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. 2021 Jul 8;23(7):871. doi: 10.3390/e23070871

Some Integral Inequalities Involving Metrics

Ravi P Agarwal 1,, Mohamed Jleli 2,, Bessem Samet 2,*,
Editor: António M Lopes
PMCID: PMC8306268  PMID: 34356412

Abstract

In this work, we establish some integral inequalities involving metrics. Moreover, some applications to partial metric spaces are given. Our results are extension of previous obtained metric inequalities in the discrete case.

Keywords: integral inequalities, metric, partial metric, sub-additive, convex, log-convex, σ-Lipschitzian

1. Introduction

Metric inequalities provide powerful tools for the investigation of several problems from different branches of mathematics and sciences. In particular, from entropy and information theory (see e.g., [1,2,3]), fixed point theory (see e.g., [4,5,6,7,8]), geometry (see e.g., [9,10,11]) and telecommunication networks (see e.g., [12,13]).

In [14], Dragomir and Gosa established a polygonal type inequality and provided some applications to normed linear spaces and inner product spaces. We recall below the main result obtained in [14]. Let X be a nonempty set and ρ:X×X[0,+) be a metric on X (see [15]), that is, for all a,b,cX,

  • ρ(a,b)=0 if and only if a=b;

  • ρ(a,b)=ρ(b,a);

  • ρ(a,b)ρ(a,c)+ρ(c,b).

Let n2 be a natural number, {xi}i=1nX, and {μi}i=1n[0,+) with μ1+μn=1. Then

1i<jnμiμjρ(xi,xj)infxXi=1nμiρ(xi,x). (1)

It was shown also that (1) is sharp in the following sense: there exists n2 and {μi}i=1n[0,+) with μ1+μn=1 such that, if

1i<jnμiμjρ(xi,xj)cinfxXi=1nμiρ(xi,x)

for some c>0, then c1. Inequality (1) can be interpreted as follows: If P is a polygon having q vertices and M is a point in the space, then the sum of all edges and diagonals of P is less than q-times the sum of the distances from M to the vertices of P.

Recently, inequality (1) has been extended by some authors. In [16], Karapinar and Noorwali derived a b-metric version of (1). In [17], Aydi and Samet proved (under the above assumptions) that

121i<jnμiμj[ρ(xi,xj)]minfxX2i=1nμi[ρ(xi,x)]m+k=1m1(mk)i=1nμi[ρ(xi,x)]ki=1nμi[ρ(xi,x)]mk,

where m1 is a natural number. In [18] (see also [19]) Dragomir improved inequality (1) by proving that for all α>0,

1i<jnμiμj[ρ(xi,xj)]αaαinfxXi=1nμi(1μi)[ρ(xi,x)]α, (2)

where

aα=2α1ifα1,1if0<α<1. (3)

In this paper, our goal is to derive continuous versions of inequality (2). In the next section, we recall some basic definitions. In Section 3, we present and prove our obtained results. Finally, in Section 4, some applications to partial metric spaces are provided.

2. Some Definitions

Let ω:[0,+)[0,+) be a given function. We say that ω is sub-additive, if

ω(y+z)ω(y)+ω(z),for all y,z0.

Some examples of sub-additive functions are given below:

  • ωα(y)=yα, y0, 0α1.

  • ω(y)=|siny|, y0.

  • ω(y)=arctany, y0.

  • ω(y)=inf{y,1}, y0.

  • ω(y)=1+y2, y0.

  • ω(y)=exp(y), y0.

We say that ω is convex, if

ω(ϕy+(1ϕ)z)ϕω(y)+(1ϕ)ω(z),

for all 0<ϕ<1 and y,z0.

We say that ω is log-convex, if

ω(ϕy+(1ϕ)z)[ω(y)]ϕ[ω(z)]1ϕ,

for all 0<ϕ<1 and y,z0. Notice that, if ω is log-convex, then it is convex, but the converse is not true in general (see [20]).

We say that ω is σ-Lipschitzian, σ>0, if

|ω(y)ω(z)|σ|yz|,for all y,z0.

3. Results and Proofs

Let (X,ρ) be a metric space. Let x:[0,A]X, A>0, be a continuous mapping. Let μ:[0,A][0,+) be a function satisfying the following conditions:

  • (H1)

    μ is continuous.

  • (H2)

    0Aμ(s)ds=1.

