let a , b E be such that a b . Then a b = 0 , so the conditions (14) and (16) imply that
M E ( b ) = M E ( 0 ) M E ( b ) = M E ( a b ) M E ( b ) M E ( a ) ,
G E ( b ) = G E ( 0 ) G E ( b ) = G E ( a b ) G E ( b ) G E ( a ) ,
If x y for all x , y U , then x y = 0 . It follows from (18) and (19) that
( y ) = min { ( 0 ) , ( y ) } = min { ( x y ) , ( y ) } ( x ) .
Assume that a b c for all a , b , c E . Then ( a b ) c = 0 , and so
M E ( c ) = M E ( 0 ) M E ( c ) = M E ( ( a b ) c ) M E ( c ) M E ( a b ) , G E ( c ) = G E ( 0 ) G E ( c ) = G E ( ( a b ) c ) G E ( c ) G E ( a b )
by (14) and (16). If x y z for all x , y , z U , then ( x y ) z = 0 . Using (18) and (19), we have
( z ) = min { ( 0 ) , ( z ) } = min { ( ( x y ) z ) , ( z ) } ( x y ) .
It follows from (16) and (18) that
M E ( a ) M E ( a b ) M E ( b ) M E ( b ) M E ( c ) , G E ( a ) G E ( a b ) G E ( b ) G E ( b ) G E ( c ) , ( x ) min { ( x y ) , ( y ) } min { ( y ) , ( z ) } .
This completes the proof. □
Proposition 5.
Let ( U , E ) be a BCK/BCI-soft universe. Every makgeolli ideal M ( E , U ) =   ( M E , G E , ) over U satisfies the following assertions.
( a , b , c E ) M E ( a b ) M E ( a c ) M E ( c b ) G E ( a b ) G E ( a c ) G E ( c b ) .
( x , y , z U ) ( t , r ( 0 , 1 ] ) x z t , z y r x y min { t , r } .
( a , b E ) M E ( a b ) = M E ( 0 ) M E ( a ) M E ( b ) G E ( a b ) = G E ( 0 ) G E ( a ) G E ( b ) .
( x , y U ) x y ( 0 ) x ( y ) .
Proof. 
Since ( a b ) ( a c ) c b for all a , b , c E , we have (22) by (3) in Proposition 4. Let x , y , z U and t , r ( 0 , 1 ] be such that x z t and z y r . Then ( x z ) t and ( z y ) r . Since ( x y ) ( x z ) z y for all x , y , z U , it follows from (4) in Proposition 4 that
( x y ) min { ( x z ) , ( z y ) } min { t , r } .
Hence x y min { t , r } , and (23) is valid. Consider a , b E satisfying M E ( a b ) = M E ( 0 ) and G E ( a b ) = G E ( 0 ) . Then
M E ( a ) M E ( a b ) M E ( b ) = M E ( 0 ) M E ( b ) = M E ( b )
and
G E ( a ) G E ( a b ) G E ( b ) = G E ( 0 ) M E ( b ) = M E ( b ) .
Suppose that x y ( 0 ) for all x , y U . Then ( x y ) = ( 0 ) , and so
( x ) min { ( x y ) , ( y ) } = min { ( 0 ) , ( y ) } = ( y ) ,
that is, x ( y ) . This completes the proof. □
Proposition 6.
Let ( U , E ) be a BCK/BCI-soft universe. For every makgeolli ideal M ( E , U ) =   ( M E , G E , ) over U, the following are equivalent.
(1)
( a , b E ) M E ( a b ) M E ( ( a b ) b ) G E ( a b ) G E ( ( a b ) b ) . ( x , y U ) ( x y ) ( ( x y ) y ) .
(2)
( a , b , c E ) M E ( ( a c ) ( b c ) ) M E ( ( a b ) c ) G E ( ( a c ) ( b c ) ) G E ( ( a b ) c ) . ( x , y , z U ) ( ( x z ) ( y z ) ) ( ( x y ) z ) .
Proof. 
Let a , b , c E and assume that (1) is valid. Since
( ( a ( b c ) ) c ) c = ( ( a c ) ( b c ) ) c ( a b ) c ,
it follows from Proposition 4 that
M E ( ( a c ) ( b c ) ) = M E ( ( a ( b c ) ) c ) M E ( ( ( a ( b c ) ) c ) c ) M E ( ( a b ) c )
and
G E ( ( a c ) ( b c ) ) = G E ( ( a ( b c ) ) c ) G E ( ( ( a ( b c ) ) c ) c ) G E ( ( a b ) c ) .
