1 Introduction

Let K be a nonempty subset of a real Hausdorff topological vector space E, and f : K × KR a bifunction such that f(x, x) ≥ 0 for all xK. Then, the scalar equilibrium problem consists in finding x ̄ K such that

f ( x ̄ , y ) 0 , y K .

It provides a unifying framework for many important problems, such as optimization problems, variational inequality problems, complementary problems, minimax inequality problems, Nash equilibrium problems, and fixed point problems, and has been widely applied to study problems arising in economics, mechanics, and engineering science (see [1]). On the other hand, several operations research problems are formulated with a multicriteria consideration. These are vector optimization problems, vector variational inequality and complementarity problems and vector equilibrium problems (VEPs). Recently, the VEP has received much attention by many authors because it provides a unified model including vector optimization problems, vector variational inequality problems, vector complementarity problems and vector saddle point problems as special cases (see, for example, [224] and the references therein).

It is well known that another important problem for VEPs is to study the topological properties of solutions set. Among its topological properties, the connectedness is of interest. Recently, Lee et al. [25], Cheng [26] have studied the connectedness of weak efficient solutions set for vector variational inequalities in finite dimensional Euclidean space. Gong [2729] has studied the connectedness of the various solutions set for VEPs in infinite dimension space. Chen et al. [30] studied the connectedness and the compactness of the weak efficient solutions set for set-valued VEPs and the set-valued vector Hartman-Stampacchia variational inequalities in normed linear space. Gong and Yao [31] have studied the connectedness of the set of efficient solutions for generalized systems. Zhong et al. [32] have studied the connectedness and path-connectedness of solutions set for symmetric VEPs. However, the connectedness of approximate solutions set for VEPs remained unstudied.

In this paper, we show a scalarization result of ε-weak efficient solution for a VEP. Using this scalarization result, we discuss the connectedness of ε-weak efficient and ε-efficient solutions sets for VEPs under some suitable conditions in real Hausdorff topological vector spaces. The main results presented in this paper generalize some known results due to Gong [27] and Gong and Yao [31].

2 Preliminaries

Throughout this paper, let X and Y be two real Hausdorff topological vector spaces and A a nonempty subset of X. Let F : A × AY be a mapping and C be a closed convex pointed cone in Y. The cone C induces a partial ordering in Y, defined by

z 1 z 2 i f a n d o n l y i f z 2 - z 1 C .

Let

C * = { f Y * : f ( y ) 0 f o r a l l y C }

be the dual cone of C.

Denote the quasi-interior of C* by C#, that is,

C # = { f Y * : f ( y ) > 0 f o r a l l y C \ { 0 } } .

Let D be a nonempty subset of Y. The cone hull of D is defined as

c o n e ( D ) = { t d : t 0 , d D } .

A nonempty convex subset B of the convex cone C is called a base of C if

C = c o n e ( B ) a n d 0 c l ( B ) .

It is easy to see that C# ≠ ∅ if and only if C has a base.

Throughout this paper, we always assume that intC ≠ ∅. Let e be a fixed point in intC and we set

C = { f C * \ { 0 } : f ( e ) = 1 } , C = { f C # : f ( e ) = 1 } .

Now, we give the concepts of ε-weak efficient solution, ε-efficient solution, and ε-f efficient solution for the VEP.

Definition 2.1. A vector xA satisfying

F ( x , y ) - i n t C - ε e f o r a l l y A ,

is called a ε-weak efficient solution to the VEP. Denote by Vε-W(A, F) the set of all ε-weak efficient solutions to the VEP.

Definition 2.2. A vector xA satisfying

F ( x , y ) - C \ { 0 } - ε e f o r a l l y A ,

is called a ε-efficient solution to the VEP. Denote by V ε (A, F) the set of all ε-efficient solutions to the VEP.

Definition 2.3. Let fC*\{0}. A vector xA is called a ε-f efficient solution to the VEP if

f ( F ( x , y ) ) - ε f o r a l l y A ,

Denote by Vε-f(A, F) the set of all ε-f efficient solutions to the VEP.

