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Pseudo-metric space and fixed point theorem

Abstract

The aim of this paper is to give a generalized version of Caristi fixed point theorems in pseudo-metric spaces. Our results generalize and improve many of well-known theorems. As an application of our results, we give a new existence theorem to the generalized nonlinear complementarity problem and a solution of differential inclusion in the distributions setting.

1 Introduction

It is well known that the Ekeland variational principle [1] and Caristi-Kirk fixed point theorem are both equivalent. Many authors [27] have established a generalized version of these two results in different settings, that is, in vector-valued generalized metric space with respect to a convex cone \(\mathbb{K}\) in a Banach space. Recall that a subset \(\mathbb{K} \subset\mathbb{Y}\) is called a convex cone on a topological vector space \(\mathbb{Y}\) if:

  1. 1.

    \(\mathbb{K}+\mathbb{K}\subset\mathbb{K}\);

  2. 2.

    for every \(\lambda>0\), \(\lambda\mathbb{K}\subset\mathbb{K}\);

  3. 3.

    \(\mathbb{K}\cap (-\mathbb{K} )= \{ \theta \} \), where θ denotes the zero of \(\mathbb{Y}\).

A convex cone \(\mathbb{K}\subset\mathbb{Y}\) generates a partial ordering on \(\mathbb{Y}\) (i.e. a reflexive, antisymmetric, and transitive relation) by

$$ x\preceq y\quad \Longleftrightarrow \quad y-x\in\mathbb{K} . $$

Thereby, since its appearance, the Brezis-Browder ordering principle [8] seems to be a strong tool to prove fixed point or minimal point theorems in an ordered set. Zermelo’s theorem [9] shows that there is an equivalency between the existence of a fixed point of such a map and the monotonicity of the map. By the way, Hamel [10] studied existence theorems, namely minimal point, Caristi fixed point, and Ekeland variational principle in the topological product space \(\mathbb{X}\times\mathbb{Y}\) where \(\mathbb{X}\) is a separated uniform space, and \(\mathbb{Y}\) is a topological vector space.

Fang [11] introduced the concept of ‘F-type topological spaces’ generating the topology by families of quasi-metrics and gave a generalization of Ekeland’s variational principle.

Furthermore, Isac [12] proved an interesting Caristi-type theorem in the framework of locally convex space, which led him to derive an existence result of a nonlinear equation.

Hence, the aim of this paper is to generalize some of the well-known fixed point theorems [11, 1315] for a pseudo-metric space \(\mathbb{X}\). This paper is divided into three sections after showing some basic results in preliminaries. Using in Section 3 the Brezis-Browder principle, we give generalized Caristi’s fixed point theorems for set-valued maps and derive some corollaries. Section 4 is devoted to an Ekeland-type variational principle in more applied general setting, namely pseudo-metric spaces, and also discuss the relationships of our main results. Finally, following investigations by Isac, Section 5 is devoted to applications.

2 Preliminaries

Over this section, \(\mathbb{Y}\) is a locally convex space, and \(\mathbb {K}\) is a convex cone in \(\mathbb{Y}\). A set Λ is said to be a directed set if ‘’ is a preorder and every pair of elements of Λ has an upper bound.

Definition 2.1

Let \(\mathbb{X}\) be a nonempty set, and \((\Lambda,\prec )\) a directed set. A family of cone pseudo-metrics on \(\mathbb{X}\) is a system \(\{ d_{\alpha} \} _{\alpha\in\Lambda}\) of mappings \(d_{\alpha}:\mathbb{X}\times\mathbb{X}\rightarrow\mathbb{K}\) satisfying the following conditions for each \(\alpha\in\Lambda\) and \(x,y,z\in\mathbb{X}\):

(A1):

\(\theta\preceq d_{\alpha} (x,y )\), and \(d_{\alpha} (x,x )=\theta\);

(A2):

\(d_{\alpha} (x,y )=d_{\alpha} (y,x )\);

(A3):

\(d_{\alpha} (x,z )\preceq d_{\alpha} (x,y )+d_{\alpha} (y,z )\);

(A4):

If \(\alpha\prec\beta\) then \(d_{\alpha} (x,y )\preceq d_{\beta} (x,y )\).

Then the pair \((\mathbb{X}, \{ d_{\alpha} \} _{\alpha\in \Lambda} )\) is called a cone pseudo-metric space. Additionally, if

(A5):

for all \(\alpha\in\Lambda\) and \(x,y\in\mathbb{X}\), \(d_{\alpha } (x,y )=\theta\) implies \(x=y\),

then the family of cone pseudo-metrics is said to be separating.

The concept of a cone pseudo-metric space was already defined by Włodarczyk et al. [16], who called it a Hausdorff cone pseudo-metric space. In this paper, we use a locally convex space as a target set for a cone pseudo-metric, which is more general that a normed space. If \((\mathbb{Y},\tau )\) is a locally convex space, then it is known that the topology τ can be generated by a family of seminorms \(\{ p_{i} \} _{i\in I}\) [17]. A subset B of \(\{ p_{i} \} _{i\in I}\) is called a basis for \(\{ p_{i} \} _{i\in I}\) if for every \(i\in I\), there exist \(q\in B\) and \(\lambda>0\) such that \(p_{i}\leqslant \lambda q\).

We say that a family of seminorms \(\{ p_{i} \} _{i\in I}\) is separating if \(\ker \{ p_{i} \} _{i\in I}=\{\theta\}\) or has a Hausdorff basis B if \(\ker B=\{\theta\}\), where

$$ \ker B= \bigl\{ x\in\mathbb{Y} : p (x )=0, \forall p\in B \bigr\} . $$

The most useful class of cones in topological vector space is the class of normal cones. For more details, we refer the reader to [18].

Definition 2.2

[13]

If \((\mathbb{Y}, \{ p_{i} \} _{i\in I} )\) is a locally convex space, then a convex cone \(\mathbb{K}\subset\mathbb{Y}\) is said to be normal if there exists a basis B of \(\{ p_{i} \} _{i\in I}\) such that, for each \(p\in B\) and all \(x,y\in\mathbb{K}\),

$$ \theta\preceq x\preceq y\quad \Longrightarrow\quad p (x )\leqslant p (y ) . $$

Throughout this paper, we assume that the topology defined on \(\mathbb {Y}\) is generated by the basis B [13], and we simply write \(B= \{ p_{i} \} _{i\in I}\).

Proposition 2.3

Let \((\mathbb{X}, \{ d_{\alpha} \} _{\alpha\in \Lambda} )\) be a cone pseudo-metric space over a normal cone \(\mathbb{K}\).

Then the mappings \(\delta_{\alpha i} : \mathbb{X}\times\mathbb {X}\rightarrow [0,\infty [\) defined for each \((\alpha,i ) \in\Lambda\times I\) by \(\delta_{\alpha i}=p_{i}\circ d_{\alpha}\) is a family of pseudo-metrics on \(\mathbb{X}\).

Proof

By (A1) and (A2) we have immediately \(\delta_{\alpha i} (x,x )=0\) and \(\delta_{\alpha i} (x,y )=\delta_{\alpha i} (y,x )\) for every \(x,y\in\mathbb{X}\).

Since for each \(\alpha\in\Lambda\) and all \(x,y,z\in\mathbb{X}\), we have \(d_{\alpha} (x,y )\in\mathbb{K}\) and

$$ \theta\preceq d_{\alpha} (x,z )\preceq d_{\alpha} (x,y )+d_{\alpha} (y,x ) $$

and since \(\mathbb{K}\) is a normal cone, we get, for each \(i \in I\),

$$ p_{i} \bigl(d_{\alpha} (x,z ) \bigr)\leqslant p_{i} \bigl(d_{\alpha} (x,y )+d_{\alpha} (y,x ) \bigr)\leqslant p_{i} \bigl(d_{\alpha} (x,y ) \bigr)+p_{i} \bigl(d_{\alpha} (y,x ) \bigr). $$

Then \(\delta_{\alpha i}\) satisfies the triangle inequality. If we assume that \(\{ d_{\alpha} \} _{\alpha\in\Lambda}\) is a separating family, so is \(\{ \delta_{\alpha i} \} _{ (\alpha,i ) \in\Lambda\times I}\). □

If the convex cone \(\mathbb{K}\) is solid (\(\operatorname{int} \mathbb {K}\neq\emptyset\)) and not normal and if \(\mathbb{Y}\) is a locally convex space, then the Gerstewitz functional [19] \(\xi_{e} :\mathbb{Y}\rightarrow\mathbb{R}\), where \(e\in\operatorname{int} {\mathbb{K}}\), is defined as

$$ \xi_{e} (x )=\inf \{ \lambda\in\mathbb{R}: x\in\lambda e-\mathbb{K} \} $$

for each \(x\in\mathbb{Y}\).

We have the following result.