Using (1), (2), and (3), we get ( ( x ( y z ) ) z ) z ( x y ) z for all x , y , z X . Hence
( ( x z ) ( y z ) ) = ( ( x ( y z ) ) z ) ( ( ( x ( y z ) ) z ) z ) ( ( x y ) z )
for all x , y , z X .
Conversely, suppose that (2) is true. If we take b = c and y = z in (2), then
M E ( a c ) = M E ( ( a c ) ( c c ) ) M E ( ( a c ) c ) G E ( a c ) = G E ( ( a c ) ( c c ) ) G E ( ( a c ) c )
and
( x z ) = ( ( x z ) ( z z ) ) ( ( x z ) z )
by (III) and (1). This proves (1). □
Theorem 6.
In a BCK-soft universe ( U , E ) , every makgeolli ideal is a makgeolli algebra.
Proof. 
Let M ( E , U ) = ( M E , G E , ) be a makgeolli ideal over U. For any a , b E and x , y U , we have
M E ( a b ) M E ( ( a b ) a ) M E ( a ) = M E ( ( a a ) b ) M E ( a ) = M E ( 0 b ) M E ( a ) = M E ( 0 ) M E ( a ) M E ( a ) M E ( b ) ,
G E ( a b ) G E ( ( a b ) a ) G E ( a ) = G E ( ( a a ) b ) G E ( a ) = G E ( 0 b ) G E ( a ) = G E ( 0 ) G E ( a ) G E ( a ) G E ( b ) ,
and
( x y ) min { ( ( x y ) x ) , ( x ) } = min { ( ( x x ) y ) , ( x ) } = min { ( 0 y ) , ( x ) } = min { ( 0 ) , ( x ) } min { ( x ) , ( y ) } .
Therefore M ( E , U ) = ( M E , G E , ) is a makgeolli algebra over U by Theorem 1. □
The following example shows that the converse of Theorem 6 is not true in general.
Example 5.
Let U = P ( N ) . Define a binary operation on U by
( A , B U ) A B = if A B A B otherwise .
Then ( U , , ) is a BCK-algebra (see the work by the authors of [31]). Consider a BCK-algebra E = { 0 , 1 , 2 , 3 , 4 } with the binary operation in Table 7.
Then ( U , E ) is a BCK-soft universe. Let M ( E , U ) =   ( M E , G E , ) be a makgeolli structure on U defined by
M E : E P ( U ) , x N if x = 0 , 4 N if x = 1 , 2 N if x = 2 , 3 N if x = 3 , 8 N if x = 4 , G E : E P ( U ) , x 12 N if x = 0 , 3 N if x = 1 , 6 N if x = 2 , 5 N if x = 3 , N if x = 4 , : U [ 0 , 1 ] , x 0.8 if x S , 0.3 if x S
where S is a subalgebra of U. It is routine to verify that M ( E , U ) =   ( M E , G E , ) is a makgeolli algebra over U. But it is not a makgeolli ideal over U since M E ( 4 2 ) M E ( 2 ) = M E ( 3 ) M E ( 2 ) = 3 N 2 N = 6 N 8 N = M E ( 4 ) and/or G E ( 4 2 ) G E ( 2 ) = G E ( 3 ) G E ( 2 ) = 5 N 6 N N = G E ( 4 ) .
We provide a condition for a makgeolli algebra to be a makgeolli ideal in BCK-soft universe.
Theorem 7.
In a BCK-soft universe ( U , E ) , let M ( E , U ) =   ( M E , G E , ) be a makgeolli algebra over U satisfying the conditions (3) and (4) in Proposition 4. Then M ( E , U ) =   ( M E , G E , ) is a makgeolli ideal over U.
Proof. 
By Proposition 1, we know that M E ( a ) M E ( 0 ) , G E ( b ) G E ( 0 ) and 0 ( x ) for all a E and x U . Sine a ( a b ) b and x ( x y ) y for all a , b E and x , y U , it follows from the conditions (3) and (4) in Proposition 4 that M E ( a ) M E ( a b ) M E ( b ) , G E ( a ) G E ( a b ) G E ( b ) and ( x ) min { ( x y ) , ( y ) } . Therefore, M ( E , U ) = ( M E , G E , ) is a makgeolli ideal over U. □
