1 Introduction

It is well known that Ekeland’s variational principle (for short, EVP), a very important result first presented by Ekeland [10] in 1974, is as follows:

Theorem 1.1 (Ekeland [10, 11])

Let X be a complete metric space with a metric d. Let f be a function from X into (,+] which is proper lower semicontinuous and bounded from below. Then for uX and λ>0, there exists vX such that

  1. (i)

    f(v)f(u)λd(u,v),

  2. (ii)

    f(w)>f(v)λd(v,w) for every wv.

It is well known that the primitive EVP is a powerful tool on many applications in optimization, nonlinear analysis, mathematical economy and mathematical programming. Moreover, EVP is equivalent to the Caristis fixed point theorem [5, 8] and nonconvex minimization theorem according to Takahashi [21]. The studies of several forms of Ekeland’s variational principle for vector valued functions were obtained by many authors, for instance, Nemeth [20], Tammer [22] and Isac [16, 17].

To begin with, let X be a (real) linear space, E be a (real) topological vector space, K be a cone in E and e,f:XE, be two map**s. Under mild conditions of f and e, Nemeth [20] got the conclusion that for ε>0 and yX there exists a zX such that

  1. (i)

    (f(z)f(y)+εe(zy))K,

  2. (ii)

    (f(w)f(z)+εe(wz)) K c ; whenever e(wz)0,

where K c is a complement of K.

Next, let Y be a topological vector space, KX, X be a real Banach space and f:XY. Tammer [22] showed that under mild assumptions on f and K, for ε>0, there exists an xK such that

  1. (i)

    f(x)f( x ε )+ε c 0 D{0}, xK,

  2. (ii)

    x ε x 0 ε ,

  3. (iii)

    f(x)f( x ε )+ ε x x ε c 0 D{0}, xK,

where x 0 is a weakly e-minimal solution of f on K and c 0 Y{0}.

On the other hand, by assuming that (X,d) is a complete metric space, Y is a locally convex Hausdorff space and CY is a normal cone, Isac [16] proved that for ε>0 and x X satisfying mild conditions, there exists λ>0 and x X such that

  1. (i)

    f( x ) C f( x ),

  2. (ii)

    d( x , x )λ,

  3. (iii)

    f(x)f( x )+ε/λd( x ,x) c 0 C 0, xX{ x },

where c 0 C{0}.

Recently, there have been many new formulation cases of EVP in [13, 6, 7]. In 2007, a generalization of the Ekeland-type variational principle for vector valued functions in the setting of complete quasi-metric spaces with ω-distance was introduced by Ansari [2]. Let (X,d) be a complete quasi-metric space, C be a proper, closed and convex cone in a locally convex Hausdorff topological vector space Y. F:X×XY satisfies mild conditions. For every ε>0 and x 0 X, there exists x ¯ X such that

  1. (i)

    F( x 0 , x ¯ )+εω( x 0 , x ¯ )eC,

  2. (ii)

    F( x ¯ ,x)+εω( x ¯ ,x)eC, for all xX, x x ¯ ,

where eintC.

By an approach similar to [2], Araya et al. [3] obtained a vectorial version of Ekeland’s variational principle related to equilibrium problem. In 2008, Al-Homidan et al. [1] established Ekeland-type variational principles in the setting of quasi-metric spaces with a Q-function. Recently, Bednarczuk and Zagrodny [6] introduced an Ekeland-type vector variational principle for monotonically semicontinuous map**s with perturbations given by a convex bounded subset of directions multiplied by the distance function, and they proved EVP for vector-valued map**s by combining topological and set-theoretic methods. Very recently, Khanh and Quy [19] have proposed a very weak type of generalized distances and used it to weaken the assumptions about lower semicontinuity in the existing versions of Ekeland’s variational principle on the complete metric space: to find vX such that, for all xv

F(v)F(x)+p(v,x) k 0 +K,

where K is a convex cone in the Hausdorff locally convex space Y, F:X 2 Y , p is a weak τ-function and k 0 (KclK).