3.1. The Case: ω Is Sub-Additive

Theorem 1.

Let ω:[0,+)[0,+) be a continuous, nondecreasing, and sub-additive function. Then

0Aμ(t)0tμ(s)ωρ(x(t),x(s))dsdtinfuX0Aμ(s)ωρ(x(s),u)ds. (4)

Proof. 

Let uX be fixed. Then, for every t,s[0,A],

ρ(x(t),x(s))ρ(x(t),u)+ρ(u,x(s)).

Since ω is nondecreasing, the above inequality leads to

ωρ(x(t),x(s))ωρ(x(t),u)+ρ(u,x(s)).

Due to the sub-additivity of ω, it holds that

ωρ(x(t),x(s))ωρ(x(t),u)+ωρ(u,x(s)).

Multiplying the above inequality by μ(t)μ(s) (notice that μ0) and integrating over [0,A]×[0,A], we obtain

0A0Aμ(t)μ(s)ωρ(x(t),x(s))dtds0A0Aμ(t)μ(s)ωρ(x(t),u)dtds+0A0Aμ(t)μ(s)ωρ(u,x(s)dtds. (5)

On the other hand, by (H2), we have

0A0Aμ(t)μ(s)ωρ(x(t),u)dtds=0Aμ(s)ds0Aμ(t)ωρ(x(t),u)dt=0Aμ(t)ωρ(x(t),u)dt.

Similarly,

0A0Aμ(t)μ(s)ωρ(u,x(s))dtds=0Aμ(s)ωρ(u,x(s))ds.

Combining the above inequalities, we obtain

0A0Aμ(t)μ(s)ωρ(x(t),u)dtds+0A0Aμ(t)μ(s)ωρ(u,x(s))dtds=20Aμ(s)ωρ(u,x(s))ds. (6)

Moreover, we have

0A0Aμ(t)μ(s)ωρ(x(t),x(s))dtds=0Aμ(t)0tμ(s)ωρ(x(t),x(s))dsdt+0Aμ(t)tAμ(s)ωρ(x(t),x(s))dsdt. (7)

On the other hand, using Fubini’s theorem and the symmetry of ρ, we obtain

0Aμ(t)tAμ(s)ωρ(x(t),x(s))dsdt=0Aμ(t)0tμ(s)ωρ(x(t),x(s))dsdt. (8)

Therefore, by (7) and (8), we deduce that

0A0Aμ(t)μ(s)ωρ(x(t),x(s))dtds=20Aμ(t)0tμ(s)ωρ(x(t),x(s))dsdt. (9)

Finally, (4) follows from (5), (6) and (9). □

Next, we study some special cases of ω. In the case ω(y)=yα, 0<α1, we deduce from Theorem 1 the

Corollary 1.

Let 0<α1. Then

0Aμ(t)0tμ(s)ρ(x(t),x(s))αdsdtinfuX0Aμ(s)ρ(x(s),u)αds.

In the special case when ω(y)=α+y2, α>0, we deduce from Theorem 1 the

Corollary 2.

Let α>0. Then

0Aμ(t)0tμ(s)α+[ρ(x(t),x(s))]2dsdtinfuX0Aμ(s)α+[ρ(x(s),u)]2ds.

In the case when ω(y)=arctan y, we deduce from Theorem 1 the

Corollary 3.

The following inequality holds:

0Aμ(t)0tμ(s)arctanρ(x(t),x(s))dsdtinfuX0Aμ(s)arctanρ(x(s),u)ds.

3.2. The Case: ω Is Convex

Theorem 2.

Let ω:[0,+)[0,+) be a nondecreasing and convex function. Then

0Aμ(t)0tμ(s)ωρ(x(t),x(s))2dsdt12infuX0Aμ(s)ωρ(x(s),u)ds. (10)

Proof. 

Fix uX. Since ω is nondecreasing, we have

ωρ(x(t),x(s))2ωρ(x(t),u)+ρ(u,x(s))2.

Due to the convexity of ω, the above inequality leads to

ωρ(x(t),x(s))212ωρ(x(t),u)+ωρ(u,x(s)).