The following example shows that Theorem 6 is not true in a BCI-soft universe ( U , E ) .
Example 6.
Consider the two BCI-algebras U = { 0 , 1 , a , b , c } and E = { 0 , a , b , c } with binary operation and given by Table 8 and Table 9, respectively.
Then ( U , E ) is a BCI-soft universe. Let M ( E , U ) =   ( M E , G E , ) be a makgeolli structure on U defined by
M E : E P ( U ) , x U if x = 0 , { 0 , 1 , a } if x = a , { 0 , 1 } if x = b , { 0 } if x = c , G E : E P ( U ) , x { 0 , 1 } if x = 0 , { 0 , 1 , b } if x = a , { 0 , 1 , c } if x = b , U if x = c , : U [ 0 , 1 ] , x 0.9 if x = 0 , 0.8 if x = 1 , 0.3 if x { a , b } , 0.6 if x = c .
It is routine to verify that M ( E , U ) =   ( M E , G E , ) is a makgeolli ideal over U, but it is not a makgeolli algebra over U since
M E ( a ) M E ( b ) = { 0 , 1 , a } { 0 , 1 } = { 0 , 1 } { 0 } = M E ( c ) = M E ( a b ) .
We provide a condition for Theorem 6 to be true in a BCI-soft universe ( U , E ) .
Theorem 8.
In a BCI-soft universe ( U , E ) , let M ( E , U ) =   ( M E , G E , ) be a makgeolli ideal over U satisfying the following condition.
( a E , x U ) ( M E ( 0 a ) M E ( a ) , G E ( 0 a ) G E ( a ) , 0 x ( x ) ) .
Then M ( E , U ) =   ( M E , G E , ) is a makgeolli algebra over U.
Proof. 
Let a , b E and x , y U . Then
M E ( a b ) M E ( ( a b ) a ) M E ( a ) = M E ( 0 b ) M E ( a ) M E ( a ) M E ( b ) ,
G E ( a b ) G E ( ( a b ) a ) G E ( a ) = G E ( 0 b ) G E ( a ) G E ( a ) G E ( b ) ,
and ( x y ) min { ( ( x y ) x ) , ( x ) } = min { ( 0 y ) , ( x ) } min { ( y ) , ( x ) } . It follows from Theorem 1 that M ( E , U ) = ( M E , G E , ) is a makgeolli algebra over U. □
Let ( X , , 0 ) be a BCI-algebra and B ( X ) : = { x X 0 x } . For any x X and n N , we define x n by
x 1 = x , x n + 1 = x ( 0 x n ) .
The element x of X is said to be of finite periodic (see the work by the authors of [32]) if there exists n N such that x n B ( X ) . The period of x is denoted by | x | and it is given as follows.
| x | = min { n N x n B ( X ) } .
Theorem 9.
Let ( U , E ) be a BCI-soft universe in which every element of U (resp., E) is of finite period. Then every makgeolli ideal over U is a makgeolli algebra over U.
Proof. 
Let M ( E , U ) = ( M E , G E , ) be a makgeolli ideal over U. For any a E and x U , assume that | a | = m and | x | = n . Then a m B ( E ) and x n B ( U ) . Note that
( 0 a m 1 ) a = ( 0 ( 0 ( 0 a m 1 ) ) ) a = ( 0 a ) ( 0 ( 0 a m 1 ) ) = 0 ( a ( 0 a m 1 ) ) = 0 a m = 0
and
( 0 x n 1 ) x = ( 0 ( 0 ( 0 x n 1 ) ) ) x = ( 0 x ) ( 0 ( 0 x n 1 ) ) = 0 ( x ( 0 x n 1 ) ) = 0 x n = 0 .
Hence M E ( ( 0 a m 1 ) a ) = M E ( 0 ) M E ( a ) , G E ( ( 0 a m 1 ) a ) = G E ( 0 ) G E ( a ) and ( ( 0 x n 1 ) x ) = ( 0 ) ( x ) by (14) and (19). It follows from (16) and (18) that
M E ( 0 a m 1 ) M E ( ( 0 a m 1 ) a ) M E ( a ) M E ( a ) , G E ( 0 a m 1 ) G E ( ( 0 a m 1 ) a ) G E ( a ) G E ( a ) , ( 0 x n 1 ) min { ( ( 0 x n 1 ) x ) , ( x ) } ( x ) .