Motivated by the above mentioned works, we establish a vectorial form of Ekeland-type variational principle for multivalued bioperator whose domain is a complete metric space and its range is a subset of a locally convex Hausdorff topological space by using the set theoretic methods. We also consider Caristi-Kirk fixed point theorem in a more general setting and our techniques allow us to improve and to extend their results in [2, 6, 7].

2 Preliminaries

This section provides the preliminary terminology and notation used throughout this paper. Let (X,d) be a complete metric space, Y be a locally convex space (i.e., a linear topological space with a local base consisting of convex neighborhoods of the origin, see [15]) and K be a closed convex cone in Y. For any x,yY we define

x K yyxK.

Now, we define the concept of a ω-distance for a metric space which has been introduced by Kada et al. [18].

Definition 2.1 Let (X,d) be a metric space. A function w:X×X[0,) is called a w-distance on X if the following conditions are satisfied:

  1. (i)

    w( x 1 , x 3 )w( x 1 , x 2 )+w( x 2 , x 3 ) for any x 1 , x 2 , x 3 X;

  2. (ii)

    for any fixed xX, w(x,) is lower semi continuous;

  3. (iii)

    for any ε>0, there exists δ>0 such that w( x 3 , x 1 )δ and w( x 3 , x 2 )δ implying d( x 1 , x 2 )ε.

Definition 2.2 (See [9, 12])

Let f be a function from X to Y. It is said to be

  1. (i)

    C-bounded below if there exists yY such that f(x)y+C, for all xX;

  2. (ii)

    (D,C)-lower semicontinuous if for all rR, {xX:f(x)rDC} closed;

  3. (iii)

    (D,C)-upper semicontinuous if for all rR, {xX:f(x)rD+C} closed;

  4. (iv)

    (D,C)-continuous if it is both (D,C)-lower semicontinuous and (D,C)-upper semicontinuous;

  5. (v)

    (e,C)-lower semicontinuous if for all rR, {xX:f(x)reC} closed;

  6. (vi)

    (e,C)-upper semicontinuous if for all rR, {xX:f(x)re+C} closed;

  7. (vii)

    (e,C)-continuous if it is both (e,C)-lower semicontinuous and (e,C)-upper semicontinuous;

  8. (viii)

    C-lower semicontinuous if for all yY, {xX:f(x)yC} closed;

  9. (ix)

    C-upper semicontinuous if for all yY, {xX:f(x)y+C} closed;

  10. (x)

    C-continuous if it is both C-lower semicontinuous and C-upper semicontinuous.

Remark 2.3 It is easy to see that the C-lower (respectively upper) semicontinuity of f implies the (e,C)-lower (respectively upper) semicontinuity.

Definition 2.4 (Holmes [15])

Let X be a linear topological space over the field R.

  1. (1)

    A sequence { x n }X is bounded if λ n x n θ whenever λ n 0 in R.

  2. (2)

    A set AX is bounded if every sequence in A is bounded.

Let C be a convex cone in a linear topological space Y with intC and D a convex subset of C such that 0cl(D+C). In order to show the main results, let us give the following definition.

Definition 2.5 A generalized nonlinear scalarization function is defined by

ξ ( D , C ) (z):=inf{rR:zrDC}zY.

Remark 2.6 If D={e} with eintC, then ξ ( D , C ) Definition 2.5 reduces to the definition of the Gerstewitz function [14]

ξ e (z):=inf{rR:zreC}zY.

Lemma 2.7 For rR, we set P r =rDC. Then the following hold:

  1. (i)

    If z P r for some rR, z P μ for each μ>r.

  2. (ii)

    For each zY, there exists a real number λ such that z P λ .

  3. (iii)

    Let zY. If z P r for some rR, z P μ for each μ<r.

Proof (i) Let z P r for some rR and μ>r. We note that

μDz=(μr)D+rDzC+CC.

This implies z P μ .

  1. (ii)

    Assume there exists zY such that for all λR, z P λ . From (i), we have zλDC for all λR. Then we see that

    tDzCand(1t)DzCfor some tR.

Note that

(tDz) ( ( 1 t ) D z ) C+CC.

Since D is convex, we have

0tD+(1t)D+CD+C,

which is a contradiction to 0cl(D+C).