Definition 2.4. [33] Let G be a set-valued map from a topological space W to another topological space Q. We say that G is

  1. (i)

    upper semicontinuous at x0W if, for any neighborhood U(G(x0)) of G(x0), there is a neighborhood U (x0) of x0 such that G(x) ⊂ U (G(x0)) for all xU(x0);

  2. (ii)

    upper semicontinuous on W if it is upper semicontinuous at each xW;

  3. (iii)

    lower semicontinuous at x0W if, for any net {xα : α ∈ I} converging to x0 and for any y0G(x0), there exists a net y α G(x α ) that converges to y0;

  4. (iv)

    lower semicontinuous on W if it is lower semicontinuous at each xW;

  5. (v)

    continuous on W if it is both upper semicontinuous and lower semicontinuous on W;

  6. (vi)

    closed if Graph(G) = {(x, y) : xW, yG(x)} is a closed subset in W × Q.

3 Scalarization

Lemma 3.1. Suppose F (x, A) + C is a convex set for each xA. Then,

V ε - W ( A , F ) = f C V ε - f ( A , F ) .

Proof. We first prove that

f C V ε - f ( A , F ) V ε - W ( A , F ) .

In fact, letting x 0 f C V - f ( A , F ) , then there exists fC',

f ( F ( x 0 , y ) ) - ε , f o r a l l y A .
(3.1)

We claim that x0Vε-W(A, F). If not, then there exists y0A such that F (x0, y0) ∈ -intC - εe. Thus, we have

f ( F ( x 0 , y 0 ) + ε e ) < 0

and so

f ( F ( x 0 , y 0 ) ) < - f ( ε e ) = - ε ,

which is a contradiction to (3.1).

We next prove that

V ε - W ( A , F ) f C V ε - f ( A , F ) .

Let xVε-W(A, F). Then, F (x, A) ∩ (-intC - εe) = ∅. Since C is a pionted convex cone, we have

( F ( x , A ) + C + ε e ) ( - i n t C ) = .

By assumption, we know that F (x, A) + C is a convex set. Using the separation theorem for convex sets, there exists some gY *\{0}, such that

i n f { g ( F ( x , y ) + c + ε e ) : y A , c C } s u p { g ( - c ) : c C } .
(3.2)

From (3.2), we get gC*\{0} and so

g ( F ( x , y ) ) - g ( ε e ) f o r a l l y A ,

where e ∈ intC with g (e) > 0. Letting f= g g ( e ) , then f (F (x, y)) ≥ -ε, for all yA and f (e) = 1. Thus, fC' and so

x f C V ε - f ( A , F ) .

This completes the proof.

Remark 3.1 When ε = 0, it is easy to see that

V ε - W ( A , F ) = f C V ε - f ( A , F ) = f C * \ { 0 } V ε - f ( A , F ) .

Therefore, Lemma 3.1 generalizes Lemma 2.1 in [27].

4 Existence of the solutions

Definition 4.1. The bifunction F : A × AY is concave-like with respect to the first variable, if for t ∈ [0, 1], the following condition is satisfied: For x1, x2A, there exists x3A, such that

F ( x 3 , y ) t F ( x 1 , y ) + ( 1 - t ) F ( x 2 , y ) + C , f o r a l l y A .

The bifunction F : A×AY is convex-like with respect to the second variable, if for t ∈ [0, 1], the following condition is satisfied: for y1, y2A, there exists y3A, such that

F ( x , y 3 ) t F ( x , y 1 ) + ( 1 - t ) F ( x , y 2 ) - C , f o r a l l x A .

Theorem 4.1. Let A be a nonempty compact subset of X, and fC'. Assume that the following conditions are satisfied:

  1. (i)

    F (x, x) ∈ C - εe, for all xA;

  2. (ii)

    F : A × AY is concave-like with respect to the first variable and convex-like with respect to the second variable;

  3. (iii)

    For each fixed yA, the function xf (F (x, y)) is upper semicontinuous on A.

Then, Vε-f(A, F) ≠ ∅.