Also, note that
( 0 a m 2 ) a = ( 0 ( 0 ( 0 a m 2 ) ) ) a = ( 0 a ) ( 0 ( 0 a m 2 ) ) = 0 ( a ( 0 a m 2 ) ) = 0 a m 1
and
( 0 x n 2 ) x = ( 0 ( 0 ( 0 x n 2 ) ) ) x = ( 0 x ) ( 0 ( 0 x n 2 ) ) = 0 ( x ( 0 x n 2 ) ) = 0 x n 1 .
Using (28), we have
M E ( ( 0 a m 2 ) a ) = M E ( 0 a m 1 ) M E ( a ) , G E ( ( 0 a m 2 ) a ) = G E ( 0 a m 1 ) G E ( a ) , ( ( 0 x n 2 ) x ) = ( 0 x n 1 ) ( x ) .
It follows from (16) and (18) that
M E ( 0 a m 2 ) M E ( ( 0 a m 2 ) a ) M E ( a ) M E ( a ) , G E ( 0 a m 2 ) G E ( ( 0 a m 2 ) a ) G E ( a ) G E ( a ) , ( 0 x n 2 ) min { ( ( 0 x n 2 ) x ) , ( x ) } ( x ) .
Continuing this prosess, we get M E ( 0 a ) M E ( a ) , G E ( 0 a ) G E ( a ) and ( 0 x ) ( x ) , i.e., 0 x ( x ) . Hence M ( E , U ) = ( M E , G E , ) satisfies the condition (27), and therefore M ( E , U ) = ( M E , G E , ) is a makgeolli algebra over U by Theorem 8. □
Theorem 10.
Let ( U , E ) be a BCK/BCI-soft universe. Then a makgeolli structure M ( E , U ) =   ( M E , G E , ) on U is a makgeolli ideal over U if and only if the sets E E ( M E ; α ) , E E ( G E ; β ) , and U ( ; t ) are ideals of E and U, respectively, for all α , β P ( U ) and t [ 0 , 1 ] .
Proof. 
Assume that M ( E , U ) = ( M E , G E , ) on U is a makgeolli ideal over U. It is clear that 0 is contained in E E ( M E ; α ) , E E ( G E ; β ) and U ( ; t ) for all α , β P ( U ) and t [ 0 , 1 ] . Let a , b E be such that a b E E ( M E ; α ) and b E E ( M E ; α ) (resp., a b E E ( G E ; β ) and b E E ( G E ; β ) ). Then
M E ( a ) M E ( a b ) M E ( b ) α
(respectively, G E ( a ) z g E ( a b ) G E ( b ) β ), and thus a E E ( M E ; α ) (resp., a E E ( G E ; β ) ). For any x , y U , let x y U ( ; t ) and y U ( ; t ) . Then ( x y ) t and ( y ) t . It follows from Theorem 1 that ( x ) min { ( x y ) , ( y ) } t . Hence x U ( ; t ) . Therefore E E ( M E ; α ) , E E ( G E ; β ) and U ( ; t ) are ideals of E and U, respectively.
Conversely, suppose that the sets E E ( M E ; α ) , E E ( G E ; β ) and U ( ; t ) are ideals of E and U, respectively, for all α , β P ( U ) and t [ 0 , 1 ] . Let a , b E and x U be such that M E ( a ) = α , G E ( b ) = β and ( x ) = t . Then M E ( a ) = α M E ( 0 ) , G E ( b ) = β G E ( 0 ) and ( x ) = t ( 0 ) . Let a , b E and x , y U be such that M E ( a b ) = α 1 , M E ( b ) = α 2 (resp., G E ( a b ) = β 1 , G E ( b ) = β 2 ) and ( x y ) = t 1 , ( y ) = t 2 . If we take α = α 1 α 2 (resp., β = β 1 β 2 ) and t = min { t 1 , t 2 } , then a b E E ( M E ; α ) , b E E ( M E ; α ) (resp., a b E E ( G E ; α ) , b E E ( G E ; α ) ) and x y U ( ; t ) , y U ( ; t ) . It follows that a E E ( M E ; α ) (resp., a E E ( G E ; α ) ) and x U ( ; t ) . Hence
M E ( a ) α = α 1 α 2 = M E ( a b ) M E ( b )
(resp., G E ( a ) β = β 1 β 2 = G E ( a b ) G E ( b ) ) and
( x ) t = min { t 1 , t 2 } = min { ( x y ) , ( y ) } .
Therefore M ( E , U ) = ( M E , G E , ) on U is a makgeolli ideal over U by Theorem 1. □

