1. Introduction
The theory of duality and optimality conditions for optimization problems has received considerable attention (see [
1,
2,
3,
4,
5,
6,
7,
8,
9,
10]). The derivative (epiderivative) plays an important role in studying duality and optimality conditions for set-valued optimization problems. The contingent derivatives [
1], the contingent epiderivatives [
11] and the generalized contingent epiderivatives [
12] for set-valued maps are employed by different authors to investigate necessary or/and sufficient optimality conditions for set-valued optimization problems. Later, the second-order epiderivatives [
13], higher-order generalized contingent (adjacent) epiderivatives [
14] and generalized higher-order contingent (adjacent) derivatives [
15] for set-valued maps are used to study the second (or high) order necessary or/and sufficient optimality conditions for set-valued optimization problems. Chen et al. [
2] utilized the weak efficiency to introduce higher-order weak adjacent (contingent) epiderivative for a set-valued map, they then investigate higher-order Mond-Weir (Wolfe) type duality and higher-order Kuhn-Tucker type optimality conditions for constrained set-valued optimization problems. Li et al. [
3] used the higher-order contingent derivatives to discuss the weak duality, strong duality and converse duality of a higher-order Mond-Weir type dual for a set-valued optimization problem. Wang et al. [
4] used the higher-order generalized adjacent derivative to extend the main results of [
3] from convexity to non-convexity. Anh [
6] used the higher-order radial derivatives [
16] to discuss mixed duality of set-valued optimization problems.
It is well known that the lower-order approximating directions are very important to define the higher-order derivatives (epiderivatives) in [
2,
3,
4,
6,
14,
15]. This limits their practical applications when the lower-order approximating directions are unknown. So, it is necessary to introduce some higher-order derivatives (epiderivatives) without lower-order approximating directions. As we know, a few paper are devoted to this topic. Motivated by [
17], Li et al. [
7] proposed the higher-order upper and lower Studniarski derivatives of a set-valued map to establish necessary and sufficient conditions for a strict local minimizer of a constrained set-valued optimization problem. Anh [
8] introduced the higher-order radial epiderivative to establish mixed type duality in constrained set-valued optimization problems. Anh [
18] proposed the higher-order upper and lower Studniarski derivatives of a set-valued map to establish Fritz John type and Kuhn-Tucker type conditions, and discussed the higher-order Mond-Weir type dual for constrained set-valued optimization problems. Anh [
19] further defined the notion of higher-order Studniarski epiderivative and established higher-order optimality conditions for a generalized set-valued optimization problems. Anh [
20] noted that the epiderivatives in [
8,
19] is singleton, they proposed a notion of the higher-order generalized Studniarski epiderivative which is set-valued, and discussed its applications in optimality conditions and duality of set-valued optimization problems.
As we know that the existence conditions of weak efficient point are weaker than ones of efficient point for a set. Inspired by [
2,
8,
18,
19,
20], we introduce the higher-order weak adjacent set without the lower-order approximating directions for set-valued maps. Furthermore, we use the higher-order weak adjacent set and weak efficiency to introduce the higher-order weak adjacent epiderivative for a set-valued map, we use it and Benson proper efficiency to discuss higher-order Mond-Weir type dual for a constrained set-valued optimization problem, and then obtain the corresponding weak duality, strong duality and converse duality, respectively.
The rest of the article is as follows. In
Section 2, we recall some of definitions and notations to be needed in the paper, and so define the higher-order adjacent set of a set-valued map without lower-order approximating directions, which has some nice properties. In
Section 3, we use the higher-order adjacent set of
Section 2 to define the higher-order weak adjacent epiderivative for a set-valued map, and discuss its properties, such as existence and subdifferential. In
Section 4, we introduce a higher-order Mond-Weir type dual for a constrained set-valued optimization problem and establish the corresponding weak duality, strong duality and converse duality, respectively.
2. Preliminaries
Throughout the paper, let
X,
Y and
Z be three real normed linear spaces. The spaces
Y and
Z are partially ordered by nontrivial pointed closed convex cones
and
with nonempty interior, respectively. By
we denote the zero vector of
Y.
stands for the topological dual space of
Y. The dual cone
of
C is defined as
Its quasi-interior
is defined as
Let M be a nonempty subset of Y. We denote the closure, the interior and the cone hull of M by , and , respectively. We denote by the open ball of radius r centered at c. A nonempty subset B of C is called a base of C if and only if and .