  1. (iii)

    Let zY and if z P r for some rR. Assume that for some μ<r, z P μ . From (i), we have z P r , a contradiction. □

Proposition 2.8 The function ξ:YR is well defined.

Proof For any zY, define

K:={rR:zrDC}.

It is sufficient to show that K is bounded from below.

Assume that for each rR, there exists lR such that l<r and zlDC.

By Lemma 2.7 (ii), there exists μR such that zμDC.

By Lemma 2.7 (iii), we have zαDC for each α<μ, a contradiction. Then K is bounded from below. □

Let us recall the basic set-theoretical concepts and tools which are used in the sequel. Let X be a nonempty set and sX×X a relation. By xsy we mean that (x,y)s and we write x s y if and only if there are finite elements x 1 ,, x n X such that

x= x 1 , x 1 s x 2 ,, x n 1 s x n , x n =y.

The relation s is said to be the transitive closure of s, and s= s if s is transitive. We say that the element xX is maximal with respect to a relation sX×X (i.e., x is s-maximal) if for every yX,

xsyy s x.

Definition 2.9 (See [13])

A set X with a relation sX×X is countably orderable with respect to s if for every nonempty subset WX there exists a well-ordered relation μ on W such that

vμwv s wfor every v,wW,vw

implies that W is at most countable.

Theorem 2.10 (See [13])

Let X be a countably orderable set by a relation sX×X. Assume that for any sequence ( x i )X satisfying

x i s x i + 1 for alliN

there are a subsequence ( x i k )( x i ) and an element x such that

x i k sxfor allkN.

Then an s -maximal element of X exists.

Moreover, if s is transitive, then there exists an s-maximal element of X.

3 Main theorem

In this section, we will present the following vectorial form of an equilibrium version of vector Ekeland’s principle in setting complete metric spaces and ω-distance.

Theorem 3.1 Let X be a complete metric space, ω:X×X[0,) be a ω-distance on X, Y be a locally convex space, C be a closed and convex cone in Y and D be a closed convex and bounded subset of C such that 0cl(D+C). Let F:X×XY be a function satisfying the following conditions:

  1. (i)

    F(x,x)=0 for all xX;

  2. (ii)

    F(x,y)+F(y,z)F(x,z)+C for every x,y,zX;

  3. (iii)

    for each xX, the function F(x,):XY is (D,C)-lower semicontinuous;

  4. (iv)

    for each fixed xX, F(x,):XY is C-bounded below.

Then for every x 0 X, there exists x ¯ X such that

  1. (i)

    F( x 0 , x ¯ )+w( x 0 , x ¯ )DC;

  2. (ii)

    F( x ¯ ,x)+w( x ¯ ,x)DC for all x x ¯ .

Proof Let rX×X be a relation defined as follows: For any x,yX,

xryF(x,y)+ω(x,y)DC.

We will first show that r is transitive. Suppose that u 1 r u 2 and u 2 r u 3 . Thus, we have

This implies that

F( u 1 , u 2 )+F( u 2 , u 3 )+ω( u 1 , u 2 )D+ω( u 2 , u 3 )DC.
(3.1)

By assumption (ii), we obtain

F( u 1 , u 3 )F( u 1 , u 2 )+F( u 2 , u 3 )C.
(3.2)

Therefore, by the convexity of D, we have

( ω ( u 1 , u 2 ) + ω ( u 2 , u 3 ) ) D=ω( u 1 , u 2 )D+ω( u 2 , u 3 )D.

Indeed, if ω( u 1 , u 2 )+ω( u 2 , u 3 )=0, we are done. If ω( u 1 , u 2 )+ω( u 2 , u 3 )>0, for d 1 , d 2 D, we have

ω ( u 1 , u 2 ) ω ( u 1 , u 2 ) + ω ( u 2 , u 3 ) d 1 + ω ( u 2 , u 3 ) ω ( u 1 , u 2 ) + ω ( u 2 , u 3 ) d 2 D.

So, we have

ω( u 1 , u 2 ) d 1 +ω( u 2 , u 3 ) d 2 ( ω ( u 1 , u 2 ) + ω ( u 2 , u 3 ) ) D.