5. Applications in Medical Sciences

Miss J (say) has cancer and needs surgery. She tries to find a hospital with excellent medical skills, low treatment costs, and friendly nurses. There are six hospitals, U = { h 1 , h 2 , h 3 , h 4 , h 5 , h 6 } and there are two parameter sets, A = { ε 1 , ε 2 , ε 3 } , and B = { δ 1 , δ 2 } , where each parameter ε i for i = 1 , 2 , 3 and δ j for j = 1 , 2 , stands for
ε 1 : Medical expenses are low ; ε 2 : Medical expenses are intermediate ε 3 : Medical expenses are expensive δ 1 : Nurses are kind ; δ 2 : Nurses are unkind
The medical skills of the hospital are indicated by the following functions.
: U [ 0 , 1 ] , x 0.1 if x = h 1 , 0.7 if x = h 2 , 0.3 if x = h 3 , 0.9 if x = h 4 , 0.8 if x = h 5 , 0.5 if x = h 6 ,
where, the higher the number, the better the medical skill. Assume that M A ( ε 1 ) = { h 1 , h 2 } , M A ( ε 2 ) = { h 3 , h 6 } , M A ( ε 3 ) = { h 4 , h 5 } , G B ( δ 1 ) = { h 2 , h 4 , h 6 } and G B ( δ 2 ) = { h 1 , h 3 , h 5 } . Then the makgeolli structure M ( A , B , U ) = ( M A , G B , ) on U is given by Table 10.
You know that, in the first row of Table 10, if you find a hospital that responds to the element ( 1 , 1 , 0.9 ) , the hospital has excellent medical skills, friendly nurses, and medical costs are also low, but you cannot see it. However, you can see the element ( 1 , 1 , 0.7 ) in the first row of Table 10, and the corresponding hospital is h 2 . Therefore, although the medical skill of h 2 is slightly lower than that of h 4 and h 5 , it can be found that the nurse is kind and also the treatment cost is cheap. Therefore Miss J will choose hospital h 2 for surgery. Even if the cost of treatment is high, if Miss J find the hospital which the medical skills are excellent and the nurses are kind, she can select the hospital h 4 that corresponds to ( M A ( ε 3 ) , G B ( δ 1 ) , ( x ) ) = ( 1 , 1 , 0.9 ) . We can see that the cost of treatment in the hospital ( h 4 ) with the best medical skills is the most expensive. If a mild cold patient tries to visit a hospital, he or she does not need high-level medical skills. Regardless of the nurse’s kindness, he/she will try to find a hospital where treatment costs are low. In this case, he or she can select the hospital h 1 .