Lemma 2.4

For all \(\lambda\in\mathbb{R}\) and \(x\in\mathbb{Y}\), we have the following statements:

  1. (i)

    \(\xi_{e} (x )\leqslant\lambda\Longleftrightarrow x\in \lambda e-\mathbb{K}\);

  2. (ii)

    \(\xi_{e} (x )>\lambda\Longleftrightarrow x\notin\lambda e-\mathbb{K}\);

  3. (iii)

    \(\xi_{e} (x )\geqslant\lambda\Longleftrightarrow x\notin \lambda e-\operatorname{int} \mathbb{K}\);

  4. (iv)

    \(\xi_{e} (x )<\lambda\Longleftrightarrow x\in\lambda e-\operatorname{int}\mathbb{K}\);

  5. (v)

    \(\xi_{e} (\cdot )\) is positively homogeneous and continuous on \(\mathbb{Y}\);

  6. (vi)

    if \(x_{1}\in x_{2}+\mathbb{K}\), then \(\xi_{e} (x_{2} )\leqslant\xi_{e} (x_{1} )\);

  7. (vii)

    \(\xi_{e} (x_{1}+x_{2} )\leqslant\xi_{e} (x_{1} )+\xi_{e} (x_{2} )\) for all \(x_{1},x_{2}\in\mathbb{Y}\).

Proof

See, for instance, [7, 2023]. □

The following result is Theorem 2.1 of Du [24].

Proposition 2.5

Let \((\mathbb{X}, \{ d_{\alpha} \} _{\alpha} )\) be a cone pseudo-metric space over a solid cone \(\mathbb{K}\). Then the family of mappings \(\delta_{\alpha} : \mathbb{X}\times\mathbb {X}\rightarrow [0,\infty [\) defined by \(\delta_{\alpha}=\xi_{e}\circ d_{\alpha}\) is a family of pseudo-metrics on \(\mathbb{X}\).

Proof

Since \(\xi_{e} (\cdot )\) is a seminorm on \(\mathbb{Y}\) by Lemma 2.4, Proposition 2.3 gives the result. □

If the cone \(\mathbb{K}\) is normal and solid, then \(\xi_{e} (\cdot )\) is a norm over \(\mathbb{Y}\), and we have the following proposition.

Proposition 2.6

If \((\mathbb{Y},\tau )\) is a Hausdorff topological space ordered by a normal solid cone \(\mathbb{K}\), then \((\mathbb{Y},\tau )\) is a normable space.

Proof

See Proposition 1.10 in [18], Chapter 2. □

Next, we discuss some convergence properties of cone pseudo-metric spaces. We note that \(x\ll y\) if and only if \(y-x \in\operatorname{int} \mathbb{K}\), where the ‘int’ is the interior.

Definition 2.7

Let \((\mathbb{X}, \{ d_{\alpha} \} _{\alpha} )\) be a cone pseudo-metric space over a solid convex cone \(\mathbb{K}\subset \mathbb{Y}\), where \(\mathbb{Y}\) is a locally convex space, \(x \in \mathbb{X}\), and \(\{ x_{n} \} _{n}\) a sequence in \(\mathbb{X}\).

  1. 1.

    \(\{ x_{n} \} _{n}\) is Cauchy sequence whenever for every \(\alpha\in\Lambda\) and \(c\in\mathbb{Y}\) with \(\theta\ll c\), there is a natural number \(N_{0}\) such that

    $$ d_{\alpha} (x_{n},x_{m} )\ll c, \quad \forall n,m \geq N_{0} . $$
  2. 2.

    \(\{ x_{n} \} _{n}\) converges to x whenever for every \(\alpha\in\Lambda\) and \(c\in\mathbb{Y}\) with \(\theta\ll c\), there is a natural number \(N_{0}\) such that

    $$ d_{\alpha} (x_{n},x )\ll c,\quad \forall n\geq N_{0} . $$
  3. 3.

    \((\mathbb{X}, \{ d_{\alpha} \} _{\alpha} )\) is complete if each Cauchy sequence converges in \(\mathbb{X}\).

Proposition 2.8

Let \((\mathbb{X}, \{ d_{\alpha} \} _{\alpha} )\) be a cone pseudo-metric space over a solid convex cone \(\mathbb{K}\subset \mathbb{Y}\), where \(\mathbb{Y}\) is a locally convex space.

Then, for each \(\alpha\in\Lambda\), we get

$$ d_{\alpha} (x_{n},x ) \longrightarrow \theta\quad\iff\quad \delta_{\alpha} (x_{n},x )=\xi_{e} \bigl( d_{\alpha} (x_{n},x ) \bigr) \longrightarrow 0 . $$

Proof

It is similar to the proof of Theorem 3.2 in [25]. □

Using this pseudo-metric \(\delta_{\alpha}\), we keep saying that \((\mathbb{X}, \{ \delta_{\alpha} \} _{\alpha} )\) is a pseudo-metric space over a solid convex cone \(\mathbb{K}\).

3 Fixed point theorems

Recall that the most famous ordering principle.

Theorem 3.1

Brezis-Browder

Let \((W,\precsim )\) be a quasi-ordered set (i.e. is a reflexive and transitive relation), and let \(\varPsi:W\longrightarrow\mathbb{R}\) be a function satisfying the following conditions:

(B1):

Ψ is bounded below;

(B2):

\(w_{1}\precsim w_{2}\Longrightarrow\varPsi (w_{1} )\leqslant\varPsi (w_{2} )\);

(B3):

For every decreasing sequence \(\{ w_{n} \} _{n\in\mathbb {N}}\subset W\) with respect to ‘, there exists \(w\in W\) such that \(w\leqslant w_{n}\) for all \(n\in\mathbb{N}\).

Then, for every \(w_{0}\in W\), there exists \(\bar{w}\in W\) such that

(i):

\(\bar{w}\precsim w_{0}\);

(ii):

\(\hat{w}\precsim\bar{w}\Longrightarrow\varPsi (\hat{w} )=\varPsi (\bar{w} )\).

In particular, if we strengthen (B2) to

(B2′):

\((w_{1}\precsim w_{2}, w_{1}\neq w_{2} )\Longrightarrow\varPsi (w_{1} )<\varPsi (w_{2} )\),

then

(ii′):

\(\hat{w}\precsim\bar{w}\Longrightarrow\hat{w}=\bar{w}\), that is, is minimal in W with respect to ‘.

Proof

See Corollary 1 in [8]. □

Now we are able to give the main result of this section.

Theorem 3.2

Let \((\mathbb{\mathbb{Y}}, \{ p_{i} \} _{i\in I} )\) a complete separated locally convex space, \((\mathbb{X}, \{ \delta_{\alpha} \} _{\alpha\in\Lambda } )\) be a complete Hausdorff pseudo-metric space over a solid convex cone \(\mathbb{K}\), \(T:\mathbb{X}\longrightarrow2^{\mathbb{X}}\) and \(S:\mathbb{X}\longrightarrow2^{\mathbb{Y}}\) two set-valued maps with nonempty values.

Suppose that, for every \((\alpha,i )\in\Lambda\times I\) and two constants \(c_{\alpha},c_{i}>0\), there exist lower semicontinuous functions \(\varphi_{\alpha i}:\mathbb{\mathbb{Y}}\longrightarrow [0,\infty )\), and for each \((x,y )\in G_{S}\), there exist \(u\in Tx\) and \(v\in Su\) such that

$$ \max \bigl\{ c_{\alpha}\delta_{\alpha} (x,u ),c_{i}p_{i} (y-v ) \bigr\} \leqslant\varphi_{\alpha i} (y )-\varphi _{\alpha i} (v ). $$
(1)

Then T has a fixed point in \(\mathbb{X}\).

Proof

Put

$$ W_{0}= \bigl\{ (x,y )\in G_{S} ; \forall (\alpha,i )\in \Lambda\times I, \max \bigl\{ c_{\alpha}\delta_{\alpha} (x_{0},x ),c_{i}p_{i} (y_{0}-y ) \bigr\} +\varphi_{\alpha i} (y )\leqslant\varphi_{\alpha i} (y_{0} ) \bigr\} $$

for some \((x_{0},y_{0} )\in G_{S}\). Then \(W_{0}\) is a nonempty closed subset of \(G_{S}\). Indeed, let \((x_{n},y_{n} )_{n}\) be a sequence in \(W_{0}\) that converges to \((x,y )\), that is, \(\lim_{n\rightarrow\infty} p_{i} (y_{n}-y )=0\). Since for each \((\alpha,i )\in\Lambda\times I\), the function \(\varphi_{\alpha i}\) is lower semicontinuous, that is,

$$ \varphi_{\alpha i} (y )\leqslant \liminf_{n\rightarrow\infty} \varphi_{\alpha i} (y_{n} ) , $$

we have

$$\begin{aligned} c_{i}p_{i} (y_{0}-y ) \leqslant& c_{i}p_{i} (y_{0}-y_{n} )+c_{i}p_{i} (y_{n}-y ) \\ \leqslant& \varphi_{\alpha i} (y_{0} )-\varphi_{\alpha i} (y_{n} )+c_{i}p_{i} (y_{n}-y ) \\ \leqslant& \varphi_{\alpha i} (y_{0} )- \liminf _{k\rightarrow\infty}\varphi_{\alpha i} (y_{k} )+c_{i}p_{i} (y_{n}-y ) \\ \leqslant& \varphi_{\alpha i} (y_{0} )-\varphi_{\alpha i} (y )+c_{i}p_{i} (y_{n}-y ). \end{aligned}$$

So, taking the limit with respect to n, we get \(c_{i}p_{i} (y_{0}-y ) \leqslant\varphi_{\alpha i} (y_{0} )-\varphi _{\alpha i} (y )\), and by similar arguments we get

$$ c_{\alpha}\delta_{\alpha} (x_{0},x )\leqslant \varphi_{\alpha i} (y_{0} )-\varphi_{\alpha i} (y ) . $$

Hence, \(\max \{ c_{\alpha}\delta_{\alpha} (x_{0},x ),c_{i}p_{i} (y_{0}-y ) \} +\varphi_{\alpha i} (y )\leqslant\varphi_{\alpha i} (y_{0} )\), so that \((x,y )\in W_{0}\).