Let
be a nonempty subset and
be a set-valued map. The domain, graph and epigraph of
F are, respectively, defined as
and
Definition 1. [9] Let and . (i) is said to be a Pareto efficient point of M () if (ii) Let . is said to be a weakly efficient point of M () if Definition 2. [10,21,22] (i) The cone C is called Daniell if any decreasing sequence in Y that has a lower bound converges to its infimum. (ii) A subset M of Y is said to be minorized if there is a such that (iii) The weak domination property is said to hold for a subset M of Y if Definition 3. Let , and .
(i) [9] The mth-order adjacent set of A at is defined bywhere . (ii) [19] The mth-order Studniarski set of A at is defined by Definition 4. Let , and . The mth-order adjacent set of K at is defined by We can obtain the equivalent characterization of in terms of sequences:
if and only if
,
such that
Now, we establish a few properties of .
Proposition 1. Let , and . Then Proof. We divide into two cases to show the proposition.
Case 1: . Note that ; for any sequence with , we choose such that This means that .
Case 2:
. Let
. Then for any sequence
with
, there exists a sequence
with
such that
Naturally, and It completes the proof. □
Remark 1. Let and . The mth-order adjacent set of K at may not be a cone; see Example 1.
Example 1. Let , and . A simple calculation shows that Take and . Then , i.e., is not a cone here.
Proposition 2. Let be a set-valued map and . Then,
(i)
(ii)
Proof. Since , it is clearly that . Therefore we only need to prove .
Let
and
. Then for any sequence
with
, there exists a sequence
with
such that
namely,
Since
,
and
, one has
This together with implies and so
(ii) Obviously, (ii) follows from (i). The proof is complete. □
Proposition 3. Let and . If K is a convex set, then is a convex set.
Proof. Let
and
. Then for any
, there exist
such that
From the convexity of
K, we have
It follows from the definition of
that
Thus, is a convex set and the proof is complete. □
3. Higher-Order Weak Adjacent Epiderivatives
In this section, we introduce the notion of higher-order weak adjacent epiderivative of a set-valued map without lower-order approximating directions, and obtain some properties of the epiderivative.
Firstly, we recall the notions of mth-order weak adjacent epiderivative with lower-order approximating directions and generalized Studniarski epiderivative without lower-order approximating directions.
Definition 5. [2] Let , and . The mth-order weak adjacent epiderivative of F at for vectors is the set-valued map from X to Y defined by Definition 6. [20] Let and . The mth-order generalized Studniarski epiderivative of F at is the set-valued map from X to Y defined by Motivated by Definitions 5 and 6, we introduce the higher-order epiderivative without lower-order approximating directions.
Definition 7. Let and . The mth-order weak adjacent epiderivative of F at is a set-valued map defined by Remark 2. There are many examples show that possibly exists even if and do not; see Examples 2 and 3. Therefore it is interesting to study this derivative and employ it to investigate the Mond-Weir duality for set-valued optimization problems.
Example 2. Let , and be defined by . Take and . Then, simple calculations show thatand So, for any , , but .
Example 3. Let , , and be defined by . Take . Then Therefore, for any , , but .
Theorem 1. Let and . Let C be a pointed closed convex cone and Daniell. If is minorized for all , then exists.
Proof. The proof is similar to that of Theorem 3.1 in [
2]. □
Definition 8. [23] Let be a nonempty set and . M is called star-shaped at , if for any point with , the segment Definition 9. [10] Let E be a nonempty convex set. The map F is said to be C-convex on E, if for any and , Motivated by Definition 9, we introduce the following concept.
Definition 10. Let E be a star-shaped set at . The map F is said to be generalized C-convex at on E, if for any and , Remark 3. Let E be a convex set and . If F is C-convex on E, then F is generalized C-convex at on E. However, the converse implication is not true.
To understand Remark 3, we give the following example.
Example 4. Let , , and be defined by Take . Then E is a convex set, and F is generalized C-convex at on E. Take and , thenand Therefore F is not C-convex on E.
Definition 11. [24] Let be a star-shaped set at . A set-valued map is said to be decreasing-along-rays at if for any and with , one has Next, we give an important property of the mth-order weak adjacent epiderivative.
Proposition 4. Let E be a star-shaped set at . Let be a set-valued map and . Suppose that the following conditions are satisfied:
(i) F is decreasing-along-rays at ;
(ii) F is generalized C-convex at on E;
(iii) the set fulfills the weak domination property for all .