6. Conclusions

Soft set theory, which was proposed by Molodtsov in 1999, is a generalization of fuzzy set theory. It is a good mathematical tool for dealing with uncertainty in a parametric manner. Soft set has many applications in medical diagnosis and decision making etc. As an extension of the classical set, Zadeh introduced the fuzzy set in 1965, which has been applied in so many areas. In this paper, we have introduced the concept of makgeolli structures (see Definition 1) using fuzzy and soft set theory and have applied it to BCK/BCI-algebras. We have defined the notion of makgeolli algebra (see Definition 3) and makgeolli ideal (see Definition 4) in BCK/BCI-algebras, and have investigated several properties. We have shown that every makgeolli ideal is a makgeolli algebra in BCK-soft universes (see Theorem 6). We have considered an example to show that any makgeolli algebra may not be a makgeolli ideal in BCK-soft universes (see Example 5). We have provided a condition for a makgeolli algebra to be a makgeolli ideal in BCK-soft universes (see Theorem 7). We have considered an example to show that any makgeolli ideal may not be a makgeolli algebra in BCI-soft universe (see Example 6), and have provided a condition for a makgeolli ideal to be a makgeolli algebra in BCI-soft universes (see Theorem 8). We have discussed characterization of makgeolli algebra and makgeolli ideal (see Theorems 1, 3, 5, and 10). We have made a new makgeolli algebra from old one (see Theorem 4). In the final section, we have considered an application in medical sciences. In the forthcoming research and papers, we will continue these ideas and will define new notions in several algebraic structures.

Author Contributions

The authors contributed equally to the completion of the paper.

Funding

This research received no external funding.

Acknowledgments

We would like to thank anonymous reviewers for their careful reading and valuable comments and suggestions.

Conflicts of Interest

The authors declare no conflict of interest.