Now we define a binary relation in \(W_{0}\) as follows: for every \((x_{1},y_{1} )\) and \((x_{2},y_{2} )\) in \(W_{0}\),

$$ (x_{1},y_{1} )\precsim (x_{2},y_{2} ) \quad \Longleftrightarrow\quad \max \bigl\{ c_{\alpha}\delta_{\alpha} (x_{1},x_{2} ),c_{i}p_{i} (y_{1}-y_{2} ) \bigr\} \leqslant \varphi_{\alpha i} (y_{2} )-\varphi_{\alpha i} (y_{1} ) $$

for each \((\alpha,i )\in\Lambda\times I\). We can show that the relation is an ordering on \(W_{0}\).

Next, we show that, for every decreasing sequence \((x_{n},y_{n} )_{n\in\mathbb{N}}\subset W_{0}\) with respect to ‘’, there exists \((x^{*},y^{*} )\in W_{0}\) such that \((x^{*},y^{*} )\precsim (x_{n},y_{n} )\) for all \(n\in\mathbb{N}\). Let \((x_{n},y_{n} )_{n\in\mathbb{N}}\) be a -decreasing sequence in \(W_{0}\). Then, for any \(m,n\in \mathbb{N}\) such that \(m\geqslant n\), we have

$$\begin{aligned}& (x_{m},y_{m} )\precsim (x_{n},y_{n} )\quad \Longleftrightarrow\quad \max \bigl\{ c_{\alpha} \delta_{\alpha} (x_{m},x_{n} ),c_{i}p_{i} (y_{m}-y_{n} ) \bigr\} \leqslant \varphi_{\alpha i} (y_{n} )-\varphi_{\alpha i} (y_{m} ) \\& \quad \mbox{for each } (\alpha,i )\in\Lambda\times I , \end{aligned}$$

which gives that the positive sequence \(\{ \varphi_{\alpha i} (y_{n} ) \} _{n}\) is decreasing (for α and i fixed). Hence, there exists \(r_{\alpha i}\) such that \(\lim\varphi_{\alpha i} (y_{n} )=r_{\alpha i}\). Let \(\varepsilon>0\) and \((\alpha,i )\in\Lambda\times I\). There exists \(N_{0}\in\mathbb{N}^{*}\) such that, for any \(n\geqslant N_{0}\), we have

$$ r_{\alpha i}\leqslant\varphi_{\alpha i} (y_{n} )\leqslant r_{\alpha i}+\min (c_{\alpha},c_{i} )\cdot\varepsilon $$

and then, for every \(m\geqslant n\geqslant N_{0}\),

$$\begin{aligned} c_{i}p_{i} (y_{m}-y_{n} ) \leqslant& \varphi_{\alpha i} (y_{n} )-\varphi_{\alpha i} (y_{m} ) \\ \leqslant& r_{\alpha i}+\min (c_{\alpha},c_{i} )\cdot \varepsilon-r_{\alpha i}. \end{aligned}$$

Thus,

$$ c_{i}p_{i} (y_{m}-y_{n} )\leqslant \min (c_{\alpha },c_{i} )\cdot\varepsilon\leqslant c_{i}\varepsilon . $$

Also, we get

$$\begin{aligned} c_{\alpha}\delta_{\alpha} (x_{m},x_{n} ) \leqslant& \varphi _{\alpha i} (y_{n} )-\varphi_{\alpha i} (y_{m} ) \\ \leqslant& r_{\alpha i}+\min (c_{\alpha},c_{i} )\cdot \varepsilon-r_{\alpha i} \end{aligned}$$

and thus

$$ c_{\alpha}\delta_{\alpha} (x_{m},x_{n} ) \leqslant c_{\alpha }\varepsilon . $$

Repeating the last computation for every \((\alpha,i )\in \Lambda\times I\) and using the fact that \(\{ \delta_{\alpha} \} _{\alpha\in \Lambda}\) and \(\{ p_{i} \} _{i\in I}\) are separated families, we obtain that \(\{ x_{n} \} _{n}\) and \(\{ y_{n} \} _{n}\) are Cauchy sequences in the complete spaces \(\mathbb{X}\) and \(\mathbb{Y}\), respectively. Therefore, there exist \(x^{*}\in\mathbb{X}\) and \(y^{*}\in\mathbb{Y}\) such that

$$ x_{n} \longrightarrow x^{*}\quad \mbox{and}\quad y_{n} \longrightarrow y^{*} . $$

Since \(W_{0}\) is closed, we have that \((x^{*},y^{*} )\in W_{0}\) and \(y^{*}\in Sx^{*}\) by the definition of \(W_{0}\).

Also, for all \((n,m)\in\mathbb{N}^{2}\) such that \(m\geqslant n\), we have \((x_{m},y_{m} )\precsim (x_{n},y_{n} )\), so that for all \((\alpha,i )\in\Lambda\times I\),

$$\begin{aligned} \max \bigl\{ c_{\alpha}\delta_{\alpha} (x_{m},x_{n} ),c_{i}p_{i} (y_{m}-y_{n} ) \bigr\} \leqslant& \varphi_{\alpha i} (y_{n} )-\varphi_{\alpha i} (y_{m} ) \\ \leqslant& \varphi_{\alpha i} (y_{n} )-\liminf _{k\rightarrow\infty}\varphi_{\alpha i} (y_{k} ) \\ \leqslant& \varphi_{\alpha i} (y_{n} )-\varphi_{\alpha i} \bigl(y^{*} \bigr). \end{aligned}$$

Taking the limit with respect to m and using the fact that \(\delta_{\alpha}\) and \(p_{i}\) are continuous, we get

$$ \max \bigl\{ c_{\alpha}\delta_{\alpha} \bigl(x^{*},x_{n} \bigr),c_{i}p_{i} \bigl(y^{*}-y_{n} \bigr) \bigr\} \leqslant\varphi_{\alpha i} (y_{n} )-\varphi_{\alpha i} \bigl(y^{*} \bigr)\quad \mbox{for all } (\alpha,i )\in\Lambda\times I. $$

Thus, for each \(n\in\mathbb{N}\),

$$ \bigl(x^{*},y^{*} \bigr)\precsim (x_{n},y_{n} ) . $$

Let \((\alpha,i )\in\Lambda\times I\) be fixed and choose \(\varPsi:W_{0}\longrightarrow\mathbb{R}\) as follows: \(\varPsi (x,y )=\varphi_{\alpha i} (y )\) for each \((x,y )\in W_{0}\). Condition (B1) from Theorem 3.1 holds since \(\varphi_{\alpha i} (y )\geq0\). We also have

$$ (x_{1},y_{1} )\precsim (x_{2},y_{2} ) \quad \Longrightarrow\quad \varphi_{\alpha i} (y_{1} )\leqslant \varphi_{\alpha i} (y_{2} )\quad \mbox{for each } (\alpha,i )\in \Lambda\times I. $$

So \(\varPsi (x_{1},y_{1} )\leqslant\varPsi (x_{2},y_{2} )\), and thus (B2) also holds. Then all assumptions of the Brezis-Browder principle are satisfied. Hence, for each \((x_{0},y_{0} )\in W_{0}\), there exists \((\bar{x},\bar{y} )\in W_{0}\) such that:

  1. (i)

    \((\bar{x},\bar{y} )\precsim (x_{0},y_{0} )\);

  2. (ii)

    if \((\hat{x},\hat{y} )\precsim (\bar{x},\bar{y} )\), then \(\varPsi (\hat{x},\hat{y} )=\varPsi (\bar{x},\bar {y} )\).