Hence ω( u 1 , u 2 )D+ω( u 2 , u 3 )D(ω( u 1 , u 2 )+ω( u 2 , u 3 ))D, which implies that (ω( u 1 , u 2 )+ω( u 2 , u 3 ))D=ω( u 1 , u 2 )D+ω( u 2 , u 3 )D.

By the definition of ω-distance, ω( u 1 , u 3 )ω( u 1 , u 2 )+ω( u 2 , u 3 ). Therefore, there is a real number ε>0 such that

ω ( u 1 , u 3 ) D = ω ( u 1 , u 2 ) D + ω ( u 2 , u 3 ) D ε D ω ( u 1 , u 2 ) D + ω ( u 2 , u 3 ) D C .
(3.3)

From (3.1), (3.2) and (3.3), we have

F( u 1 , u 3 )+ω( u 1 , u 3 )DC.

This implies that u 1 r u 3 .

We define S:X 2 X by

S(x)= { y X : F ( x , y ) + ω ( x , y ) D C } for all xX.

It is easy to see that xS(x), and so S(x) is nonempty for all xX. By assumption (iii), we note that S(x) is a closed set for all xX. We now show that S(x) is a countably orderable set by a relation rX×X.

Let

V(x):= inf y S ( x ) ξ ( D , C ) ( F ( x , y ) ) ,

where ξ ( D , C ) (z):=inf{rR:zrDC} for all zY.

Let W be any nonempty subset of A which is well ordered by a relation s satisfying

usvu r vfor every u,vW,uv.

Then, for any u,vW with uv, we note that

usvu r vurvandS(u)S(v)

because r is transitive. Since urv, uv, thus F(u,v)+ω(u,v)DC, which implies that ξ ( D , C ) (F(u,v))ω(u,v)<0. Moreover,

V ( u ) = inf y S ( u ) ξ ( D , C ) ( F ( u , y ) ) inf y S ( v ) ξ ( D , C ) ( F ( u , y ) ) inf y S ( v ) ( ξ ( D , C ) ( F ( u , v ) ) + ξ ( D , C ) ( F ( v , y ) ) ) = ξ ( D , C ) ( F ( u , v ) ) + inf y S ( v ) ξ ( D , C ) ( F ( v , y ) ) < inf y S ( v ) ξ ( D , C ) ( F ( v , y ) ) = V ( v ) .

Thus V(W)R is well ordered by the relation “<” and hence V(W) is at most countable. Since V is one-to-one map** on W, W is at most countable.

For any xX, we let ( y n )S(x) with y n r y n + 1 for all nN. We next show that there is an element y 0 such that y n r y 0 for all nN.

In case y m = y m + 1 = y m + 2 = for some mN, we can put y 0 := y m and so we have done. Then, it is enough to consider the case i = 1 ω( y i , y i + 1 )>0. Since y n r y n + 1 for each nN, we obtain

F( y n , y n + 1 )+ω( y n , y n + 1 )DC.
(3.4)

From (3.4) and assumption (ii), we observe that

F ( y 1 , y 2 ) F ( y 1 , y m + 1 ) F ( y 2 , y 3 ) F ( y 3 , y 4 ) F ( y m , y m + 1 ) + C F ( y 1 , y m + 1 ) + ( ω ( y 2 , y 3 ) D + C ) + ( ω ( y 3 , y 4 ) D + C ) + + ( ω ( y m , y m + 1 ) D + C ) + C F ( y 1 , y m + 1 ) + i = 2 m ( ω ( y i , y i + 1 ) D ) + C ,

for all mN. Since F is C-bounded below, there exists zY such that

F( y 1 , y 2 )z+C+ i = 2 m ( ω ( y i , y i + 1 ) D ) .
(3.5)

By the convexity of D, we have

i = 1 m ( ω ( y i , y i + 1 ) D ) = ( i = 1 m ω ( y i , y i + 1 ) ) D
(3.6)

for any mN. Therefore, it follows from (3.5) and (3.6) that

F( y 1 , y 2 )z+C+ ( i = 2 m ω ( y i , y i + 1 ) ) D.

