1. Introduction
Let 
 and 
 be two fuzzy sets in 
 with the membership functions 
 and 
, respectively. The arithmetic operations 
, 
, 
 and 
 are based on the extension principle. More precisely, the membership functions are given by
      
      for all 
. In this paper, we consider the vectors of fuzzy sets in 
. The purpose is to study the addition, difference and scalar products of vectors of fuzzy sets.
Suppose that 
 and 
 consist of fuzzy sets in 
 given by
      
      where 
 and 
 are fuzzy sets in 
 for 
. Then, we study the addition 
, the difference 
 and the scalar product 
.
The addition 
, the difference 
 and multiplication 
 regarding the components can be realized as shown above. Let 
 and 
 be the membership functions of 
 and 
, respectively, and let ⊙ denote any one of the arithmetic operations 
 between 
 and 
. According to the extension principle, the membership function of 
 is defined by
      
      for all 
, where the arithmetic operations 
 correspond to the arithmetic operations 
. More detailed properties can refer to the monographs of Dubois and Prade [
1] and Klir and Yuan [
2]. In general, we can consider the t-norms instead of minimum functions by referring to Bede and Stefanini [
3], Dubois and Prade [
4], Gebhardt [
5], Gomes and Barros [
6], Fullér and Keresztfalvi [
7], Mesiar [
8], Ralescu [
9], Weber [
10], Wu [
11,
12,
13] and Yager [
14]. More precisely, the membership function of 
 is given by
      
      for all 
, where 
t is a t-norm that is a function from 
 into 
 satisfying four axioms. It is well-known that the minimum function min is a t-norm. In this paper, we consider the general aggregation function rather than using t-norms. In this case, the membership function of 
 is given by
      
      for all 
, where 
 is an aggregation function from 
 into 
 without needing to satisfy some required conditions.
According to the arithmetic operations (
1), the addition 
, the difference 
 and the scalar product 
 can be naturally defined as follows
      
We can see that the scalar product 
 is a fuzzy set in 
. The membership function of 
 can be realized below. Let 
 for 
. The membership function of 
 can be obtained from (
1). Therefore, the membership function of 
 is given by
      
      where 
 is an aggregation function from 
 into 
. In particular, the extension principle says that the aggregation function 
 is given by the minimum function. Therefore, the membership function of 
 is given by
      
We can see that 
 and 
 are still vectors of fuzzy sets. However, their membership functions cannot be obtained directly from (
1). The main purpose of this paper is to propose two methodologies to define the membership functions of 
 and 
. Those methodologies can also be used to define the membership function of the scalar product 
.
Following the conventional way, we can use the extension principle to define the arithmetic operations of vectors of fuzzy sets. In this paper, we consider the general aggregation functions rather than using t-norms. We should mention that the decomposition theorem is a well-known result in fuzzy sets theory. Alternative, we also use the form of decomposition theorem to define the arithmetic operations of vectors of fuzzy intervals. These two methodologies can lead to the different types of membership functions. In this paper, we establish the equivalences between using the extension principle and the form of decomposition theorem under some mild conditions.
In 
Section 2, the concept and basic properties of non-normal fuzzy sets are presented. In 
Section 3, the arithmetic operations of vectors of fuzzy sets are presented using the extension principle based on the general aggregation functions. In 
Section 4, the arithmetic operations of vectors of fuzzy sets are presented using the form of decomposition theorem. In 
Section 5, many types of difference of vectors of fuzzy sets are proposed using the extension principle and the form of decomposition theorem, and their 
-level sets are studied. Their equivalences are also established under some mild conditions. In 
Section 6, we study the addition of vectors of fuzzy sets following the same theme from 
Section 5. In 
Section 7, the scalar product of vectors of fuzzy sets are proposed, and their 
-level sets are also studied.
  2. Non-Normal Fuzzy Sets
Let 
 be a fuzzy set in 
 with membership function 
. For 
, the 
-level set of 
 is denoted and defined by
      
We remark that the 
-level set 
 can be an empty set when 
 is larger than the supremum of the membership function 
. This ambiguity will be clarified in this section. On the other hand, the support of a fuzzy set 
 is the crisp set defined by
      
The 0-level set  is defined to be the closure of the support of , i.e., .
The range of membership function  is denoted by  that is a subset of . We see that the range  can be a proper subset of  with . For example, the range  can be some disjoint union of subintervals of .
Example 1. The membership function of a trapezoidal-like fuzzy number is given by  Notice that if , we still can consider the -level set . Since , it is possible that the -level set  can be an empty set for some . Therefore, when we study the properties that deal with more than two fuzzy sets, we cannot simply present the properties by saying that they hold true for each , since some of the -level sets can be empty. In this case, we need to carefully treat the ranges of membership functions.
Example 2. Continuing from Example 1, we see that . However, we still have the -level set . It is clear to see that , where .
 Let 
 be a real-valued function defined on 
, and let 
S be a subset of 
. Recall that the supremum 
 is attained if and only if there exists 
 such that 
 for all 
 with 
. Equivalently, the supremum 
 is attained if and only if
      