Proof. Define the set-valued map G : A → 2A by

G ( y ) = { x A , f ( F ( x , y ) ) - ε }

By assumption, yG (y), for all yA, so G (y) ≠ ∅. By assumption, we can see that G (y) is a closed subset of A. Next, we prove that ∩{G (y) : yA} ≠ ∅. Since A is a compact, we need to show that i = 1 n G ( y i ) for any arbitrary chosen y1,..., y n in A. Suppose it is not true. Then, there exists a set B = {y1,..., y n } ⊂ A such that i = 1 n G ( y i ) . Thus, for any xA, there exists y i B such that xG (y i ). It follows that

f ( F ( x , y i ) ) + ε < 0

and so there exists η i > 0 such that

f ( F ( x , y i ) ) + ε < - η i , i = 1 , 2 , , n .

Since xf (F (x, y)) is upper semicontinuous on A, we can choose η > 0 such that, for any xA, there exists y i B satisfying

f ( F ( x , y i ) ) + ε + η < 0 .

Define g : ARn by

g ( x ) = ( - f ( F ( x , y 1 ) ) - ε - η , - f ( F ( x , y 2 ) ) - ε - η , . . . , - f ( F ( x , y n ) ) - ε - η ) ,

where xA. We get

g ( x ) i n t R + n , f o r a l l x A .
(4.1)

Since fC' and F (x, y) is concave-like with respect to the first variable, we can see that, for t ∈ [0, 1], x1, x2A, there exists x3A such that

g ( x 3 ) t g ( x 1 ) + ( 1 - t ) g ( x 2 ) - C .

This shows that g ( A ) + R + n is a convex set. It follows from (4.1) that

0 g ( A ) + i n t R + n .

By the separation theorem of convex sets (see, for example, [34]), we can find t1,..., t n ≥ 0 with i = 1 n t i =1 such that

0 i = 1 n t i ( - f ( F ( x , y i ) ) - ε - η ) , f o r a l l x A .

It follows that

i = 1 n t i f ( F ( x , y i ) ) - ε - η , f o r a l l x A .

By assumption, there exists yA such that

F ( x , y ) i = 1 n t i ( F ( x , y i ) ) - C , f o r a l l x A .

Since fC', we have

f ( F ( x , y ) ) f i = 1 n t i ( F ( x , y i ) ) , f o r a l l x A .

So f (F (x, y)) ≤ -ε - η < -ε, for all xA. Setting x = y, it follows that

f ( F ( y , y ) ) < - ε .

On the other hand, by the assumption,

f ( F ( y , y ) ) - ε .

This is a contradiction. Therefore, ∩{G (y) : yA} ≠ ∅, and so there exists x ∈ ∩{G (y) : yA}. This means that Vε-f(A, F) ≠ ∅. This completes the proof.

5 Connectedness of the solutions set

In this section, we discuss the connected results of ε-weak efficient solutions set and ε-efficient solutions set.

Definition 5.1. Let A be a convex set. The bifunction F : A × AY is C-concave with respect to the first variable, if for t ∈ [0, 1], x1, x2A,

F ( t x 1 + ( 1 - t ) x 2 , y ) t F ( x 1 , y ) + ( 1 - t ) t F ( x 2 , y ) + C .

It is clear that when A is a convex set, F : A×AY is C-concave with respect to the first variable, then it is concave-like about the first variable.

Theorem 5.1 Let A be a nonempty compact convex subset of X, and fC'. Assume that the following conditions are satisfied.

(i) F (x, x) ∈ C - εe, for all xA;

(ii) F : A × AY is C-concave with respect to the first variable and convex-like with respect to the second variable;

(iii) For each fixed yA, the function xf (F (x, y)) is upper semicontinuous on A;

(iv) D = {F (x, y) : x, yA} is a bounded set of Y.

Then, Vε-W(A, F) is a connected set.

Proof. Define a set-valued mapping H : C' → 2A by

H ( f ) = V - f ( A , F ) , f C .

By Theorem 4.1, we know that, for each fC', Vε-f(A, F) ≠ ∅. It is easy to see that C' is a convex set and so is connected. Next, we prove that, for each fC', H (f) is a connected set. Let x1, x2H (f), we have x1, x2A, and

f ( F ( x i , y ) ) - ε , y A , i = 1 , 2 .
(5.1)

Because F : A ×AY is C-concave with respect to the first variable, for each fixed yA, t ∈ [0, 1],

F ( t x 1 + ( 1 - t ) x 2 , y ) t F ( x 1 , y ) + ( 1 - t ) F ( x 2 , y ) + C .