We claim that is a fixed point for T. For this \((\bar {x},\bar{y} )\in W_{0} \subset G_{S}\), there exists \((u,v )\in\mathbb{X}\times\mathbb{Y}\) such that \(u\in T\bar{x}\) and \(v\in S\bar{u}\) satisfy the following inequality for each \((\alpha,i )\in \Lambda\times I\):

$$ \max \bigl\{ c_{\alpha}\delta_{\alpha} (u,\bar{x} ),c_{i}p_{i} (v-\bar{y} ) \bigr\} \leqslant \varphi_{\alpha i} (\bar{y} )-\varphi_{\alpha i} (v ) . $$

Given \((u,v )\precsim (\bar{x},\bar{y} )\), we have \(\varPsi (u,v )=\varPsi (\bar{x},\bar{y} )\); hence, \(x=\bar{x}\), and thus \(\bar{x}\in T\bar{x}\), which completes the proof. □

Theorem 3.3

Under the hypotheses of Theorem  3.2, suppose that the condition ‘for each \((x,y )\in G_{S}\), there exist \(u\in Tx\) and \(v\in Su\) ’ is replaced by ‘for each \((x,y )\in G_{S}\) and for every \(u\in Tx\), there exists \(v\in Su\) .

Then T has a critical point, that is, there exists \(\bar{x}\in\mathbb{X}\) such that \(\{ \bar{x} \} =T\bar{x}\).

Proof

By Theorem 3.2, T has a fixed point in \(\mathbb{X}\). We claim that it is a critical point. For this, let us show that assumption (B2′) of Brezis-Browder holds, and so we have (ii′). Let \((\alpha ,i )\in\Lambda\times I\) be fixed and choose \(\varPsi:W_{0}\longrightarrow\mathbb{R}\) as in the above proof: \(\varPsi (x,y )=\varphi_{\alpha i} (y )\) for each \((x,y )\in W_{0}\). Then

$$ (x_{1},y_{1} )\precsim (x_{2},y_{2} ), \quad (x_{1},y_{1} )\neq (x_{2},y_{2} ) \quad \Longrightarrow\quad \varPsi (x_{1},y_{1} )< \varPsi (x_{2},y_{2} ) . $$

Indeed, suppose that \(x_{1}\neq x_{2}\). Then, for each \(\alpha\in \Lambda\), we get

$$ \delta_{\alpha} (x_{1},x_{2} )\neq0\quad \implies \quad \delta_{\alpha } (x_{1},x_{2} )>0 . $$

Then

$$ 0< c_{\alpha}\delta_{\alpha} (x_{1},x_{2} ) \leqslant\varphi _{\alpha i} (y_{2} )-\varphi_{\alpha i} (y_{1} ) , $$

and hence \(\varphi_{\alpha i} (y_{1} )<\varphi_{\alpha i} (y_{2} )\Longleftrightarrow\varPsi (x_{1},y_{1} )<\varPsi (x_{2},y_{2} )\).

Otherwise, if \(x_{1}=x_{2}\), then by the assumption \((x_{1},y_{1} )\neq (x_{2},y_{2} )\) we must have \(y_{1}\neq y_{2}\), and then \(\varphi_{\alpha i} (y_{1} )<\varphi_{\alpha i} (y_{2} )\). Therefore, assumption (B2′) in Theorem 3.1 is satisfied. Then \((\bar{x},\bar{y} )\) is minimal point in \(W_{0}\) by (ii′) of the Brezis-Browder principle.

Now we claim that is a critical point for T. By inequality (1) we have

$$ \max \bigl\{ c_{\alpha}\delta_{\alpha} (u,\bar{x} ),c_{i}p_{i} (v-\bar{y} ) \bigr\} \leqslant \varphi_{\alpha i} (\bar{y} )-\varphi_{\alpha i} (v ) $$

for each \(u\in T\bar{x}\) and \((\alpha,i )\in\Lambda\times I\), and then \((u,v )\precsim (\bar{x},\bar{y} )\). Since \((\bar{x},\bar{y} )\) is a minimal point in \(W_{0}\), it follows that \(u=\bar{x}\), and thus \(T\bar{x}= \{ \bar{x} \} \), which completes the proof. □

By the same process as before we can also get the same results if we replace the cone pseudo-distance \(\{ \delta_{\alpha} \} _{\alpha\in\Lambda}\) with respect to the solid cone with the real-valued pseudo-distance \(\{ d_{\alpha} \}_{\alpha\in \Lambda}\).

Proposition 3.4

Let \((\mathbb{X}, \{ d _{\alpha} \} _{\alpha\in\Lambda } )\) be a complete Hausdorff pseudo-metric space, \((\mathbb{\mathbb {Y}}, \{ p_{i} \} _{i\in I} )\) a complete separated locally convex space, and \(T:\mathbb {X}\longrightarrow2^{\mathbb{X}}\) and \(S:\mathbb{X}\longrightarrow2^{\mathbb{Y}}\) two set-valued maps with nonempty values.

Suppose that, for every \((\alpha,i )\in\Lambda\times I\) and two constants \(c_{\alpha},c_{i}>0\), there exist lower semicontinuous functions \(\varphi_{\alpha i}:\mathbb{\mathbb{Y}}\longrightarrow [0,\infty )\) and, for each \((x,y )\in G_{S}\), there exist \(u\in Tx\) and \(v\in Su\) (resp., for every \(u\in Tx\), there exists \(v\in Su\)) such that:

$$ \max \bigl\{ c_{\alpha}d_{\alpha} (x,u ),c_{i}p_{i} (y-v ) \bigr\} \leqslant\varphi_{\alpha i} (y )-\varphi_{\alpha i} (v ). $$
(2)

Then T has a fixed point (resp. critical point) in \(\mathbb{X}\).

If the set-valued map S in Proposition 3.4 is only a single-valued map, then we have the following:

Corollary 3.5

Isac [12]

Let \((\mathbb{X}, \{ p_{\alpha} \} _{\alpha\in\Lambda } )\) be a Hausdorff locally convex space, and \(M\subset\mathbb{X}\) be a nonempty set. The set-valued map \(T:\mathbb{X}\longrightarrow 2^{\mathbb{X}}\) has a critical point if and only if there exist a complete Hausdorff locally convex space \((\mathbb{Y}, \{ q_{i} \} _{i\in I} )\), a subset \(M_{0}\subseteq M\), \(S:M_{0}\longrightarrow\mathbb{Y}\), for every couple \((\alpha,i )\in\Lambda \times I\), a function \(\varphi_{\alpha i}:\overline{S (M_{0} )}\longrightarrow [0,\infty )\), and two constants \(c_{\alpha},c_{i}>0\) such that:

  1. (i)

    \(T (M_{0} )\subset M_{0}\), and \(M_{0} \subset M\) is closed;

  2. (ii)

    S is closed, and \(\overline{S (M_{0} )}\) is complete;

  3. (iii)

    \(\varphi_{\alpha i}\) is lower semicontinuous for each \((\alpha,i )\in\Lambda \times I\);

  4. (iv)

    \(\max \{ c_{\alpha}p_{\alpha} (x-y ),c_{i}q_{i} (S (x )-S (y ) ) \} \leqslant\varphi _{\alpha i} (S (x ) )-\varphi_{\alpha i} (S (y ) )\) for all \(x\in M_{0}\) and all \(y\in Tx\).

Proof

If T has a critical point \(\bar{x}\in M\), then the assumptions of Isac’s theorem are satisfied if we put \(M_{0}= \{ \bar {x} \}\), \(\mathbb{X}=\mathbb{Y}\), \(\{ p_{\alpha} \} _{\alpha\in\Lambda}= \{ q_{i} \} _{i\in I}\), \(S=I_{M_{0}}\), and for each \((\alpha,i )\in\Lambda\times I \), \(c_{\alpha }=c_{i}=1\) and \(\varphi_{\alpha i}=0\).

Conversely, \(\{ p_{\alpha} \} _{\alpha\in\Lambda}\) is generating family of separated seminorms on \(\mathbb{X}\), and if we set

$$ p_{\alpha} (x-y )=d_{\alpha} (x,y ) $$

for each \(\alpha\in\Lambda\), then \((M_{0}, \{ d_{\alpha} \} _{\alpha\in\Lambda} )\) is a complete Hausdorff pseudo-metric subspace of \(\mathbb{X}\). Also, by (ii) we get that \((\overline {S (M_{0} )}, \{ q_{i} \} _{i\in I} )\) is a complete Hausdorff locally convex subspace of \(\mathbb{Y}\), and since \(T (M_{0} )\subset M_{0}\), all assumptions of Proposition 3.4 are satisfied, so that we get the result. □

Remark 3.6

Our main result does not involve any assumptions about closeness of intermediary set-valued map S, contrary to the result of Isac [12].

Corollary 3.7

Fang [11]

Let \(T:\mathbb{X}\longrightarrow\mathbb{X}\) be a map of a complete Hausdorff locally convex space \((\mathbb{X}, \{ p_{\alpha} \} _{\alpha\in\Lambda} )\). Suppose that there exists a lower semicontinuous function \(\varphi :\mathbb{X}\longrightarrow [0,\infty )\) such that, for each \(x\in\mathbb{X}\) and for each \(\alpha\in\Lambda\),

$$ p_{\alpha} (x-Tx )\leqslant\varphi (x )-\varphi (Tx ). $$
(3)

Then T has a fixed point.