Define 
. If 
, then 
. If the supremum 
 is not attained, then 
. For example, assume that
      
It is clear to see that . In this case, the supremum  is not attained. However, we have . In this case, the 1-level set , since .
Proposition 1. Let  be a fuzzy set in  with membership function . Define  and Then  for all  and  for all . Moreover, we have  and  The interval  presented in Proposition 1 is also called an interval range of . We see that the interval range  contains the actual range . The role of interval range  can be used to say  for all  and  for all . We also remark that  and  in general, since the range  can be some disjoint union of subintervals of .
Example 3. Continuing from Example 1, recall that . We also see that . Proposition 1 says that . It is clear to see that  for all  and  for all .
 Therefore, the interval  plays an important role for considering the -level sets. In other words, the range  is not helpful for identifying the -level sets.
Recall that  is called a normal fuzzy set in  if and only if there exists  such that . In this case, we have . However, the range  is not necessarily equal to  even though  is normal.
Let 
 be a normal fuzzy set in 
. The well-known decomposition theorem says that the membership function 
 can be expressed as
      
      where 
 is the characteristic function of the 
-level set 
. If 
 is not normal, then we can similarly obtain the following form.
Theorem 1. (
Decomposition Theorem) 
Let  be a fuzzy set in . Then the membership function  can be expressed as where  is given in (3).    3. Arithmetics Using the Extension Principle
The generalized extension principle for non-normal fuzzy sets has been extensively studied in Wu [
15]. In this paper, we use the extension principle to study the arithmetics of a vector of fuzzy intervals.
We denote by  the family of all fuzzy sets in  such that each  satisfies the following conditions.
The membership function  is upper semi-continuous and quasi-concave on .
The 0-level set  is a compact subset of ; that is, a closed and bounded subset of .
Each  is also called a fuzzy interval. If the fuzzy interval  is normal and the 1-level set  is a singleton set , where , then  is also called a fuzzy number with core value a. It is well-known that the -level sets of fuzzy interval  are all closed intervals denoted by  for , which can be regarded as a closed interval with degree . This is the reason why we call  as a fuzzy interval.
Example 4. The membership function of a trapezoidal fuzzy interval is given by which is denoted by . It is clear to see that Proposition 1 says that the interval range is given by If , then the α-level set . For , the α-level set  is given by  Let 
 and 
 be two vectors in 
. Then, the arithmetics of vectors 
 and 
 are given by
      
Let 
 and 
 be two vectors of fuzzy intervals given by
      
Based on the extension principle (abbreviated as EP), we study the arithmetics of  and  by considering the scalar product , the addition  and the difference . Given the aggregation function , the membership functions are defined below.
For each 
, the membership function of the scalar product 
 is given by
          
For each 
 and for the operation 
 corresponding to the operation 
, the membership function of 
 is given by
          
If the aggregation function  is taken to be the minimum function, then the above arithmetics coincide with the extension principle.
Given any fuzzy intervals 
 and 
 in 
, let
      
      and
      
From Proposition 1, the interval ranges 
 of 
 and 
 of 
 are given by
      
      and
      
We also write 
 to denote the ranges of membership functions 
 for 
, and write 
 to denote the ranges of membership functions 
 for 
. Let
      
Example 5. Continuing from Example 4, we consider the following trapezoidal fuzzy intervals and the interval ranges are given by From (10), by taking the aggregation function  as the minimum function, we have  We denote by 
 and 
 the interval ranges of 
 and 
, respectively, where 
 and 
 depend on 
 and 
. The supremum of range of membership function is given by
      
Therefore, the definition of interval range says that
      
      and
      
Proposition 1 says that
      
      and
      
Example 6. Continuing from Example 5, we take the aggregation function  as the minimum function. The membership function of scalar product  is given by and it is a continuous function. Therefore, the supremum is attained. This says that the interval range  of scalar product  is given By considering the α-level sets, we also see that The membership function of addition  is given by The interval range  of addition  is given by By considering the α-level sets, we also see that The membership function of difference  is given by The interval range  of addition  is given By considering the α-level sets, we also see that  For further discussion, we provide a useful lemma.
Lemma 1. (Royden [
16], p. 161) 
Let X be a topological space, and let K be a compact subset of X. Let f be a real-valued function defined on X. Then the following statements hold true.- (i)
 If f is upper semi-continuous, then f assumes its maximum on a compact subset of X; that is, the supremum is attained in the following sense: - (ii)
 If f is lower semi-continuous, then f assumes its minimum on a compact subset of X; that is, the infimum is attained in the following sense: 
 Proposition 2. Suppose that the aggregation function  is given by Then, the following statements hold true.
- (i)
 - (ii)
 The supremum  is attained if and only if the supremum  is attained, and the supremum  is attained if and only if the supremum  is attained.
- (iii)
 