Hence

t f ( F ( x 1 , y ) ) + ( 1 - t ) f ( F ( x 2 , y ) ) f ( F ( t x 1 + ( 1 - t ) x 2 , y ) ) .

It follows from (5.1) that

f ( F ( t x 1 + ( 1 - t ) x 2 , y ) ) - ε .

Hence

t x 1 + ( 1 - t ) x 2 H ( f )

and so H (f) is a convex set. Thus, it is a connected set.

Next, we show that H is upper semicontinuous on C'. Since A is compact, we only need to show that H is closed. Let {(f α , x α ) : αI} ⊂ Graph (H) be a net such that (f α , x α ) → (f, x), where f α f means that {f α } converges to f with respect to the strong topology β (Y*, Y) in Y*. Since C' is a closed set and A is a compact set, we know that (f, x) ∈ C' × A. From x α H (f α ) = Vε- (A, F), we have

f α ( F ( x α , y ) ) - ε .
(5.2)

For any δ > 0,

U = y * Y * : sup u D | y * ( u ) | < δ

is a neighborhood of 0 with respect with to β (Y *, Y). Since f α f, there exists α0I such that f α - fU, for all αα0. It follows that

sup u D | ( f α - f ) ( u ) | < δ , w h e n e v e r α α 0 .

Therefore, for any yA,

| ( f α - f ) ( F ( x α , y ) ) | < δ , w h e n e v e r α α 0

and so

lim α ( f α ( F ( x α , y ) ) - f ( F ( x α , y ) ) ) = 0 , f o r a l l y A .
(5.3)

Because xf (F (x, y)) is upper semicontinuous on A, then

l i m s u p f ( F ( x α , y ) ) f ( F ( x , y ) ) .
(5.4)

From (5.2), (5.3) and (5.4), we have

- ε l i m s u p f α ( F ( x α , y ) ) (1) lim α ( f α ( F ( x α , y ) ) - f ( F ( x α , y ) ) ) + l i m s u p f ( F ( x α , y ) ) (2) f ( F ( x , y ) ) . (3) (4)

Hence, xH (f) = Vε-f(A, F). By Theorem 3.1 in [35], f C V ε - f ( A , F ) is a connected set. Because F : A × AY is convex-like with respect to the second variable, we have F (x, A) + C is a convex set, by Lemma 3.1,

V ε - W ( A , F ) = f C V ε - f ( A , F )

is a connected set. This completes the proof.

Next, we give an example to illustrate Theorem 5.1.

Example 5.1 Let X = R, Y = R2, C= R + 2 = { ( x 1 , x 2 ) : x 1 0 , x 2 0 } , ε = 2, e = (2, 3), and A = [0, 2]. Let

F ( x , y ) = ( y - x 2 - 2 , y - x 2 - 4 ) , x , y A .

Then, F satisfies all conditions of Theorem 5.1. It is easy to see that V ε - W ( A , F ) = 0 , 2 . Clearly, Vε-W(A, F) is a nonempty connected set.

Definition 5.2. The bifunction F : A ×AY is ε-C strictly monotone if, for any x, yA, xy,

F ( x , y ) + F ( y , x ) - i n t C - 2 ε e .

Theorem 5.2 Suppose that all conditions of Theorem 5.1 are satisfied and F : A × AY is ε-C strictly monotone. Then, Vε-W(A, F) is a path connected set.

Proof. Define the set-valued mapping H : C' → 2A by

H ( f ) = V ε - f ( A , F ) , f C .

By Theorem 4.1, we know that, for each fC', Vε-f(A, F) ≠ ∅. Furthermore, because F : A × AY is ε-C strictly monotone, it is easy to see that, for each fC', H (f) = Vε-f(A, F) is a single point set. From the proof of Theorem 5.1, we know that H is upper semicontinuous on C' and so it is continuous on C'. Since C' is a convex set, so it is a path connected set. Hence,

V ε - W ( A , F ) = H ( C ) = f C H ( f ) = f C V ε - f ( A , F )

is a path connected set. This completes the proof.

Next, we give an example to illustrate Theorem 5.2.