Proof

For every \(x,y\in\mathbb{X}\), we even replace \(p_{\alpha} (x-y )=d _{\alpha} (x,y )\) and take single-valued maps \(T'\) and S with \(Sx=\{x\}\) and \(T'x=\{Tx\}\) for all \(x\in\mathbb{X}\). Then inequality (3) implies inequality (2) of Proposition 3.4, and the result follows. □

We get the next obvious two corollaries.

Corollary 3.8

Downing and Kirk [15]

Let \(\mathbb{X}\) and \(\mathbb{Y}\) be complete metric spaces, and \(T:\mathbb{X}\longrightarrow\mathbb{X}\) an arbitrary mapping. Suppose that there exist a closed mapping \(S:\mathbb{X}\longrightarrow\mathbb{Y}\), a lower semicontinuous mapping \(\varphi:S (\mathbb{X} )\longrightarrow [0,\infty )\), and a constant \(c>0\) such that, for each \(x\in\mathbb{X}\),

$$ \max \bigl\{ d_{\mathbb{X}} (x,Tx ),cd_{\mathbb{Y}} \bigl(S (x ),S (Tx ) \bigr) \bigr\} \leqslant\varphi \bigl(S (x ) \bigr)-\varphi \bigl(S (Tx ) \bigr) . $$

Then there exists \(x\in\mathbb{X}\) such that \(Tx=x\).

Corollary 3.9

Caristi [14]

Let \((\mathbb{X},d )\) be a complete metric space, and let \(\varphi:\mathbb{X}\longrightarrow [0,\infty )\) be a lower semicontinuous function. If a mapping \(T:\mathbb {X}\longrightarrow\mathbb{X}\) satisfies for each \(x\in\mathbb{X}\) the condition

$$ d (x,Tx )\leqslant\varphi (x )-\varphi (Tx ) , $$

then T has a fixed point in \(\mathbb{X}\).

We conclude this section with an application of Theorem 3.2.

Theorem 3.10

Let \((\mathbb{Y}, \{ p_{i} \} _{i\in I} )\) be a complete separated locally convex space, \((\mathbb{X}, \{ \delta_{\alpha} \} _{\alpha\in\Lambda } )\) be a complete Hausdorff pseudo-metric space over a solid cone \(\mathbb {K}\), \(S:\mathbb{X}\longrightarrow2^{\mathbb{Y}}\) be set-valued map, and for every \((\alpha,i )\in\Lambda \times I\), \(\varphi_{\alpha i}:\mathbb{\mathbb{Y}}\longrightarrow [0,\infty )\) be lower semicontinuous function.

Suppose that, for each \((x,y )\in G_{S}\), there exists \((x_{0},y_{0} )\in G_{S}\) such that

  1. 1.

    \(x_{0}\neq x\);

  2. 2.

    \(\varphi_{\alpha i} (y_{0} )+\max \{ c_{\alpha}\delta_{\alpha} (x,x_{0} ),c_{i}p_{i} (y-y_{0} ) \} \leqslant\varphi_{\alpha i} (y )\) for every \((\alpha,i )\in\Lambda\times I\).

Then there exist \((\bar{x},\bar{y} )\in G_{S}\) and \((\alpha_{0},i_{0} )\in\Lambda\times I\) such that \(\varphi_{\alpha _{0} i_{0}} (\bar{y} )=\inf_{t\in\mathbb{Y}}\varphi _{\alpha_{0} i_{0}} (t )\).

Proof

By contradiction suppose that, for each \((x,y )\in G_{S}\) and for every \((\alpha,i )\in\Lambda\times I\), we have

$$ \varphi_{\alpha i} (y )>\inf_{t\in\mathbb{Y}}\varphi _{\alpha i} (t ) . $$

By assumptions, there exists \((x_{0},y_{0} )\in G_{S}\) such that 1 and 2 hold. Set

$$\begin{aligned} E (x,y ) =& \bigl\{ (z,t )\in G_{S}:z\neq x, \mbox{and } \forall ( \alpha,i )\in\Lambda\times I, \\ &\varphi_{\alpha i} (t )+\max \bigl\{ c_{\alpha}\delta_{\alpha} (x,z ),c_{i}p_{i} (y-t ) \bigr\} \leqslant\varphi_{\alpha i} (y ) \bigr\} . \end{aligned}$$

For all \((x,y )\in G_{S}\), we have \((x_{0},y_{0} )\in E (x,y )\) and \((x,y )\notin E (x,y )\). For all \(x\in\mathbb{X} \), we put \(G_{S}(x)=\{y\in\mathbb{Y} : (x,y )\in G_{S}\}\). Define the set-valued map T by

$$ Tx=\bigcup_{y\in G_{S}(x)} \bigl\{ z\in\mathbb{X} : \exists t \in Sz \mbox{ such that } (z,t )\in E (x,y ) \bigr\} $$

for \(x\in\mathbb{X}\). For all \((x,y )\in G_{S}\) and \((\alpha,i )\in\Lambda \times I\), there exist \(z\in Tx\) and \(t\in Sz\) such that

$$ \max \bigl\{ c_{\alpha}\delta_{\alpha} (x,z ),c_{i}p_{i} (y-t ) \bigr\} \leqslant\varphi_{\alpha i} (y )-\varphi _{\alpha i} (t ) . $$

Then by Theorem 3.2, T admits a point such that \(\bar{x}\in T\bar{x}\). For this , we get that, for some \(\bar{y}_{1},\bar{y}_{2}\in\mathbb{Y}\), \((\bar {x},\bar{y}_{1} )\in E (\bar{x},\bar{y}_{2} )\), which is absurd. □

4 Variational principle

Theorem 4.1

Let \((\mathbb{Y}, \{ p_{i} \} _{i\in I} )\) be a complete separated locally convex space, \((\mathbb{X}, \{ \delta_{\alpha} \} _{\alpha\in\Lambda } )\) be a complete Hausdorff pseudo-metric space over a solid cone \(\mathbb {K}\), \(S:\mathbb{X}\longrightarrow2^{\mathbb{Y}}\) be a set-valued map, and, for every \((\alpha,i )\in\Lambda \times I\), \(\varphi_{\alpha i}:\mathbb{\mathbb{Y}}\longrightarrow [0,\infty )\) be a lower semicontinuous function.

Then, for each \(\varepsilon>0\) and \((x_{0},y_{0} )\in G_{S}\) satisfying

$$ \varphi_{\alpha i} (y_{0} )\leqslant\inf\varphi_{\alpha i}+ \varepsilon, \quad \forall (\alpha,i )\in\Lambda\times I , $$

there exists \((\bar{x},\bar{y} )\in G_{S}\) such that:

  1. (i)

    for each \((\alpha,i )\in\Lambda\times I\), \(\varphi _{\alpha i} (\bar{y} )\leqslant\varphi_{\alpha i} (y_{0} )\);

  2. (ii)

    for each \((x,y )\in G_{S}\) with \(x\neq\bar{x}\), there exist \((\alpha,i )\in\Lambda\times I\) and two constants \(c_{\alpha},c_{i}>0\) such that

    $$ \varphi_{\alpha i} (\bar{y} )< \varphi_{\alpha i} (y )+\varepsilon\max \bigl\{ c_{\alpha}\delta_{\alpha} (x,\bar{x} ),c_{i}p_{i} (y-\bar{y} ) \bigr\} . $$

Proof

Let \(\varepsilon>0\) and \((x_{0},y_{0} )\in G_{S}\). Put

$$ W_{0}= \bigl\{ (x,y )\in G_{S}; \forall (\alpha,i )\in \Lambda\times I, \varphi_{\alpha i} (y )+\varepsilon\max \bigl\{ c_{\alpha}\delta_{\alpha} (x,x_{0} ),c_{i}p_{i} (y-y_{0} ) \bigr\} \leqslant\varphi_{\alpha i} (y_{0} ) \bigr\} . $$

It is a nonempty and closed subset of \(G_{S}\) since the family \(\{ \varphi_{\alpha i} \}_{\alpha i} \) is lower semicontinuous.