 Proof.  It suffices to prove the case of 
, since the case of 
 can be similarly obtained. From (
11), we have
        
On the other hand, from (
11) again, we also have
        
        which proves part (i).
Suppose that the supremum 
 is attained. From (
11), there exists 
 such that
        
Since the set 
 is closed and bounded, i.e., a compact set, and the functions 
 and 
 are upper semi-continuous, Lemma 1 says that the supremum in (
13) is attained. In other words, there exists 
 such that
        
For convenience, we write 
, 
 and 
 for 
. Then, from (
13) and (
14), we have
        
        and we can say that 
 for some 
. Part (i) also says that 
 for some 
. Then, using (
15), we have
        
        which says that the supremum 
 is attained. Using (
8) and (
9), we obtain 
 is a closed interval, which also says that 
. Therefore, we conclude that the supremum 
 is also attained.
On the other hand, suppose that the supremum 
 is attained. Then, we have
        
        and
        
        which also says that the supremum 
 is attained; i.e., there exists 
 such that 
. By referring to (
12), there exists 
 such that its 
-component is 
 and
        
        where 
 for 
. In this case, we have 
, which says that the supremum 
 is attained, which proves part (ii). Finally, part (iii) follows immediately from parts (i) and (ii). This completes the proof. □
   4. Arithmetics Using the Form of Decomposition Theorem
The differentiation and integrals of fuzzy-number-valued functions using the form of decomposition theorem have been studied in Wu [
17]. In this paper, we use the form of decomposition theorem to study the arithmetics of vector of fuzzy intervals.
Let 
 and 
 be two vectors of fuzzy intervals with components 
 and 
, respectively, for 
. Let
      
Then 
 is not empty, since 
 and 
 are intervals with left end-point 0 for 
. For each 
, the 
-level sets of 
 and 
 are nonempty and denoted by
      
In order to define the difference , we consider the family  that is formed by applying the operation  to the -level sets  and  for , where each  is a subset of . In this paper, we study three different families described below.
We take
          
          to define 
.
We take
          
          where 
 are bounded closed intervals given by
          
          for 
 to define 
.
We take
          
          where 
 are bounded closed intervals given by
          
          for 
 to define 
.
For 
, based on the form of decomposition theorem, the membership function of 
 is defined by
      
Example 7. Continuing from Example 5, we have We consider three familiesgiven below. for all . The membership function of  is given by where  and  are bounded closed intervals given by which says that  is a singleton set  for all . Similarly, we can obtain for all . Therefore, we obtain for all , which is a singleton set in . The membership function of  is given by where  and  are bounded closed intervals given by Therefore, we obtainfor all , which is a singleton set in . The membership function of  is equal to membership function of . 
 In order to define the addition , we consider the family  that is formed by applying the operation  to the -level sets  and  for , where each  is a subset of . In this paper, we study three different families described below.
We take
          
          to define 
.
We take
          
          where 
 are bounded closed intervals given by
          
          for 
 to define 
.
We take
          
          where 
 are bounded closed intervals given by
          
          for 
 to define 
.
For 
, based on the form of decomposition theorem, the membership function of 
 is defined by
      
Example 8. Continuing from Examples 5 and 7, we consider three familiesgiven below. for all . The membership function of  is given by where  and  are bounded closed intervals given by for all . We also obtain for all . Now, we have for all . The membership function of  is equal to the membership function of 
where  and  are bounded closed intervals given by for all . The membership function of  is equal to membership function of .
 In order to define the scalar product of  and , we consider the family  that is formed by applying the operation  to the -level sets  and  for , where each  is a subset of . In this paper, we study three different families described below.
We take
          
          to define the scalar product 
.
We take
          
          where 
 are bounded closed intervals given by
          
          to define the scalar product 
.
We take
          
          to define the scalar product 
.
For 
, based on the form of decomposition theorem, the membership function of 
 is defined by
      