Multiplying the above inequality by μ(t)μ(s) and integrating over [0,A]×[0,A], we obtain

0A0Aμ(t)μ(s)ωρ(x(t),x(s))2dtds120A0Aμ(t)μ(s)ωρ(x(t),u)dtds+120A0Aμ(t)μ(s)ωρ(u,x(s)dtds. (11)

Proceeding as in the proof of Theorem 1, we obtain

0A0Aμ(t)μ(s)ωρ(x(t),x(s))2dtds=20Aμ(t)0tμ(s)ωρ(x(t),x(s))2dsdt (12)

and

120A0Aμ(t)μ(s)ωρ(x(t),u)dtds+120A0Aμ(t)μ(s)ωρ(u,x(s)dtds=0Aμ(s)ωρ(x(s),u)ds. (13)

Finally, combining (11), (12), and (13), (10) follows. □

In the special case when ω(y)=yα, α>1, by Theorem 2, we deduce the following result.

Corollary 4.

Let α>1. Then

0Aμ(t)0tμ(s)ρ(x(t),x(s))αdsdt2α1infuX0Aμ(s)ρ(x(s),u)αds.

3.3. The Case: ω Is log-Convex

Theorem 3.

Let ω:[0,+)[0,+) be a nondecreasing and log-convex function. Then

0Aμ(t)0tμ(s)ωρ(x(t),x(s))2dsdt12infuX0Aμ(s)ωρ(x(s),u)ds2. (14)

Proof. 

Fix uX. Since ω is nondecreasing, we have

ωρ(x(t),x(s))2ωρ(x(t),u)+ρ(u,x(s))2.

Due to the log-convexity of ω, the above inequality leads to

ωρ(x(t),x(s))2ωρ(x(t),u)ωρ(u,x(s)).

Multiplying the above inequality by μ(t)μ(s) and integrating over [0,A]×[0,A], we obtain

0A0Aμ(t)μ(s)ωρ(x(t),x(s))2dtds0A0Aμ(t)μ(s)ωρ(x(t),u)ωρ(u,x(s))dtds. (15)

On the other hand,

0A0Aμ(t)μ(s)ωρ(x(t),u)ωρ(u,x(s))dtds=0Aμ(s)ωρ(x(s),u)ds2. (16)

Hence, using (12), (15) and (16), (14) follows. □

Consider the special case ω(y)=exp(yα), α1. By Theorem 3, we obtain the

Corollary 5.

Let α1. Then

0Aμ(t)0tμ(s)expρ(x(t),x(s))2αdsdt12infuX0Aμ(s)expρ(x(s),u)αds2.

3.4. The Case: ω Is σ-Lipschitzian

Theorem 4.

Let ω:[0,+)[0,+) be a nondecreasing and σ-Lipschitzian function, σ>0. Then

0Aμ(t)0tμ(s)ωρ(x(t),x(s))dsdtσinfuX0Aμ(s)ωρ(x(s),u)ds+ω(0)2. (17)

Proof. 

Let uX be fixed. Then, for every t,s[0,A],

ρ(x(t),x(s))ρ(x(t),u)+ρ(u,x(s)).

Since ω is nondecreasing, the above inequality leads to

ωρ(x(t),x(s))ωρ(x(t),u)+ρ(u,x(s)).

On the other hand, since ω is σ-Lipschitzian, we have

ωρ(x(t),u)+ρ(u,x(s))=ωρ(x(t),u)+ρ(u,x(s))ω(0)+ω(0)σρ(x(t),u)+ρ(u,x(s))+ω(0).

Hence, it holds that

ωρ(x(t),x(s))σρ(x(t),u)+ρ(u,x(s))+ω(0).

Multiplying the above inequality by μ(t)μ(s) and integrating over [0,A]×[0,A], we obtain

0A0Aμ(t)μ(s)ωρ(x(t),x(s))dtdsσ0A0Aμ(t)μ(s)ωρ(x(t),u)dtds+σ0A0Aμ(t)μ(s)ωρ(u,x(s)dtds+ω(0)0A0Aμ(t)μ(s)dtds=σ0A0Aμ(t)μ(s)ωρ(x(t),u)dtds+σ0A0Aμ(t)μ(s)ωρ(u,x(s)dtds+ω(0). (18)

Next, using (6), (9) and (18), we deduce that

20Aμ(t)0tμ(s)ωρ(x(t),x(s))dsdt2σ0Aμ(s)ωρ(u,x(s))ds+ω(0),

which yields (17). □

3.5. The Case: μA1

Consider now the case when

μ(t)=A1,for all t[0,A].