Then for all , one has and Proof. Let
and
. For any
with
,
. Since
E is a star-shaped set at
,
and
Together this with conditions (i) and (ii) implies
Hence,
. It follows from the definition of
that
. Replacing
with
x of condition (iii), from the definition of
, we have
This completes the proof. □
We now give an example to explain Proposition 4.
Example 5. Let , , and be defined as . Take . Then, simple calculations show that and We can easily see that all conditions of Proposition 4 are satisfied. For any , one has and Therefore Proposition 4 is applicable here.
The following examples show that every condition of Proposition 4 is necessary.
Example 6. Let , , and be a set-valued map satisfing . Take . By a simple calculation, we obtainand Thus , for any .
Obviously, the conditions (ii) and (iii) of Proposition 4 are satisfied except condition (i), and Thus Proposition 4 does not hold here and the condition (i) of Proposition 4 is essential.
Example 7. Let , , and be given by Take . Then,and Clearly, the conditions (i) and (iii) of Proposition 4 are satisfied except condition (ii), and for any , Therefore Proposition 4 does not hold here and the condition (ii) of Proposition 4 is essential.
Example 8. Let , , and be defined by . Take . Then a simple calculation shows that This means that: (i) and ; (ii) for each . Obviously, does not fulfill the weak domination property for each and . Thus Proposition 4 does not hold here and the condition (iii) of Proposition 4 is essential.
4. Higher-Order Mond-Weir Type Duality
In this section, by virtue of the higher-order weak adjacent epiderivative of a set-valued map, we establish Mond-Weir duality theorems for a constrained optimization problem under Benson proper efficiency.
Let
,
and
be two set-valued maps. We consider the following constrained set-valued optimization problem:
Let and . We denote by . The point is said to be a feasible solution of (SOP) if and .
Definition 12. [25] The feasible solution is called a Benson proper efficient solution of (SOP) if Let
,
,
and
. Inspired by [
2], We establish a new higher-order Mond-Weir type dual problem (DSOP) of (SOP) as follows:
The point is called a feasible solution of (DSOP) if satisfies conditions (1), (2), (3) and (4) of (DSOP). A feasible solution is called a maximal solution of (DSOP) if for all , , where , and is the feasible solution of (DSOP)}.
Definition 13. [26] Let , the interior tangent cone of K at is defined bywhere stands for the closed ball centered at and of radius λ. Theorem 2. (Weak Duality) Let E be a star-shaped set at and . Let and be the feasible solution of (SOP) and (DSOP), respectively. Then the weak duality: holds if the following conditions are satisfied:
(i) is decreasing-along-rays at ;
(ii) is generalized -convex at on E;
(iii) the set fulfills the weak domination property.
Proof. Since
is a feasible solution of (SOP),
. Take
. It follows from (2) and (4) that
From Proposition 4 it follows that
and
Noting that
and
, we have by (
1) and (
6) that
. Combining this with (
5), one has
Thus and the proof is complete. □
Theorem 2 is an extension of [
2], Theorem 4.1 from cone convexity to generalized cone convexity. Now, we give an example to illustrate that Theorem 2 can apply but [
2], Theorem 4.1 dose not.
Example 9. Let , , be given as and be defined by Then sets of the feasible solutions for (DSOP) and (SOP) are and , respectively. Thus and Theorem 2 holds here. However, [2], Theorem 4.1 is not applicable here because G is not C-convex on E. Lemma 1. [27] Let and . If K is convex, then The inclusion relation between the generalized second-order adjacent epiderivative and convex cone
C and
D is established by Wang and Yu in [
28], Theorem 5.2. Inspired by [
28], Theorem 5.2, we next introduce the equality of the higher-order weak adjacent epiderivative and convex cone
C and
D to the proof of the strong duality theory.
Lemma 2. Let and . If is a Benson proper efficient solution of (SOP), then for all , Proof. We can easily see that (
7) is equivalent to
Thus we only need to prove that (
8) holds. Suppose on the contrary that there exist
,
and
such that
and
It follows from
that
. Then for any sequence
with
, there exists
such that
From (
9) and (
11), there exists a sufficiently large natural number
such that
where the last inclusion follows from Lemma 1. According to Definition 13, there exists
such that
Since
, there exists a sufficiently large natural number
with
such that
. Combining this with (
13), one has
From (
12) and (
14), we have
It follows from
,
and
that
Noting that
, there exist
,
,
and
such that
By (
15),
. Therefore
It follows from (
11) and (
16) that
. Combining this with (
10), one has
which contradicts that
is a Benson proper efficient solution of (SOP). Thus (
7) holds and the proof is complete. □
According to Theorem 2.3 of [
29], we have the following lemma.