Example 9. Continuing from Examples 5 and 7, we consider three familiesgiven below. for all . The membership function of  is given by where  is a bounded closed interval given by for all . Therefore, we obtain The membership function of  is equal to the membership function of .
Therefore, the membership function of  is equal to the membership function of .
 We denote by 
 and 
 the interval ranges of membership functions 
 and 
 for 
, respectively, where 
 and 
 depends on 
 and 
. We consider the supremum of range of membership function 
 as follows:
Therefore, the definition of interval ranges says that
      
      and
      
Proposition 1 also says that
      
      and
      
Proposition 3. Let  and  be fuzzy intervals. Suppose that the supremum  in (16) is attained. Then  Proof.  Recall the definition 
 and 
 in (
8) and (
9), respectively, for 
. It is clear to see that
        
Since 
 is assumed to be attained, it follows that 
. By referring to (
23), we can take 
, which says that the supremum 
 is attained for the range 
. Therefore, from (
24), we have 
. We can similarly obtain 
. This completes the proof. □
 More detailed properties will be studied separately in the sequel.
Example 10. Continuing from Examples 7–9, we consider the interval ranges ,  and  of ,  and , respectively. Recall that . From (23), we see that . Proposition 3 says that Therefore, it follows that    5. Difference of Vectors of Fuzzy Intervals
Let  and  be two vectors of fuzzy intervals with components  and , respectively, for . Here we study the -level set of  that is obtained from the extension principle, and the -level sets of  for  that are obtained from the form of decomposition theorem.
  5.1. Using the Extension Principle to Study the -Level Sets of
      
Given any aggregation function 
, recall that the membership function of difference 
 is defined by
        
        for any 
. Let 
 be the interval range of 
. The 
-level set 
 of 
 for 
 can be obtained by applying the results obtained in Wu [
11] to the difference 
, which is shown below. For each 
 with 
, we have
        
The 0-level set is given by
        
Moreover, for each , the -level sets  are closed and bounded subsets of .
Now, the aggregation function 
 is given by
        
Proposition 2 says that 
. Therefore, for each 
, we have 
, 
 and 
 for all 
. Now, for each 
 with 
, using (
27), we have
        
For the 0-level set, from (
28) and (
4), it is not difficult to show that
        
Regarding the components 
 and 
, let 
 be the interval range of 
. From Proposition 2, we can similarly obtain 
. For 
, we also have
        
Therefore, from (
28) and (
29), for 
, we obtain
        
The above results are summarized in the following theorem.
Theorem 2. Let  and  be any fuzzy intervals. Suppose that the aggregation function  is given by Then, we have the following results.
- (i)
 Let  be the interval range of  for . Then, for each , we have We also have .
- (ii)
 Let  be the interval range of . We have For each , we also have 
 Remark 1. When  and  are taken to be fuzzy numbers instead of fuzzy intervals, it follows that Therefore, Theorem 2 says that for all .
 Example 11. Continuing from Examples 5 and 7, Theorem 2 says thatandand for . Moreover, we have  for .
   5.2. Using the Form of Decomposition Theorem to to Study the -Level Sets of
Let 
 and 
 be fuzzy intervals. The family 
 is given by
        
We see that 
 and 
 for each 
 and for 
. Now, for 
 with 
, we have
        
Based on the form of decomposition theorem, the membership function of 
 is given by
        
Let  be the interval range of . The -level sets  of  for  are presented below.
Proposition 4. Suppose that the supremum  is attained. Then  and for each .
 Proof.  We first consider 
 with 
. Given any 
, we see that 
 by (
31). Therefore, we obtain 
, which proves the inclusion 
.
For proving another direction of inclusion, it is clear to see that  is a nested family. Given any , i.e., , let . Assume that . Let . According to the concept of supremum, there exists  satisfying  and , which implies . This also says that , since  by the nestedness.
Now, we assume that 
. Since 
 is an interval with left end-point 0, given any 
 with 
, we can consider the sequence 
 in 
 satisfying 
 with 
 for all 
s. Since 
 and 
 are fuzzy intervals for 
, it is well-known that
          
Since 
, we conclude that
          
Let 
. According to the concept of supremum, there exists 
 satisfying 
 and 
, which implies 
. This also says that 
 by the nestedness for all 
s. Therefore, we conclude that 
. From (
33), it follows that 
. Therefore, for 
 with 
, we obtain
          
For the 0-level set, since 
 from Proposition 3, by referring to (
4), it is not difficult to show that
          