For all \(x\in\mathbb{X} \), we put \(W_{0}(x)=\{y\in\mathbb{Y} : (x,y )\in W_{0}\}\). Next, we define the set-valued map \(T:\mathbb{X}\longrightarrow 2^{\mathbb{X}}\) by

$$\begin{aligned} Tx =&\bigcup_{y\in W_{0}(x)} \bigl\{ \hat{x}\in\mathbb{X}; \exists\hat{y}\in S\hat{x}, \forall (\alpha,i )\in\Lambda\times I , \\ & \varphi_{\alpha i} (\hat{y} )+\varepsilon\max \bigl\{ c_{\alpha} \delta_{\alpha } (\hat{x},x ),c_{i}p_{i} (\hat{y}-y ) \bigr\} \leqslant\varphi_{\alpha i} (y ) \bigr\} . \end{aligned}$$

Obviously, T satisfies inequality (1) of Theorem 3.2 with \(\phi_{\alpha i}=\frac{1}{\varepsilon}\varphi_{\alpha i}\) so that T has a fixed point, that is, there exists \((\bar {x},\bar{y} )\in W_{0}\) such that \(\bar{x}\in T\bar {x}\) with

$$ (\bar{x},\bar{y} )\in W_{0}\quad \Longrightarrow\quad \varphi _{\alpha i} (\bar{y} )\leqslant\varphi_{\alpha i} (y_{0} ) , $$

and if \((\hat{x},\hat{y} )\in G_{S}\) with \((\hat{x},\hat {y} )\precsim (\bar{x},\bar{y} )\), then \(\hat {x}=\bar{x}\), which is equivalent to the assertion that, for each \((x,y )\in G_{S}\) with \(x\neq\bar{x}\), there exist \((\alpha,i )\in\Lambda\times I\) and two constants \(c_{\alpha},c_{i}>0\) such that

$$ \varphi_{\alpha i} (\bar{y} )< \varphi_{\alpha i} (y )+\varepsilon\max \bigl\{ c_{\alpha}\delta_{\alpha} (x,\bar{x} ),c_{i}p_{i} (y-\bar{y} ) \bigr\} . $$

The proof is complete. □

Remark 4.2

We claim that Theorem 4.1 implies Theorem 3.2. Indeed, let \((x_{0},y_{0} )\in G_{S}\) be given and take \(\varepsilon=1\). By Theorem 4.1 there exists \((\bar{x},\bar{y} )\in G_{S}\) such that assertions (i) and (ii) hold. Since (i), we have \((\bar {x},\bar{y} )\in W_{0}\). We claim that is a fixed point of T. Assuming the contrary, by inequality (1) we get the existence of some \((x,y )\in G_{S}\) such that \(x\in T\bar{x}\), \(x\neq\bar{x}\), and

$$ \max \bigl\{ c_{\alpha}\delta_{\alpha} (x,\bar{x} ),c_{i}p_{i} (y-\bar{y} ) \bigr\} \leqslant \varphi_{\alpha i} (\bar{y} )-\varphi_{\alpha i} (y ) \quad \mbox{for every } (\alpha,i )\in\Lambda\times I . $$

This contradicts (ii). Hence, is a fixed point.

The above considerations show that Theorem 4.1 and Theorem 3.2 are equivalent.

Since the Caristi theorem (Corollary 3.9) is a particular case of our main result and the Ekeland variational principle is equivalent to Caristi’s theorem, Theorem 4.1 is a generalization of the variational principle of Ekeland:

Corollary 4.3

Ekeland [1]

Let \((\mathbb{X},d )\) be a complete metric space, and \(\varphi:\mathbb{X}\longrightarrow [0,\infty )\) be a lower semicontinuous function. Let \(\varepsilon>0\), and let a point \(u\in\mathbb{X}\) be such that \(\varphi (u )\leqslant\inf\varphi +\varepsilon\). Then there exists a point \(v\in\mathbb{X}\) such that:

  1. (i)

    \(\varphi (v )\leqslant\varphi (u )\);

  2. (ii)

    \(\varphi (v )<\varphi (w )+\varepsilon d (w;v )\) for any \(w\in\mathbb{X}\); \(w\neq v\).

5 Applications

In this section, we propose two applications.

5.1 General nonlinear complementarity problem

In a Hilbert space \((\mathbb{X},\langle\cdot,\cdot\rangle )\), the dual cone \(\mathbb{K}'\) of a convex cone \(\mathbb{K}\) with respect to the duality \(\langle\mathbb{X}^{\prime},\mathbb{X}\rangle\) is defined by

$$ \mathbb{K}'= \bigl\{ y\in\mathbb{X}:\langle y,x\rangle\geqslant 0, \forall x\in\mathbb{K} \bigr\} , $$

and the polar of \(\mathbb{K}\) is \(\mathbb{K}^{0}=-\mathbb{K}'\).

Next, we suppose that \(\mathbb{K}\) is a closed convex cone in \(\mathbb{X}\). It is shown in [26] that the projection operator onto \(\mathbb{K}\), denoted by \(P_{\mathbb{K}}\), is well defined and satisfies, for all \(x\in\mathbb {X}\),

$$ \bigl\lVert x - P_{\mathbb{K}} (x ) \bigr\rVert =\min_{y\in\mathbb {K}} \lVert x - y \rVert . $$

The next two results can be found in [26].

Theorem 5.1

For every \(x\in\mathbb{X}\), \(P_{\mathbb{K}}\) has the following properties:

  1. 1.

    \(\langle P_{\mathbb{K}} (x )-x,y\rangle\geq0\) for every \(y\in\mathbb{K}\);

  2. 2.

    \(\langle P_{\mathbb{K}} (x )-x, P_{\mathbb{K}} (x ) \rangle= 0\).

Theorem 5.2

For all \(x,y,z\in\mathbb{X}\), the following statements are equivalent:

  1. 1.

    \(z=x+y\), \(x\in\mathbb{K}\), \(y\in\mathbb{K}^{0}\), and \(\langle x,y\rangle=0\);

  2. 2.

    \(x= P_{\mathbb{K}} (z )\) and \(y= P_{\mathbb {K}^{0}} (z )\).

Following Isac [26, 27], we give a new application of our main result to the so called general nonlinear complementarity problem (GNCP).

Let \(S:\mathbb{K} \rightarrow2^{\mathbb{X}}\) be a set-valued mapping. As is known [28], the GNCP with S and \(\mathbb{K}\), denoted by \(\operatorname{GNCP} (S,\mathbb{K} )\), is

$$ \operatorname{GNCP} (S,\mathbb{K} ) \mbox{:}\quad \textstyle\begin{cases} \mbox{find } (\hat{x},\hat{y} )\in\mathbb {K}\times\mathbb{X} \\ \mbox{s.t. } \hat{y}\in S (\hat{x} )\cap\mathbb{K}' \mbox{ and } \langle\hat{x},\hat{y}\rangle=0. \end{cases} $$

Before we obtain some existence results for \(\operatorname{GNCP} (S,\mathbb {K} )\) by using existence results obtained in the previous sections, we give a useful theorem, which improves Theorem 4 in [26].

Theorem 5.3

The problem \(\operatorname{GNCP} (S,\mathbb{K} )\) has a solution if and only if the set-valued map defined, for all \(x\in \mathbb{X}\), by

$$ Tx= \bigl\{ z\in\mathbb{X}, z\in P_{\mathbb{K}} (x ) - S \bigl(P_{\mathbb{K}} (x ) \bigr) \bigr\} $$

has a fixed point in \(\mathbb{X}\). Moreover, if \(x_{0}\) is a fixed point of T, then \(\hat{x}=P_{\mathbb{K}} (x_{0} )\) is a solution of the problem \(\operatorname{GNCP} (S,\mathbb{K} )\).

Proof

Suppose that T has a fixed point \(x_{0}\), that is,

$$ x_{0}\in P_{\mathbb{K}} (x_{0} ) - S \bigl(P_{\mathbb{K}} (x_{0} ) \bigr) . $$

Then there exists \(\hat{y}\in S (P_{\mathbb{K}} (x_{0} ) )\) such that

$$ x_{0}= P_{\mathbb{K}} (x_{0} )-\hat{y} . $$

Then if we denote by \(\hat{x}=P_{\mathbb{K}} (x_{0} )\), then it is clear that \(\hat{x}\in\mathbb{K}\), and by item 1 of Theorem 5.1 we get for all \(x\in\mathbb{K}\),

$$ \langle\hat{y},x\rangle=\langle\hat{x}-x_{0},x\rangle\geq0 , $$

then \(\hat{y}\in\mathbb{K}'\). Therefore, by item 2 of Theorem 5.1 \(\langle\hat{y},\hat{x}\rangle=\langle\hat{x}-x_{0},\hat {x}\rangle=0\), which implies that \((\hat{x},\hat{y} )\) is a solution of \(\operatorname{GNCP} (S,\mathbb{K} )\).

Conversely, if \((\hat{x},\hat{y} )\) is a solution of \(\operatorname {GNCP} (S,\mathbb{K} )\), then denoting

$$ x_{0}=\hat{x}-\hat{y} , $$

by Theorem 5.2 we get \(\hat{x}=P_{\mathbb{K}} (x_{0} )\), and since \(\hat{y}\in S (\hat{x} )\cap\mathbb{K}'\), we get \(\hat {y}\in S (P_{\mathbb{K}} (x_{0} ) )\). Hence, \(x_{0}\in P_{\mathbb{K}} (x_{0} )-S (P_{\mathbb{K}} (x_{0} ) )\), and thus \(x_{0}\in Tx_{0}\). This completes the proof. □

Now we formulate an existence result for the \(\operatorname{GNCP} (S,\mathbb {K} )\) problem.