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Table 1. Tabular representation of the makgeolli structure M ( A , B , U ) = ( M A , G B , ) .
Table 1. Tabular representation of the makgeolli structure M ( A , B , U ) = ( M A , G B , ) .
X h 1 h 2 h 3 h 4 h 5 h 6
( M A ( ε 1 ) , G B ( δ 1 ) , ( x ) ) ( 1 , 0 , 0.4 ) ( 1 , 1 , 0.7 ) ( 0 , 0 , 0.6 ) ( 0 , 1 , 0.2 ) ( 0 , 0 , 0.5 ) ( 0 , 1 , 0.1 )
( M A ( ε 1 ) , G B ( δ 2 ) , ( x ) ) ( 1 , 0 , 0.4 ) ( 1 , 0 , 0.7 ) ( 0 , 1 , 0.6 ) ( 0 , 1 , 0.2 ) ( 0 , 1 , 0.5 ) ( 0 , 0 , 0.1 )
( M A ( ε 1 ) , G B ( δ 3 ) , ( x ) ) ( 1 , 0 , 0.4 ) ( 1 , 0 , 0.7 ) ( 0 , 1 , 0.6 ) ( 0 , 1 , 0.2 ) ( 0 , 1 , 0.5 ) ( 0 , 1 , 0.1 )
( M A ( ε 2 ) , G B ( δ 1 ) , ( x ) ) ( 0 , 0 , 0.4 ) ( 1 , 1 , 0.7 ) ( 1 , 0 , 0.6 ) ( 1 , 1 , 0.2 ) ( 0 , 0 , 0.5 ) ( 0 , 1 , 0.1 )
( M A ( ε 2 ) , G B ( δ 2 ) , ( x ) ) ( 0 , 0 , 0.4 ) ( 1 , 0 , 0.7 ) ( 1 , 1 , 0.6 ) ( 1 , 1 , 0.2 ) ( 0 , 1 , 0.5 ) ( 0 , 0 , 0.1 )
( M A ( ε 2 ) , G B ( δ 3 ) , ( x ) ) ( 0 , 0 , 0.4 ) ( 1 , 0 , 0.7 ) ( 1 , 1 , 0.6 ) ( 1 , 1 , 0.2 ) ( 0 , 1 , 0.5 ) ( 0 , 1 , 0.1 )
( M A ( ε 3 ) , G B ( δ 1 ) , ( x ) ) ( 1 , 0 , 0.4 ) ( 0 , 1 , 0.7 ) ( 0 , 0 , 0.6 ) ( 1 , 1 , 0.2 ) ( 0 , 0 , 0.5 ) ( 1 , 1 , 0.1 )
( M A ( ε 3 ) , G B ( δ 2 ) , ( x ) ) ( 1 , 0 , 0.4 ) ( 0 , 0 , 0.7 ) ( 0 , 1 , 0.6 ) ( 1 , 1 , 0.2 ) ( 0 , 1 , 0.5 ) ( 1 , 0 , 0.1 )
( M A ( ε 3 ) , G B ( δ 3 ) , ( x ) ) ( 1 , 0 , 0.4 ) ( 0 , 0 , 0.7 ) ( 0 , 1 , 0.6 ) ( 1 , 1 , 0.2 ) ( 0 , 1 , 0.5 ) ( 1 , 1 , 0.1 )
Table 2. Cayley table for the binary operation “∗”.
Table 2. Cayley table for the binary operation “∗”.
h 0 h 1 h 2 h 3 h 4
h 0 h 0 h 0 h 0 h 0 h 0
h 1 h 1 h 0 h 0 h 1 h 0
h 2 h 2 h 1 h 0 h 2 h 0
h 3 h 3 h 3 h 3 h 0 h 3
h 4 h 4 h 4 h 4 h 4 h 0
Table 3. Cayley table for the binary operation “ ”.
Table 3. Cayley table for the binary operation “ ”.
ε 0 ε 1 ε 2 ε 3
ε 0 ε 0 ε 0 ε 0 ε 0
ε 1 ε 1 ε 0 ε 1 ε 1
ε 2 ε 2 ε 2 ε 0 ε 2
ε 3 ε 3 ε 3 ε 3 ε 0
Table 4. Cayley table for the binary operation “ ”.
Table 4. Cayley table for the binary operation “ ”.
ε 0 ε 1 ε 2 ε 3
ε 0 ε 0 ε 1 ε 2 ε 3
ε 1 ε 1 ε 0 ε 3 ε 2
ε 2 ε 2 ε 3 ε 0 ε 1
ε 3 ε 3 ε 2 ε 1 ε 0
Table 5. Cayley table for the binary operation “∗”.
Table 5. Cayley table for the binary operation “∗”.
w 1 w 2 w 3 w 4 w 5
w 1 w 1 w 1 w 3 w 4 w 5
w 2 w 2 w 1 w 3 w 4 w 5
w 3 w 3 w 3 w 1 w 5 w 4
w 4 w 4 w 4 w 5 w 1 w 3
w 5 w 5 w 5 w 4 w 3 w 1
Table 6. Cayley table for the binary operation “ ”.
Table 6. Cayley table for the binary operation “ ”.