This completes the proof. □
 Now, for 
 and for 
 with 
, we take
        
Let 
 be obtained using the form of decomposition theorem based on the family 
 that is defined in (
34). Let 
 be the interval range of 
. Suppose that the supremum 
 is attained for each 
. Then each 
 is a bounded and closed interval with left end-point 0 for 
. In this case, it is also clear to see that 
 is a bounded and closed interval with left end-point 0; that is, the supremum 
 is also attained. By referring to Proposition 4, we can similarly obtain 
 and
        
        for 
 and 
, which also implies
        
        for each 
. The above results are summarized below.
Theorem 3. Let  and  be fuzzy intervals. Suppose that the family  is given by Let  be the interval range of , and let  be the interval range of  for .
- (i)
 Suppose that the supremum  is attained. Then  andfor each . - (ii)
 Suppose that the supremum  is attained for each . Thenfor each  and each , andfor each . 
 Remark 2. From (8) and (9), we see that if the supremum  and  are attained, then  and  are closed intervals for all , which also say that the supremum  and  for  are attained.  Example 12. Continuing from Example 7, part (i) of Theorem 3 says that for . Moreover, we have  for .
   5.3. Using the Form of Decomposition Theorem to to Study the -Level Sets of
Let 
 and 
 be any fuzzy intervals. The family 
 is given by
        
        and
        
        where 
 are bounded closed intervals given by
        
        for 
. Based on the form of decomposition theorem, the membership function of 
 is given by
        
Let  be the interval range of . Here we study the -level sets  of  for .
For 
, we write
        
It is clear to see that 
 is a nested family. Since 
 is a bounded interval with left end-point 0, using the nestedness, we can show that
        
From (
37), we also see that
        
Using (
38), we can also obtain
        
Suppose that the supremum 
 is attained. By applying (
39) to the argument in the proof of Proposition 4, we can show that 
 and
        
        for any 
.
Now, we consider the difference 
 of components 
 and 
 for 
. Using the form of decomposition theorem, the membership function of 
 is defined by
        
Let 
 be the interval range of 
. We also study the 
-level sets 
 of 
 for 
. Suppose that the supremum 
 is attained. Using the argument in the proof of Proposition 4 again, we can obtain 
 and
        
        for any 
.
In order to obtain the compact form of the -level sets, we propose a concept below.
Definition 1. We say that  is a canonical fuzzy interval if and only if  is a fuzzy interval such that  and  are continuous with respect to α on .
 Now, we assume that 
 and 
 are any canonical fuzzy intervals. Let
        
Then .
We also see that 
 and 
 are continuous functions on 
. Then, for 
 with 
, we can obtain
        
The above results are summarized below.
Theorem 4. Let  and  be any fuzzy intervals. Suppose that the family  is given byandwhere  are bounded closed intervals given byfor . Let  be the interval range of , and let  be the interval range of  for . - (i)
 Suppose that the supremum  is attained. Then  andfor each . - (ii)
 Suppose that the supremum  is attained for each . Thenfor each  and each , andfor each . 
Assume that  and  are canonical fuzzy intervals. Then, for , we havethat are bounded and closed intervals.  Example 13. Continuing from Example 7 by referring to (20), part (i) of Theorem 4 says that for . Moreover, we have  for .
   5.4. Using the Form of Decomposition Theorem to Study the -Level Sets of
Let 
 and 
 be any fuzzy intervals. The family 
 is given by
        
        and
        
        where 
 are bounded closed intervals given by
        
        for 
. Based on the form of decomposition theorem, the membership functions of 
 and 
 for 
 are given by
        
        for any 
 and
        
        for any 
, respectively. Let 
 and 
 be the interval ranges of 
 and 
, respectively, for 
. Herein we study the 
-level sets 
 of 
 for 
, and the 
-level sets 
 of 
 for 
. We first provide some useful lemmas.
Lemma 2. Let I be a closed subinterval of  given by  for some . Let  and  be two bounded real-valued functions defined on I with  for each . Suppose that the following conditions are satisfied:
 is an increasing function and  is a decreasing function on I;
 and  are left-continuous on .
Let  for . For any fixed , the functionis upper semi-continuous on I.  Lemma 3. Let I be a closed subinterval of  given by  for some . For each , let  and  be bounded real-valued functions defined on I with  for each . Suppose that the following conditions are satisfied:
 are increasing function and  are decreasing function on I for ;
 and  are left-continuous on  for .
Let  for  and for , and let . For any fixed , the following functionis upper semi-continuous on I.  Proof.  Lemma 2 says that the functions
          
          are upper semi-continuous on 
I for 
. For 
, we define the sets
          
The upper semi-continuity of  says that  is a closed set for . For , we want to claim . Given any , it follows that  and , i.e.,  and  for , which also implies  for . Therefore, we obtain the inclusion . On the other hand, suppose that  for . It follows that  and  for ; i.e.,  and . Therefore, we obtain the equality , which also says that  is a closed set, since each  is a closed set for . For , it is clear to see that  is a closed subinterval of . Therefore, we conclude that  is indeed upper semi-continuous on I. This completes the proof. □
 Now, we assume that the supremum 
 is attained. Then 
 is a bounded closed interval with 
 by referring to Proposition 3. We also assume that 
 and 
 are canonical fuzzy intervals. Under these assumptions, we claim
        