Then by Theorems 1–4, we deduce the following inequalities.

Corollary 6.

Let ω:[0,+)[0,+) be a continuous, nondecreasing, and sub-additive function. Then

0A0tωρ(x(t),x(s))dsdtAinfuX0Aωρ(x(s),u)ds.

Corollary 7.

Let ω:[0,+)[0,+) be a nondecreasing and convex function. Then

0A0tωρ(x(t),x(s))2dsdtA2infuX0Aωρ(x(s),u)ds.

Corollary 8.

Let α>0. Then

0A0tρ(x(t),x(s))αdsdtaαAinfuX0Aρ(x(s),u)αds,

where aα is given by (3).

Corollary 9.

Let ω:[0,+)[0,+) be a nondecreasing and log-convex function. Then

0A0tωρ(x(t),x(s))2dsdt12infuX0Aωρ(x(s),u)ds2.

Corollary 10.

Let ω:[0,+)[0,+) be a nondecreasing and σ-Lipschitzian function, σ>0. Then

0A0tωρ(x(t),x(s))dsdtσAinfuX0Aωρ(x(s),u)ds+A2ω(0)2.

4. Applications to Partial Metrics

Let X be a nonempty set and ξ:X×X[0,+) be a partial metric on X (see e.g., [21]), i.e., for all x,y,zX,

  • ξ(x,y)=ξ(x,x)=ξ(y,y)=0 if and only if x=y;

  • ξ(x,x)ξ(x,y);

  • ξ(x,y)=ξ(y,x);

  • ξ(x,y)ξ(x,z)+ξ(z,y)ξ(z,z).

Let x:[0,A]X, A>0, be a continuous mapping. Let μ:[0,A][0,+) be a function satisfying (H1) and (H2).

Corollary 11.

Let ω:[0,+)[0,+) be a continuous, nondecreasing, and sub-additive function. Then

0Aμ(t)0tμ(s)ω2ξ(x(t),x(s))ξ(x(t),x(t))ξ(x(s),x(s))dsdtinfuX0Aμ(s)ω2ξ(x(s),u)ξ(x(s),x(s))ξ(u,u)ds. (19)

Proof. 

Observe that the mapping ρ:X×X[0,+) defined by

ρ(u,v)=2ξ(u,v)ξ(u,u)ξ(v,v),(u,v)X×X,

is a metric on X. Hence, applying Theorem 1 with ρ defined as above, (19) follows. □

Similarly, by Theorems 2–4, we obtain the following inequalities.

Corollary 12.

Let ω:[0,+)[0,+) be a nondecreasing and convex function. Then

0Aμ(t)0tμ(s)ω2ξ(x(t),x(s))ξ(x(t),x(t))ξ(x(s),x(s))2dsdt12infuX0Aμ(s)ω2ξ(x(s),u)ξ(x(s),x(s))ξ(u,u)ds.

Corollary 13.

Let ω:[0,+)[0,+) be a nondecreasing and log-convex function. Then

0Aμ(t)0tμ(s)ω2ξ(x(t),x(s))ξ(x(t),x(t))ξ(x(s),x(s))2dsdt12infuX0Aμ(s)ω2ξ(x(s),u)ξ(x(s),x(s))ξ(u,u)ds2.

Corollary 14.

Let ω:[0,+)[0,+) be a nondecreasing and σ-Lipschitzian function, σ>0. Then

0Aμ(t)0tμ(s)ω2ξ(x(t),x(s))ξ(x(t),x(t))ξ(x(s),x(s))dsdtσinfuX0Aμ(s)ω2ξ(x(s),u)ξ(x(s),x(s))ξ(u,u)ds+ω(0)2.

5. Conclusions

Metric inequalities provide powerful tools for the study of several problems from different branches of mathematics and sciences. New integral inequalities involving metrics, sub-additive, convex, log-convex, and σ-Lipschitzian functions are established in this work, and some applications to partial metric spaces are provided. The obtained results are continuous versions of some discrete metric inequalities obtained in [14,18,19].

Author Contributions

All authors contribute equally to this paper. All authors have read and agreed to the published version of the manuscript.

Funding

The third author is supported by Researchers Supporting Project number (RSP-2021/4), King Saud University, Riyadh, Saudi Arabia.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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