Since 0 cl(D+C), by the Separation theorem, there exists f Y such that

f , 0 <inf { f , d + c , d D , c C } .

This implies that 0<ε< f ,d+c= f ,d+ f ,c for some ε>0, and for any dD, cC. Hence inf d D f ,d>0 and f ,c ≥ 0 for any cC. Hence, for each mN, we have

f , F ( y 1 , y 2 ) = f , z + f , c + i = 2 m ω( y i , y i + 1 ) f , d

for some cC and dD. Since f ,c0 for any cC, it follows that

f , F ( y 1 , y 2 ) f , z + i = 2 m ω( y i , y i + 1 ) inf d D f , d .

Since inf d D f ,d>0, we have that i = 1 m ω( y i , y i + 1 ) is bounded above by f , F ( y 1 , y 2 ) f , z inf d D f , d . Moreover, ( i = 1 m ω( y i , y i + 1 )) is a monotone sequence then the series i = 1 ω( y i , y i + 1 ) converges. This implies that lim i ω( y i , y i + 1 )=0. It is easy to see that ( y n ) is a Cauchy sequence in S(x). By the completeness of X and closedness of S(x), ( y n ) converges to a certain y 0 S(x). Since r is transitive and y n r y n + 1 , then y n r y m for all m>n, and so y n r y 0 . This entails that S(x) satisfies the condition in Theorem 2.10. Now, the proof includes applying Theorem 2.10 to show that S(x) has an r-maximal element x ¯ S(x). Let us observe that for xX, any r-maximal element of S(x) is an r-maximal element of X. Hence, (i) holds for  x ¯ . Finally, we show that x ¯ satisfies (ii). Assume that x ¯ rz for some z x ¯ . Since r is transitive and x ¯ is r-maximal, zr x ¯ . Consequently, V( x ¯ )>V(z) and V(z)>V( x ¯ ), a contradiction. Hence x ¯ satisfies (ii). □

Remark 3.2 We see in the proof that we do not use the symmetry condition of the metric. So, the conclusion in Theorem 3.1 still holds if we replace the word ‘‘metric space’’ with ‘‘quasi-metric space’’.

By setting D={εe} for all ε>0 in Theorem 3.1, we obtain the following Corollary which is proven by Ansari [2].

Corollary 3.3 (Theorem 3.1 in [2])

Let (X,d) be a complete quasi-metric space, ω:X×X[0,) a ω-distance on X, Y be a locally convex Hausdorff topological vector space, C be a proper, closed and convex cone in Y with apex at origin and intC, and eY be a fixed vector such that eintC. Let F:X×XY be a function satisfying the following:

  1. (i)

    F(x,x)=0, for all xX;

  2. (ii)

    F(x,y)+F(y,z)F(x,z)+C for all x,y,zX;

  3. (iii)

    for each fixed xX, the function F(x,):XY is (e,C)-lower semicontinuous and C-bounded below.

Then for every ε>0 and for every x 0 X, there exists x ¯ X such that

  1. (a)

    F( x 0 , x ¯ )+εω( x 0 , x ¯ )eC,

  2. (b)

    F( x ¯ ,x)+εω( x ¯ ,x)eC, for all xX, x x ¯ .

If F(x,y)=f(y)f(x), where f:XR is lower semicontinuous and bounded below, then we have the following result.

Corollary 3.4 Let X be a complete metric space, ω:X×X[0,) be a ω-distance on X, Y be a locally convex space, C be a closed and convex cone in Y and D be a closed convex and bounded subset of C such that 0cl(D+C). Let f:XY be (D,C)-lower semicontinuous and C-bounded below. Then for every x 0 X there exists x ¯ X such that

  1. (i)

    f( x ¯ )+w( x 0 , x ¯ )Df( x 0 )C;

  2. (ii)

    f(x)+w( x ¯ ,x)Df( x ¯ )C for all x x ¯ .

We obtain that Corollary 3.4 is the extension of the following.