Example 5.2 Let X = R, Y = R2, C= R + 2 = { ( x 1 , x 2 ) : x 1 0 , x 2 0 } , ε = -1, e = (1, 2), and A = [-1, 1]. Let

F ( x , y ) = ( x ( y - x ) + 1 , x ( y - x ) + 2 ) , x , y A .

Then, F satisfies all the conditions of Theorem 5.2. It is easy to see that Vε-W(A, F) = {0}. Clearly, Vε-W(A, F) is a nonempty path connected set.

Next, we give a lemma before we give the connectedness theorem of ε-efficient solutions set.

Lemma 5.1. Suppose that all conditions of Theorem 5.2 are satisfied, then

f C V ε - f ( A , F ) V ε ( A , F ) c l f C V ε - f ( A , F ) .

Proof. By Theorem 4.1, we know that, for each fC', Vε-f(A, F) ≠ ∅. By definition, we have

f C V ε - f ( A , F ) V ε ( A , F ) V ε - W ( A , F ) .
(5.5)

From Lemma 3.1, we have

V ε - W ( A , F ) = f C V ε - f ( A , F ) .
(5.6)

By (5.5) and (5.6), we have

f C V ε - f ( A , F ) V ε ( A , F ) f C V ε - f ( A , F ) .

Next, we prove that

f C V ε - f ( A , F ) c l f C V ε - f ( A , F ) .

Define the set-valued mapping: H : C' → 2A by

H ( f ) = V ε - f ( A , F ) , f C .

From Theorem 5.2, we know that H (f) is a single-valued mapping, and H is continuous on C'.

Let x f C V ε - f ( A , F ) . Then, there exists fC', such that

{ x } = V ε - f ( A , F ) = H ( f ) .

Let gC", and set

f n = n - 1 n f + 1 n g = f + 1 n ( g - f ) .

Then, f n C# and f n (e) = 1. Thus, f n C".

Next, we show that {f n } converges to f with respect to the topology β (Y*, Y). For any neighborhood of 0 with respect to β (Y*, Y), there exist bounded subsets B i Y (i = 1, 2,..., m) and δ > 0 such that

i = 1 m f Y * : sup y B i | f ( y ) | < δ U .

Since B i is bounded and g - fY *, it is easy to see that |(g - f) (B i )| is bounded for i = 1, 2,..., m. This implies that there exists N such that

sup y B i 1 n ( g - f ) ( y ) < δ , i = 1 , 2 , . . . , m ; n N .

Hence, 1 n ( g - f ) U, that is f n - fU. Hence, {f n } converges to f with respect to β (Y*, Y).

Since H is continuous on f, we have H (f n ) → H (f). Set {x n } = H (f n ), then

{ x n } = H ( f n ) = V ε - f n ( A , F ) f C V ε - f ( A , F ) .

Because {x} = H (f), we have x n x. This implies that

x c l f C V ε - f ( A , F ) .

Since x f C V ε - f ( A , F ) is arbitrary, we have

f C V ε - f ( A , F ) c l f C V ε - f ( A , F ) .

Therefore,

f C V ε - f ( A , F ) V ε ( A , F ) c l f C V ε - f ( A , F ) .

This completes the proof.

Theorem 5.3. Suppose that all the conditions of Theorem 5.2 are satisfied. Then, V ε (A, F) is a connected set.

Proof. By Lemma 5.1, we have

f C V ε - f ( A , F ) V ε ( A , F ) c l f C V ε - f ( A , F ) .
(5.7)

From Theorem 5.2, we can get

f C V ε - f ( A , F )

is connected set and so (5.7) implies that V ε (A, F) is a connected set. This completes the proof.

Remark 5.1 When ε = 0, we can get

f C V ε - f ( A , F ) = f c V ε - f ( A , F ) .

Therefore, Theorem 5.3 generalizes Theorem 2.2 in [31].

Next, we give an example to illustrate Theorem 5.3.

Example 5.3 Let X = R, Y = R, C = R+, ε = 1, e = 1, and A = [1, 2]. Let F (x, y) = x (y - x) - 1 for all x, yA. Then, it is easy to check that all the conditions of Theorem 5.3 are satisfied and

V ε ( A , F ) = { 1 } .

Clearly, V ε (A, F) is a nonempty connected set.