Then 
. We also see that 
 and 
 are continuous functions on 
. Using Lemmas 2 and 3, given any fixed 
, the functions
        
        and
        
        are upper semi-continuous on 
 for 
.
Given any 
 with 
, suppose that 
 and 
 for all 
 with 
. Then 
 for all 
. Since 
 is a bounded closed interval, i.e., a compact set, and 
 is upper semi-continuous on 
 as described above, the supremum of the function 
 is attained by Lemma 1. This says that
        
        for some 
, which violates 
. Therefore, there exists 
 with 
 satisfying 
, which shows the following inclusion:
On the other hand, the inclusion
        
        is obvious. This shows (
40).
Suppose that the supremum 
 is attained. Then 
 is also a bounded closed interval. Therefore, we can similarly obtain 
 and
        
The above results are summarized below.
Theorem 5. Let  and  be canonical fuzzy intervals. Suppose that the family  is given byandwhere  are bounded closed intervals given byfor . Let  be the interval range of , and let  be the interval range of  for . - (i)
 Suppose that the supremum  is attained. Then  andfor each  with , and the 0-level set - (ii)
 Suppose that the supremum  is attained for each . Thenfor each  with  and each . The 0-level set is Moreover, for , we havewhich are bounded and closed intervals. 
 Remark 3. We remark that, in general, we cannot have the following equality: When  and  are taken to be canonical fuzzy numbers instead of canonical fuzzy intervals, it follows that Then, we can have the following equality:  Example 14. Continuing from Example 7 by referring to (21), we have . Part (i) of Theorem 5 says that for . Moreover, we have  for .
   5.5. The Equivalences and Fuzziness
Next, we present the equivalences between  and  in Theorems 2 and 3, respectively.
Theorem 6. Let  and  be any fuzzy intervals. Suppose that  and  are obtained from Theorems 2 and 3, respectively. We also assume that the supremum  is attained. Then Moreover, for , we have  Proof.  From Propositions 3 and 2, we have 
. The equality (
41) follows immediately Theorems 2 and 3, which also says that 
. This completes the proof. □
 We are not able to study the equivalences among ,  and . However, we can study their fuzziness by considering the -level sets. The formal definition regarding the fuzziness is given below.
Definition 2. Let  and  be two fuzzy intervals with interval ranges  and , respectively. We say that  is fuzzier than  if and only if  and  for all  with .
 Suppose now that we plan to collect  real number data  in . Owing to the unexpected situation, we cannot exactly obtain the desired data. Instead, we can just obtain the fuzzy data  that can be described by some suitable membership functions. Now, we have two ways to calculate the difference between  and . One is based on the extension principle to obtain , and another one is based on the form of decomposition theorem to obtain  for . We claim that  is fuzzier than . In other words, we prefer to take , which has less fuzziness.
Let 
 and 
 be canonical fuzzy intervals, and let 
 and 
 be obtained from Theorems 4 and 5, respectively. Suppose that the supremum 
 is attained. Then we have
        
For each 
 with 
, we also have
        
        and
        
Since the inclusion
        
        is obvious, it follows that
        
        which says that 
 is fuzzier than 
.
On the other hand, from Theorems 6 and 4, we have
        
For each 
 with 
, we also have
        
It follows that
        
        which says that 
 is fuzzier than 
. The above results are summarized below.
Theorem 7. Let  and  be canonical fuzzy intervals. Suppose that , ,  and  are obtained from Theorem 2, Theorem 3, Theorem 4 and Theorem 5, respectively. We also assume that the supremum  is attained. Thenand for each . In other words,  is fuzzier than , and  is fuzzier than .
 Remark 4. Theorem 7 says that, when  and  are taken to be canonical fuzzy intervals, we may prefer to pick  that has less fuzziness in applications.
   6. Addition of Vectors of Fuzzy Intervals
Let  and  be two vectors of fuzzy intervals with components  and , respectively, for . Next we study the -level set of  that is obtained from the extension principle, and the -level sets of  for  that are obtained from the form of decomposition theorem.
  6.1. Using the Extension Principle to Study the -Level Sets of
Given any aggregation function 
, the membership function of addition 
 is defined by
        
        for any 
. Let 
 be the interval range of 
. The 
-level set 
 of 
 for 
 can be obtained by applying the results obtained in Wu [
11] to the addition 
, which is shown below. For each 
 with 
, we have
        