Theorem 5.4

Let \((\mathbb{X},\langle\cdot,\cdot\rangle )\) be a Hilbert space, and \(\mathbb{K}\) be a closed convex cone in \(\mathbb{X}\). Let \(\{\varphi_{i} \}_{i\in I}\) be a family of lower semicontinuous functions from \(\mathbb{X}\) to \(\mathbb{R}_{+}\), and \(a_{i}>0\) and \(b_{i}>0\) be two families of positive real numbers. Suppose that the set-valued maps T and S defined before satisfy the supplementary condition:

For all \(i\in I\) and \((x,y )\in G_{S}\), there exist \(z\in Tx\cap\mathbb{K}\) and \(t\in S (z )\) such that

$$ \max \bigl\{ a_{i}\lVert x-z \rVert_{\mathbb{X}} ,b_{i}\lVert y-t\rVert _{\mathbb{X}} \bigr\} \leqslant \varphi_{i} (y )-\varphi_{i} (t ) . $$

Then \(\operatorname{GNCP} (S,\mathbb{K} )\) has a solution.

Proof

It suffices to replace T by \(T^{\prime}\) defined from \(\mathbb{K}\) into \(2^{\mathbb{K}}\) as \(T^{\prime} (x )=T (x )\cap \mathbb{K}\) and apply Theorem 5.3 and Proposition 3.4. □

Example 5.5

Let \(\mathbb{X}=\mathbb{R}\), \(\mathbb{K}=\mathbb{R_{+}}\), and, for all \(i\in I\), \(a_{i}=b_{i}=1\), \(\varphi_{i} (x )=\lvert x\rvert\) for \(x\in\mathbb{X}\), and \(S (x )=[0,x] \) for all \(x\in\mathbb {K}\). Then the GNCP problem becomes:

$$ \operatorname{GNCP} (S,\mathbb{R}_{+} ) \mbox{:}\quad \textstyle\begin{cases} \mbox{find } (\hat{x},\hat{y} )\in\mathbb {R}_{+}\times\mathbb{R} \\ \mbox{s.t. } \hat{y}\in[0,\hat{x}] \mbox{ and } \hat{x}\hat{y}=0. \end{cases} $$

It is obvious that \(T (x )=[0,x]\) for each \((x,y )\in G_{S}\). It is clear that, for all \(x\geq0\) and \(y\in[0,x]\), we get

$$ \lvert x-y\rvert+\lvert y\rvert\leq\lvert x \rvert\quad \Leftrightarrow\quad \lvert x-y\rvert\leqslant\varphi_{i} (x )-\varphi_{i} (y ) , $$

and choosing \(z\in T (x )\) and \(t\in S (z )\), we have:

  1. 1.

    for \(x=y\), we choose \(z=0\) and \(t=0\), and then we have

    $$ \max \bigl\{ \lvert x\rvert,\lvert y\rvert \bigr\} \leqslant\varphi _{i} (y ) ; $$
  2. 2.

    for \(y< x\), we choose \(z=x-y+t\) and \(t\leq\min\{x-y,y\}\), so that \(\lvert x-z\rvert=\lvert y-t\rvert\), and then we get

    $$ \lvert y-t\rvert\leqslant\varphi_{i} (y )-\varphi_{i} (t ) . $$

Finally, by 1 and 2 we get

$$ \max \bigl\{ a_{i}\lvert x-z \rvert,b_{i}\lvert y-t\rvert \bigr\} \leqslant\varphi_{i} (y )-\varphi_{i} (t ) . $$

Then all assumptions of Theorem 5.4 hold, and hence problem \(\operatorname {GNCP} (S,\mathbb{R}_{+} )\) has a solution, and the set of solutions is

$$ \operatorname{Sol}\bigl(\operatorname{GNCP} (S,\mathbb{R}_{+} ) \bigr)=\bigl\{ ( x,0) ; x\geq0 \bigr\} . $$

5.2 Differential inclusion in a nuclear space

Let \(\mathbb{R}^{d}\) (with fixed \(d\in\mathbb{N}^{\ast}\)), set \(\mathcal{D} (\mathbb{R}^{d} )\) to be the space of all complex-valued infinitely differentiable functions on \(\mathbb{R}^{d}\) with compact support, and define the differential operator for each multiindex \(\alpha\in\mathbb{N}^{d}\) with \(\alpha= (\alpha_{1},\alpha _{2},\ldots,\alpha_{d} )\) by

$$ D^{\alpha}=\cfrac{\partial^{\vert \alpha \vert }}{\partial x_{1}^{\alpha_{1}} \, \partial x_{2}^{\alpha_{2}}\cdots\partial x_{d}^{\alpha_{d}}}, $$

where \(\vert \alpha \vert =\alpha_{1}+\cdots+\alpha_{d}\). The space \(\mathcal{D} (\mathbb{R}^{d} )\) is endowed by a locally convex topology defined by the family of separated seminorms

$$ \Vert \varphi \Vert _{N}=\sup \bigl\{ \bigl\vert D^{\alpha}\varphi (x )\bigr\vert ; x\in\mathbb{R}^{d} \mbox{ and }\vert \alpha \vert \leq N \bigr\} . $$

Recall that a subset \(B\subset\mathcal{D} (\mathbb{R}^{d} )\) is bounded if for some compact \(K\subset\mathbb{R}^{d}\), we have \(B\subset\mathcal{D} (K )\) and there are numbers \(M_{N}<\infty\) such that every \(\varphi\in B\) satisfies the inequalities

$$ \Vert \varphi \Vert _{N}\leq M_{N}, \quad N=0,1,2, \ldots . $$

It is worth noting that \(\mathcal{D} (\mathbb{R}^{d} )\) endowed with the limit inductive topology of \(\{ \mathcal{D} (K_{n} ) \} _{n}\) is a complete nonmetric space, where \((K_{n} )_{n\in\mathbb{N}}\) is an exhaustive sequence of compact subsets, that is, for every \(n\in \mathbb{N}\), \(K_{n}\) included in the interior of \(K_{n+1}\), and \(\mathbb{R}^{d}=\cup _{n}K_{n}\); for more details, see [29].

Now, let \(\mathcal{D}^{\prime} (\mathbb{R}^{d} )\) be the strong dual of \(\mathcal{D} (\mathbb{R}^{d} )\), also endowed with the locally convex topology generated by an uncountable separated family of seminorms over the bounded subset of \(\mathcal{D} (\mathbb {R}^{d} )\) denoted by τ, that is,

$$ p_{B} (f )=\sup_{\varphi\in B}\bigl\vert \langle f,\varphi \rangle\bigr\vert , \quad B\subset\mathcal{D} \bigl(\mathbb{R}^{d} \bigr) \quad \mbox{bounded} . $$

Definition 5.6

In a Hausdorff locally convex space \((\mathbb{X}, \{ p_{i} \} _{i\in\Lambda} )\), a convex cone \(\mathbb{K}\subset\mathbb{X}\) is supernormal [13] if for each \(i\in\Lambda\), there exists a continuous linear form \(f_{i}\in\mathbb{K}^{\prime}\) (dual cone) such that, for each \(x\in\mathbb{K}\), we have

$$ p_{i} (x )\leq f_{i} (x ) . $$

\(\mathcal{D}^{\prime} (\mathbb{R}^{d} )\) endowed with τ-topology is a nuclear space [17], and we have the following:

Proposition 5.7

In a nuclear space \(\mathbb{X}\), a convex cone \(\mathbb {K}\subset\mathbb{X}\) is τ-supernormal if and only if it is τ-normal.

It is shown in [17] that the cone \(\mathbb{K}\) defined by

$$ \mathbb{K}= \bigl\{ \Lambda\in\mathcal{D}^{\prime} \bigl(\mathbb {R}^{d} \bigr); \langle\Lambda,\varphi \rangle\geq0, \forall \varphi\in \mathcal{C} \bigr\} $$

is τ-normal cone, where \(\mathcal{C}= \{ \varphi\in\mathcal {D} (\mathbb{R}^{d} ); \varphi (x )\geq0, \forall x\in \mathbb{R}^{d} \} \), and hence \(\mathbb{K}\) is τ-supernormal.

Next, we propose to solve the partial differential inclusion problem;

$$ (\mathcal{P} ) \mbox{:}\quad \textstyle\begin{cases} \mbox{find a locally integrable function }u\in L_{\mathrm{loc}}^{1} (\mathbb {R}^{d} ) \mbox{ such that} \\ D^{\alpha}u\in F (u ) \mbox{ a.e. on }\mathbb{R}^{d}, \end{cases} $$

where \(\alpha\in\mathbb{N}^{d}\) a multiindex, and \(F:L_{\mathrm{loc}}^{1} (\mathbb{R}^{d} )\longrightarrow2^{L_{\mathrm{loc}}^{1} (\mathbb {R}^{d} )}\).

Given \(u\in L_{\mathrm{loc}}^{1} (\mathbb{R}^{d} )\), it is shown in [29] that u defines a regular distribution, denoted \(\Lambda_{u}\in\mathcal{D}^{\prime} (\mathbb{R}^{d} )\), as follows:

$$ \Lambda_{u} (\varphi )= \int_{\mathbb{R}^{d}}u (x )\varphi (x )\, dx $$

for all \(\varphi\in\mathcal{D} (\mathbb{R}^{d} )\).