ε 1 ε 2 ε 3 ε 4 ε 5
ε 1 ε 1 ε 1 ε 1 ε 4 ε 4
ε 2 ε 2 ε 1 ε 2 ε 5 ε 4
ε 3 ε 3 ε 3 ε 1 ε 4 ε 4
ε 4 ε 4 ε 4 ε 4 ε 1 ε 1
ε 5 ε 5 ε 4 ε 5 ε 2 ε 1
Table 7. Cayley table for the binary operation “∗”.
Table 7. Cayley table for the binary operation “∗”.
01234
000000
110000
222000
333300
443310
Table 8. Cayley table for the binary operation “∗”.
Table 8. Cayley table for the binary operation “∗”.
01abc
000abc
110abc
aaa0cb
bbbc0a
cccba0
Table 9. Cayley table for the binary operation “ ”.
Table 9. Cayley table for the binary operation “ ”.
0abc
00abc
aa0cb
bbc0a
ccba0
Table 10. Tabular representation of the makgeolli structure M ( A , B , U ) = ( M A , G B , ) .
Table 10. Tabular representation of the makgeolli structure M ( A , B , U ) = ( M A , G B , ) .
X h 1 h 2 h 3 h 4 h 5 h 6
( M A ( ε 1 ) , G B ( δ 1 ) , ( x ) ) ( 1 , 0 , 0.1 ) ( 1 , 1 , 0.7 ) ( 0 , 0 , 0.3 ) ( 0 , 1 , 0.9 ) ( 0 , 0 , 0.8 ) ( 0 , 1 , 0.5 )
( M A ( ε 1 ) , G B ( δ 2 ) , ( x ) ) ( 1 , 1 , 0.1 ) ( 1 , 0 , 0.7 ) ( 0 , 1 , 0.3 ) ( 0 , 0 , 0.9 ) ( 0 , 1 , 0.8 ) ( 0 , 0 , 0.5 )
( M A ( ε 2 ) , G B ( δ 1 ) , ( x ) ) ( 0 , 0 , 0.1 ) ( 0 , 1 , 0.7 ) ( 1 , 0 , 0.3 ) ( 0 , 1 , 0.9 ) ( 0 , 0 , 0.8 ) ( 1 , 1 , 0.5 )
( M A ( ε 2 ) , G B ( δ 2 ) , ( x ) ) ( 0 , 1 , 0.1 ) ( 0 , 0 , 0.7 ) ( 1 , 1 , 0.3 ) ( 0 , 0 , 0.9 ) ( 0 , 1 , 0.8 ) ( 1 , 0 , 0.5 )
( M A ( ε 3 ) , G B ( δ 1 ) , ( x ) ) ( 0 , 0 , 0.1 ) ( 0 , 1 , 0.7 ) ( 0 , 0 , 0.3 ) ( 1 , 1 , 0.9 ) ( 1 , 0 , 0.8 ) ( 0 , 1 , 0.5 )
( M A ( ε 3 ) , G B ( δ 2 ) , ( x ) ) ( 0 , 1 , 0.1 ) ( 0 , 0 , 0.7 ) ( 0 , 1 , 0.3 ) ( 1 , 0 , 0.9 ) ( 1 , 1 , 0.8 ) ( 0 , 0 , 0.5 )

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Ahn, S.S.; Song, S.-Z.; Jun, Y.B.; Kim, H.S. Makgeolli Structures and Its Application in BCK/BCI-Algebras. Mathematics 2019, 7, 784. https://doi.org/10.3390/math7090784

AMA Style

Ahn SS, Song S-Z, Jun YB, Kim HS. Makgeolli Structures and Its Application in BCK/BCI-Algebras. Mathematics. 2019; 7(9):784. https://doi.org/10.3390/math7090784

Chicago/Turabian Style

Ahn, Sun Shin, Seok-Zun Song, Young Bae Jun, and Hee Sik Kim. 2019. "Makgeolli Structures and Its Application in BCK/BCI-Algebras" Mathematics 7, no. 9: 784. https://doi.org/10.3390/math7090784

APA Style

Ahn, S. S., Song, S. -Z., Jun, Y. B., & Kim, H. S. (2019). Makgeolli Structures and Its Application in BCK/BCI-Algebras. Mathematics, 7(9), 784. https://doi.org/10.3390/math7090784

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