The 0-level set is given by
        
Moreover, for each , the -level sets  are closed and bounded subsets of .
When the aggregation function 
 is given by
        
Proposition 2 says that 
. Therefore, for each 
, we have 
, 
 and 
 for all 
. Now, for each 
 with 
, using (
42), we have
        
For the 0-level set, from (
43) and (
4), it is not difficult to show that
        
Regarding the components 
 and 
, let 
 be the interval range of 
. From Proposition 2, we can similarly obtain 
, and, for each 
, we also have
        
Therefore, from (
43) and (
44), for 
, we obtain
        
The above results are summarized in the following theorem.
Theorem 8. Let  and  be fuzzy intervals. Suppose that the aggregation function  is given by Then, we have the following results.
- (i)
 Let  be the interval range of  for . For each , we have We also have .
- (ii)
 Let  be the interval range of . We have For each , we also have 
 Example 15. Continuing from Examples 5 and 7, part (ii) of Theorem 8 says thatandand for . Moreover, we have  for .
   6.2. Using the Form of Decomposition Theorem to Study the -Level Sets
Let 
 and 
 be fuzzy intervals. The family 
 is given by
        
Since 
 and 
 for 
 and 
, given any 
 with 
, we have
        
Based on the form of decomposition theorem, the membership function of 
 is given by
        
Let 
 be the interval range of 
. Suppose that the supremum 
 is attained. Using the similar argument in the proof of Proposition 4, we can obtain 
 and the 
-level sets 
 of 
 are given by
        
        for 
.
Now, for 
 and for 
 with 
, we take
        
Then, for 
, from (
45), we see that
        
Let 
 be obtained using the form of decomposition theorem based on the family
        
        that is defined in (
47). Let 
 be the interval range of 
. Suppose that the supremum 
 is attained for each 
. Then the supremum 
 is also attained. For 
, we can similarly obtain 
 and
        
        which also implies
        
The above results are summarized below.
Theorem 9. Let  and  be fuzzy intervals. Suppose that the family  is given by Let  be the interval range of , and let  be the interval range of  for .
- (i)
 Suppose that the supremum  is attained. Then  andfor each . Moreover, we have where  is obtained from Theorem 8.
- (ii)
 Suppose that the supremum  is attained for each . Thenfor each  and each , and for each .
 Next, we study the addition  by considering a family that has the same form of Theorem 4. We first need a useful property given below.
Lemma 4. Let  be a fuzzy interval with interval range . Then the function  is lower semi-continuous on , and the function  is upper semi-continuous on .
 Theorem 10. Let  and  be fuzzy intervals. Suppose that the family  is given byandwhere  are bounded closed intervals given by If we further assume that the supremum  is attained, then  Proof.  Let 
 and 
. Then 
. Lemma 4 say that 
 is lower semi-continuous on 
 and 
 is upper semi-continuous on 
. Then, for 
 with 
, we can obtain
          
Therefore, by referring to (
48), we have
          
          which is the same as (
45). Therefore, we obtain 
. Now, we assume that the supremum 
 is attained. Theorems 8 and 9 say that
          
          and
          
          for each 
, which says that 
. This completes the proof. □
 Next, we study the addition  by considering a family that has the same form of Theorem 5. However, in this case, we need to consider the canonical fuzzy intervals rather than the fuzzy intervals.
Theorem 11. Let  and  be canonical fuzzy intervals. Suppose that the family  is given byandwhere  are bounded closed intervals given byfor . Suppose that the supremum  is attained. Then  Proof.  For each 
, it is clear to see that
          
Since the supremum 
 is attained, for each 
 with 
, using the similar argument of Theorem 5, we can obtain
          
This completes the proof. □
 We remark that Theorem 11 needs to consider the canonical fuzzy intervals rather than the fuzzy intervals, and assume that the supremum  is attained.
Remark 5. When  and  are taken to be canonical fuzzy numbers instead of canonical fuzzy intervals, it follows that which also says that the supremum  is attained. Therefore, the above theorems are applicable.
 Example 16. Using Theorem 11 and Example 15, we see thatand    7. Scalar Product of Vectors of Fuzzy Intervals
In the sequel, we are going to use the extension principle by referring to (
6) to study the scalar product 
, and use the form of decomposition theorem by referring to (
22) to study the scalar product 
.
  7.1. Using the Extension Principle
Given any aggregation function 
, the membership function of scalar product 
 is defined by
        
        for any 
. Let 
 be the interval range of 
. The 
-level set 
 of 
 for 
 can be obtained by applying the results obtained in Wu [
11] to the scalar product 
, which is shown below. For each 
 with 
, we have
        