Corollary 3.5 Let X be a complete metric space, ω:X×X[0,) be a ω-distance on X, Y be a locally convex space, C be a closed and convex cone in Y and D be a closed convex and bounded subset of C such that 0cl(D+C). Let f:XY be (D,C)-lower semicontinuous and C-bounded below. Then for every x 0 X there exists x ¯ X such that

  1. (i)

    (f( x 0 )C)(f( x ¯ )+w( x 0 , x ¯ )D);

  2. (ii)

    (f( x ¯ )C)(f(x)+w( x ¯ ,x)D)= for all x x ¯ .

Proof By all conditions of Corollary 3.4, we have for every x 0 X there exists x ¯ X such that

(3.7)
(3.8)

From 3.7, we have (i) holds.

If (ii) were not satisfied, we would have (f( x ¯ )C)(f(x)+w( x ¯ ,x)D) for some x x ¯ . Then there are c 1 C and d 1 D such that

f( x ¯ )=f(x)+w( x ¯ ,x) d 1 + c 1 .
(3.9)

Since 0 cl(D+C), by the Separation theorem, there exists y Y such that 0<ε< y ,d+c= y ,d+ y ,c for some ε>0, dD and cC. Hence inf d D y ,d>0 and y ,c 0 for any cC.

From (3.9), we obtain that

y , f ( x ¯ ) = y , f ( x ) + w ( x ¯ , x ) d 1 + c 1 > y , f ( x ) .

Using the same method of (3.9), we conclude that y f( x ¯ )< y f(x), a contradiction. Consequently (ii) holds □

If we set Y=R, C=[0,) and D={ε} for ε>0 in Theorem 3.1, we have the following result which is a well-known Ekeland’s variational principle in a more general setting.

Corollary 3.6 Let X be a complete metric space, ω:X×X[0,) be a ω-distance on X, f:X×XR be a function satisfying the following conditions:

  1. (i)

    F(x,x)=0 for all xX;

  2. (ii)

    F(x,y)+F(y,z)F(x,z) for every x,y,zX;

  3. (iii)

    for each xX the function F(x,):XR is lower semicontinuous and bounded below.

Then for every x 0 X and ε>0, there exists x ¯ X such that

  1. (i)

    F( x 0 , x ¯ )+εω( x 0 , x ¯ )0;

  2. (ii)

    F( x ¯ ,x)+εω( x ¯ ,x)>0 for all x x ¯ .

Remark 3.7 By setting w=d and F(x,y)=f(y)f(x), where f:XR is lower semicontinuous and bounded below in Corollary 3.6, we obtain Theorem 1.1 proven by Ekeland [10, 11].

The following theorem provides the equivalence between the equilibrium version of Ekeland-type variational principle, the equilibrium problem, Caristi-Kirk type fixed point theorem and Oettli and Théra type theorem

Theorem 3.8 Let X be a complete metric space, ω:X×X[0,) be a ω-distance on X, Y be a locally convex space, C be a closed and convex cone in Y and D be a closed convex and bounded subset of C. Let T:X 2 X and F:X×XY be a function satisfying the following conditions:

  1. (i)

    F(x,x)=0 for all xX;

  2. (ii)

    F(x,y)+F(y,z)F(x,z)+C for every x,y,zX;

  3. (iii)

    for each xX, the function F(x,):XY is (D,C)-lower semicontinuous;

  4. (iv)

    for each fixed xX, F(x,):xY is C-bounded below;

  5. (v)

    for each xX, there is yX such that yTx and F(x,y)+ω(x,y)DC.

Then T has at least one fixed point, i.e., there exists xX such that xTx.

Proof By assumption (i)-(iv) applied to Theorem 3.1, there exists x ¯ X such that

F( x ¯ ,z)+w( x ¯ ,z)DCfor all z x ¯ .

On the other hand by assumption (v), there exists yT( x ¯ ) such that

F( x ¯ ,y)+w( x ¯ ,y)DC.

Then we see that x ¯ =y, and so x ¯ T( x ¯ ), that is, T has at least one fixed point. □

Remark 3.9 We set F(x,y)=f(y)f(x), D={ε}, ε>0 and replace ω-distance by d-distance in Theorem 3.8, we obtain Theorem 3.1 in [3] and Theorem 4.1 in [4] (vectorial Caristi-Kirk fixed point theorem).