Also, if \(u\in L_{\mathrm{loc}}^{1} (\mathbb{R}^{d} )\), we know that \(\Lambda_{D^{\alpha}u}=D^{\alpha}\Lambda_{u}\), and hence we propose to solve problem (\(\mathcal{P} \)) in regular distributions setting and consider the differentiability in the weak sense. Problem (\(\mathcal{P} \)) is transformed by the canonical isomorphism

$$ \mathcal{G}:L_{\mathrm{loc}}^{1} \bigl(\mathbb{R}^{d} \bigr)\longrightarrow \mathcal{G} \bigl(\mathcal{D}^{\prime} \bigl(\mathbb{R}^{d} \bigr) \bigr) $$

to

$$ \bigl(\mathcal{P}^{\prime} \bigr) \mbox{:}\quad \textstyle\begin{cases} \mbox{find a regular distribution }\Lambda_{u}\in\mathcal{D}^{\prime } (\mathbb{R}^{d} ) \mbox{ such that} \\ D^{\alpha}\Lambda_{u}\in\mathcal{F} (\Lambda_{u} ) \mbox{ a.e. on }\mathbb{R}^{d}, \end{cases} $$

where \(\mathcal{F}\) is the set-valued map defined from \(\mathcal {D}^{\prime} (\mathbb{R}^{d} )\) into \(2^{\mathcal{D}^{\prime } (\mathbb{R}^{d} )}\) by

$$ \Lambda_{v}\in\mathcal{F}(\Lambda_{u})\quad \Leftrightarrow\quad v\in F(u) . $$

Now, passing to the second part of our developments, there is no chance that problem (\(\mathcal{P^{\prime}}\)) has a solution, so we will give a sufficient condition on the set-valued map F in order that the problem has at least one solution. For this, we define two subsets \(\mathcal{I}\) and \(\mathcal{J}\) of \(\mathcal{D}^{\prime} (\mathbb{R}^{d} )\) by

$$\begin{aligned}& \mathcal{I}= \biggl\{ \Lambda_{f}; f\in L_{\mathrm{loc}}^{1} \bigl(\mathbb {R}^{d} \bigr), \Lambda_{f}(\varphi)= \int_{\mathbb{R}^{d}}f (x )D^{\alpha}\varphi (x )\,dx \mbox{ for each } \varphi\in\mathcal{D} \bigl(\mathbb{R}^{d} \bigr) \biggr\} ; \\& \forall\Lambda_{u}\in\mathcal{D}^{\prime} \bigl( \mathbb{R}^{d} \bigr)\mbox{:} \quad \mathcal{J} (\Lambda_{u} )= \bigl\{ \Lambda_{f}\in\mathcal {I}; u (x )\geq (-1 )^{\vert \alpha \vert }f (x ), \forall x\in\mathbb{R}^{d} \bigr\} , \end{aligned}$$

and for each regular distribution \(\Lambda_{u}\in\mathcal{D}^{\prime } (\mathbb{R}^{d} )\), we define the set-valued maps \(\mathcal{R}\) and \(\mathcal{T}\) as follows:

$$\begin{aligned}& \mathcal{R} (\Lambda_{u} )= \bigl\{ \Lambda_{v}\in\mathcal {D}^{\prime} \bigl(\mathbb{R}^{d} \bigr); \forall\varphi\in \mathcal{C}, \langle\Lambda_{u}-\Lambda_{v},\varphi \rangle \geq0 \bigr\} ; \\& \mathcal{T} (\Lambda_{u} )= \bigl\{ \Lambda_{v}\in\mathcal {R} (\Lambda_{u} ); D^{\alpha}v\in F (u ) \mbox{ a.e. on } \mathbb{R}^{d} \bigr\} . \end{aligned}$$

It is obvious that \(\mathcal{R} (\Lambda_{u} )\) is nonempty since \(\Lambda_{u}\in\mathcal{R} (\Lambda_{u} )\), and for \(\mathcal{T} (\Lambda_{u} )\), we need the next lemma.

Lemma 5.8

If for each \(\Lambda_{u}\in\mathcal{D}^{\prime} (\mathbb {R}^{d} )\), \(\mathcal{F} (\Lambda_{u} )\cap\mathcal{J} (\Lambda _{u} )\neq\emptyset\), then \(\mathcal{T} (\Lambda_{u} )\) is a nonempty subset of \(\mathcal{D}^{\prime} (\mathbb{R}^{d} )\).

Proof

Let f be a locally integrable function, and let \(\Lambda_{u}\in \mathcal{D}^{\prime} (\mathbb{R}^{d} )\). Then the function

$$ \varphi\mapsto \int_{\mathbb{R}^{d}}f (x )D^{\alpha}\varphi (x )\,dx\quad \mbox{is an element of } \mathcal{F} (\Lambda_{u} ) , $$

and a simple calculation leads to

$$\begin{aligned} \int_{\mathbb{R}^{d}}f (x )D^{\alpha}\varphi (x )\,dx & = (-1 )^{\vert \alpha \vert } \int_{\mathbb{R}^{d}}D^{\alpha }f (x )\varphi (x )\,dx \\ & = \int_{\mathbb{R}^{d}}D^{\alpha} \bigl[ (-1 )^{\vert \alpha \vert }f (x ) \bigr]\varphi (x )\,dx. \end{aligned}$$

Put \(v (x )= (-1 )^{\vert \alpha \vert }f (x )\) for \(x\in\mathbb{R}^{d}\). Then \(v\in L_{\mathrm{loc}}^{1} (\mathbb {R}^{d} )\), and

$$ \int_{\mathbb{R}^{d}}D^{\alpha}v (x )\varphi (x )\,dx= \Lambda_{D^{\alpha}v} (\varphi ) , $$

which leads to \(\Lambda_{D^{\alpha}v}\in\mathcal{F} (\Lambda _{u} )\). Thus, \(D^{\alpha}v\in F(u)\).

For each \(\varphi\in\mathcal{C}\), we have

$$\begin{aligned} \Lambda_{u} (\varphi )-\Lambda_{v} (\varphi ) & = \Lambda_{u} (\varphi )- (-1 )^{\vert \alpha \vert }\Lambda_{f} ( \varphi ) \\ & = \int_{\mathbb{R}^{d}} \bigl[u (x )- (-1 )^{ \vert \alpha \vert }f (x ) \bigr]\geq0. \end{aligned}$$

Hence, \(\Lambda_{v}\in\mathcal{T} (\Lambda_{u} )\). □

As an interesting application of the main result, we can state and prove the following existence theorem.

Theorem 5.9

If \(\mathbb{K}\) and \(\mathcal{R}\) are as before and \(\mathcal{T}\) satisfies the assumption in the previous lemma, then problem (\(\mathcal{P^{\prime}}\)) has a solution.

Proof

By assumption, for each \(\Lambda_{u}\in\mathcal{D}^{\prime} (\mathbb {R}^{d} )\), there exists \(\Lambda_{v}\in\mathcal{T} (\Lambda_{u} )\) such that:

  1. (i)

    \(D^{\alpha}\Lambda_{v}\in\mathcal{F} (\Lambda_{u} )\), and

  2. (ii)

    \(\Lambda_{v}\in\mathcal{R} (\Lambda_{u} )\).

Then, for every \(\varphi\in\mathcal{D} (\mathbb{R}^{d} )\), we have

$$ \langle\Lambda_{u}-\Lambda_{v},\varphi \rangle\geq 0\quad \Longleftrightarrow\quad (\Lambda_{u}-\Lambda_{v} ) (\varphi )\geq0 , $$

which implies that \((\Lambda_{u}-\Lambda_{v} )\in\mathbb{K}\); since \(\mathbb{K}\) is a supernormal cone, for each bounded subset B of \(\mathcal{D} (\mathbb{R}^{d} )\), there exists \(f_{B}\in \mathbb{K^{\prime}}\) such that

$$ p_{B} (\Lambda_{u}-\Lambda_{v} )\leq f_{B} (\Lambda _{u}-\Lambda_{v} )\quad \Longleftrightarrow\quad p_{B} (\Lambda _{u}- \Lambda_{v} )\leq f_{B} (\Lambda_{u} )-f_{B} (\Lambda_{v} ) . $$

All assumptions of our former result in Proposition 3.4 hold. Therefore, \(\mathcal{T}\) has a fixed point \(\Lambda_{u^{\star}}\in\mathcal{D}^{\prime} (\mathbb {R}^{d} )\), that is,

$$ \Lambda_{u^{\star}}\in\mathcal{T} (\Lambda_{u^{\star}} )\quad \Leftrightarrow\quad D^{\alpha}u^{\star}\in F \bigl(u^{\star}\bigr) . $$

 □

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The authors are grateful to the anonymous referees for their helpful comments and remarks.

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Lazaiz, S., Chaira, K., Aamri, M. et al. Pseudo-metric space and fixed point theorem. Fixed Point Theory Appl 2017, 3 (2016). https://doi.org/10.1186/s13663-017-0594-z

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