The 0-level set is given by
        
Moreover, for each , the -level sets  are closed and bounded subsets of .
Now, the aggregation function 
 is given by
        
Proposition 2 says that 
. Therefore, for each 
, we have 
, 
 and 
 for all 
. Now, for each 
 with 
, using (
49), we have
        
        where 
 and 
 are given in (
18) and (
19). For the 0-level set, from (
50) and (
4), it is not difficult to show that
        
Definition 3. Let  be a fuzzy set in  with membership function . We say that  is nonnegative when  for each .
 It is clear to see that a fuzzy interval 
 is nonnegative if and only if 
 for each 
. Suppose that 
 and 
 are nonnegative fuzzy intervals. Then
        
The above results are summarized in the following theorem.
Theorem 12. Let  and  be any fuzzy intervals. Suppose that the aggregation function  is given by Let  be the interval range of . Then , and, for each , we havewhere  and  are given in (18) and (19). Suppose that  and  are nonnegative fuzzy intervals. Thenwhere , ,  and  are given in (17).  Example 17. Continuing from Examples 5 and 7, Theorem 12 says that we need to calculateand In other words, given any fixed , we want to calculate Since , the minimum isand the maximum is Therefore, Theorem 12 says that for . Moreover, we have  for .
   7.2. Using the Form of Decomposition Theorem
Let 
 and 
 be fuzzy intervals. The family 
 is given by
        
        and
        
Since 
 and 
 for 
 and 
, given any 
 with 
, we have
        
Based on the form of decomposition theorem, the membership function of 
 is given by
        
Let 
 be the interval range of 
. Suppose that the supremum 
 is attained. Using the similar argument in the proof of Proposition 4, we can obtain 
 and the 
-level sets 
 of 
 is given by
        
        for 
. The above results are summarized below.
Theorem 13. Let  and  be any fuzzy intervals. Suppose that the family  is given by We also assume that the supremum  is attained. Then , and, for , we have When  and  are taken to be nonnegative fuzzy intervals, we have  Example 18. By referring to Example 17, Theorems 12 and 13 say that for . Moreover, we have  for .
 Next, we study the scalar product  by considering a different family that has the similar form of Theorem 4. Recall that  is a canonical fuzzy interval in a universal set U if and only if  is a fuzzy interval such that  and  are continuous with respect to  on .
Theorem 14. Let  and  be canonical fuzzy intervals. Suppose that the family  is given bywhere  is a bounded closed interval given by We also assume that the supremum  is attained. Then , and, for , we have When  and  are taken to be nonnegative canonical fuzzy intervals, we have  Proof.  We define two functions 
 and 
 on 
 as follows:
          
Then 
 and 
 are continuous on 
, since we consider the canonical fuzzy intervals. We also see that 
. Using the similar argument of Theorem 4, we can obtain 
, and, for 
, we also have
          
This completes the proof. □
 Example 19. Continuing from Examples 5 and 7, we can obtainand for . Moreover, we have  for .
 Theorem 15. Let  and  be any canonical fuzzy intervals. Suppose that the family  is given byand We also assume that the supremum  is attained. Then , and, for , we have When  and  are taken to be nonnegative canonical fuzzy intervals, we have  Proof.  Using the similar argument of Theorem 5, we can obtain 
. For 
, we also have
          
By referring to (
52), we complete the proof. □
 Example 20. By referring to Example 19, Theorems 14 and 15 say that for . Moreover, we have  for .
   7.3. The Equivalences and Fuzziness
Next, we present the equivalences among  and  for .
Theorem 16. Let  and  be fuzzy intervals. Suppose that  and  are obtained from Theorems 12 and 13, respectively. We also assume that the supremum  is attained. Then Moreover, for , we have  Theorem 17. Let  and  be canonical fuzzy intervals. Suppose that  and  are obtained from Theorems 14 and 15, respectively. We also assume that the supremum  is attained. Then Moreover, for , we have  Theorem 18. Let  and  be nonnegative canonical fuzzy intervals. Suppose that , ,  and  are obtained from Theorem 12, Theorem 13, Theorem 14 and Theorem 15, respectively. We also assume that the supremum  is attained. Then Moreover, for , we have  The equivalence between  and  cannot be guaranteed. The following theorem compares their fuzziness.
Theorem 19. Let  and  be canonical fuzzy intervals. Suppose that  and  are obtained from Theorems 13 and 14, respectively. We also assume that the supremum  is attained. Then  and  is fuzzier than .
 Proof.  For 
 with 
, it is clear to see that
          
          and
          
From Theorems 16 and 17, we obtain
          
          for each 
 with 
, which says that 
 is fuzzier than 
. This completes the proof. □