Lemma 3. [29] Let W be a locally convex space, H and Q be cones in W. If H is closed, Q have a compact base and , then there is a pointed convex cone such that and . Theorem 3. (Strong Duality) Let E be a convex subset of X, and . Suppose that the following conditions are satisfied:
(i) is -convex on E;
(ii) fulfills the weak domination property for all ;
(iii) C has a compact base;
(iv) be a Benson proper efficient solution of (SOP);
(v) for any .
Then there exist and such that is a maximal solution of (DSOP).
Proof. Define
where
.
Step 1. We firstly prove that is a convex set. Indeed, it is sufficient to show the convexity of .
Let
. Then there exist
and
such that
According to the definition of , one has .
Since
is
-convex on
E,
is a convex set. From Proposition 3,
is a convex set. So for any
,
Combining this with (
17), one has
Therefore is a convex set and so is a convex set.
Step 2. We prove that there exist and such that is a feasible solution of (DSOP).
Since
is a convex set,
is a convex cone. According to Lemma 2, we have
In fact, assume that (
19) does not hold. Since
is a cone, there exists
such that
Then there exist
,
,
and
such that
According to the definition of
, for any
, there exists
such that
This together with condition (v) implies
It follows from (
20), (
21), (
22) and
that
which contradicts that
is a Benson proper efficient solution of (SOP). Thus (
19) holds.
Since
C has a compact base,
also has a compact base. Combining this with (
19) and Lemma 3, replacing
H and
Q with
and
, there exists a pointed convex cone
such that
and
Let , where . Thus is a convex cone.
Next, we further prove that
is a pointed cone. According to Proposition 1, we get
. Combining this with the weak domination property of
P, we get
For
and
, we have
and so
It follows from (
24) and (
26) that
Hence,
Combining with the definition of
A, one has
To obtain this result, we suppose on the contrary that there exists
. Then there exist
and
such that
and
So
which contradicts (
27). Therefore (
28) holds. Then
is a pointed convex cone and
.
To see the conclusion, we suppose on the contrary that there exists
such that
because
is a pointed convex cone and
is a convex cone. From the definition of
, there exist
and
such that
According to the definition of
, there exist
,
,
and
such that
Since
, without loss of generality, we may assume that
. It follows from the definition of
that
and so
By (
30) and (
31), we have
which contradicts (
18).
To obtain this conclusion, we replace
B and
C in [
30], Theorem 2.2 with
and
, respectively, which together with the fact:
yields that
Let
and
. Then by (
23) and (
33), one has
and so (
32) holds.
According to the separation theorem for convex set and (
29), there exist
and
such that
and
By (
32) and (
34), we have
Taking
in (
36), one has
thus
. For any
, take
in (
36). Then we can observe that
, which implies
.
It follows from (
35) that
Together with (
25), we get
. It follows from
and
that
. Thus,
Combining this with (
37), one has
and so
Thus is a feasible solution of (DSOP).
Step 3. We prove that is a maximal solution of (DSOP).
Suppose on the contrary that there exists a feasible solution
such that
. By
, we have
Since
is a feasible solution of (SOP), it follows from Theorem 2 that
, which contradicts (
38). The proof is complete. □
Theorem 4. (Converse Duality) Let E be a star-shaped set at . Let , and such that is a feasible solution of (DSOP). Then is a Benson proper efficient solution of (SOP) if the following conditions are satisfied:
(i) is decreasing-along-rays at ;
(ii) is a generalized -convex at on E;
(iii) the set fulfills the weak domination property for all .
Proof. It follows from (
1), (3) and (4) that
According to Proposition 4, we get
By (2), we have
. It follows from
and
that
, thus
. Then
It follows from (
39), (
40) and (
41) that
Further more, we can get
and so
Assume that the feasible solution
is not a Benson proper efficient solution of (SOP). Then there exists
such that
. This together with (
42) implies that
It follows from
and
that
, which contradicts (
43). Thus
is a Benson proper efficient of (SOP) and the proof is complete. □
Remark 4. Example 9 also illustrates that Theorem 4 extends [2], Theorem 4.3 from the cone convexity to generalized cone convexity. Indeed, take . Then simple calculations show thatand Then we can choose and such that is a feasible solution of (DSOP). It is easy to show that the all conditions of Theorem 4 are fulfilled and is a Benson proper efficient solution of (SOP). Thus Theorem 4 holds here. However, [2], Theorem 4.3 is not applicable here because G is not C-convex on E.