The theory of fixed points continues to be a widely used tool across various branches of mathematics, with the classical Banach contraction principle being a well-known example [7]. This principle is particularly significant as it allows for the resolution of integral equations, differential equations, and fractional differential equations by reducing them to the problem of identifying a self-mapping’s fixed points. The assurance of a unique fixed point on a complete metric space provided by the Banach contraction principle has sparked numerous extensions by researchers, expanding its applicability in various contexts (see [2,3,4,5,6, 8, 10, 12, 15,16,17,18,19, 21]). In 1994, the concept of partial metric spaces was introduced by Matthews during the study of denotational semantics of data-flow networks. Expanding on this notion, Shukla [21] made significant progress two decades later by generalizing both partial metric spaces and b–metric spaces, leading to the establishment of the class of partial b–metric spaces. This new framework was utilized to establish a fixed point theorem as an analog of the Banach contraction principle.
In 2007, Huang and Zhang [12] introduced the concept of cone metric spaces by substituting the set of real numbers (range set of the metric) with an ordered Banach space. Later, in 2014, Ma et al. [17] expanded on this concept by inventing C∗-algebra valued metric spaces, which give a more comprehensive framework than ordinary metric spaces by substituting a unital C∗-algebra for the range set. Within this context, they successfully proved fixed point results. The subsequent year, Ma et al. [16] took it a step further and introduced C∗-algebra valued b-metric spaces, thereby broadening their work and establishing additional fixed point results, including an application involving integral type operators. In 2019, Chandok [9] generalized C∗-algebra valued metric spaces to C∗-algebra valued partial metric spaces and demonstrated some fixed point theorems. By developing the novel class of C∗-algebra valued partial b-metric spaces in 2020, Mlaiki et al. [19] expanded both C∗-algebra valued partial metric spaces and C∗-algebra valued b-metric spaces. They utilized this innovative concept to prove fixed point theorems and presented an application for solving integral type equations.
In 2012, Sedghi et al. [20] introduced the concept of S-metric spaces and established fixed point theorems for implicit relations. Concurrently, in the same year, Iranmanesh et al. [13] pioneered the idea of PIV-metric spaces and proved fixed point results within this framework. Subsequently, in 2019, Iranmanesh et al. [14] further expanded on this concept and presented additional fixed point and the results on best proximity point in PIV-metric spaces.
Building on the previous observations, we propose the notion of PIV-metric space and S-metric space, culminating in the concept of PIV-S-metric space. By doing so, we not only unify these two notions but also employ this new framework to establish fixed point results. Additionally, we provide an illustrative example to showcase the practical applications and utility of our main findings.
Now, we gather a few pertinent definitions and facts that will be relevant for the subsequent discussion:
In 1994, Matthews put forth the definition of a partial metric space, which is as follows:
Let V ≠ ∅. A mapping p : V × V → ℝ+ is called partial metric on U if (for all χ, ϱ, θ ∈ V):
- (1)
χ = ϱ ⇔ p(χ, χ) = p(χ, ϱ) = p(ϱ, ϱ),
- (2)
p(χ, χ) ≤ p(χ, ϱ),
- (3)
p(χ, ϱ) = p(ϱ, χ),
- (4)
p(χ, θ) ≤ p(χ, ϱ) + p(ϱ, θ) − p(ϱ, ϱ).
The pair (V, p) is called a partial metric space.
Since then this fundamental concept has played a significant role in various mathematical investigations and continues to be relevant in subsequent research.
Obviously, if p(χ, χ) = 0 for all χ ∈ V, then (V, p) is a metric space.
Throughout the paper, we denote by (𝔹, ⊕) an idempotent space and 𝔹+ := {χ ∈ 𝔹 : χ ≥⊕ 0𝔹}, where 0𝔹 is a zero element in 𝔹.
We define an order relations on idempotent space (𝔹, ⊕) by
Let 𝔹 = ℝ endowed with χ ⊕ ϱ = max{χ, ϱ} or χ ⊕ ϱ= min{χ, ϱ} for all χ, ϱ ∈ ℝ. Then (𝔹, ⊕) is an idempotent space.
Let 𝔹 be a set of real matrices. The conforming matrices M1 = (χij), M2 = (ϱij) satisfy the conventional rule of matrix addition together with multiplication by a scalar α ∈ ℝ as follows
A vector space 𝔹 over field ℝ is said to be an idempotent space if it satisfies the following (for all χ, ϱ, θ ∈ 𝔹):
- (i)
χ ⊕ (ϱ ⊕ θ) = (χ ⊕ ϱ) ⊕ θ;
- (ii)
χ ⊕ χ = χ.
An idempotent space (𝔹, ⊕) is commutative if χ ⊕ ϱ = ϱ ⊕ χ.
Assume that (𝔹, ≤) is a partially ordered set. We define
Let (𝔹, ≤) be a partially ordered vector space. Let {χn} be a sequence in 𝔹 and χ ∈ 𝔹. If ∀ 0𝔹 < a ∃ N ∈ ℕ ∀ n ≥ N (χn − χ < a), then the sequence {χn} is called convergent and converges to χ, where χ is called limit of {χn}. We write then
Consider a partially ordered vector space (𝔹, ≤), and let us focus on its order relation. We say that the order relation on 𝔹 has a positive cone ordering property when the following conditions hold: For any vector 0𝔹 ≤ r ≤ s and scalar inequalities 0 ≤ l ≤ ϱ, the resulting inequalities are as follows:
Let (𝔹, ≤) be a partially ordered vector space. If the order relation on 𝔹 has the positive cone ordering property, then 𝔹 is a normal space.
Now, we recall the definition of PIV-metric space as follows:
Let V ≠ ∅. An idempotent valued S-metric on V is a function dI : V × V → 𝔹+ that satisfies the following (for all χ, ϱ, θ ∈ V):
- (i)
dI (χ, ϱ) = dI (χ, χ) = dI (ϱ, ϱ) ⇔ χ = ϱ;
- (ii)
dI (χ, χ) ≤⊕ dI (χ, ϱ);
- (iii)
dI (χ, ϱ) = dI (ϱ, χ);
- (iv)
dI (χ, ϱ) ≤⊕ dI (χ, θ) ⊕ dI (θ, ϱ).
Let V = [0, ∞), 𝔹 = ℝ endowed with χ ⊕ ϱ = max{χ, ϱ}. Define a mapping d : V × V → 𝔹+ by
The concept of S-metric space was initiated by Sedghi et al. [20] in 2012 and runs as follows.
Let V ≠ ∅. An S-metric space is a function d : V × V × V → ℝ+ that satisfies the following (for all χ, ϱ, θ, σ ∈ V ):
- (i)
d(χ, ϱ, θ) ≥ 0;
- (ii)
d(χ, ϱ, θ) = 0 ⇔ χ = ϱ = θ;
- (iii)
d(χ, ϱ, θ) ≤ d(χ, χ, σ) + d(ϱ, ϱ, σ) + d(θ, θ, σ).
The following notion of partial S-metric space is proposed by Asil et al. [1].
Let V ≠ ∅. A partial S-metric space is a function d : V × V × V → ℝ+ that satisfies the following (for all χ, ϱ, θ, σ ∈ V):
- (i)
d(χ, χ, χ) = d(ϱ, ϱ, ϱ) = d(χ, χ, ϱ) ⇔ χ = ϱ;
- (ii)
d(χ, χ, χ) ≤ d(χ, ϱ, θ);
- (iii)
d(χ, ϱ, θ) ≤ d(χ, χ, σ) + d(ϱ, ϱ, σ) + d(θ, θ, σ) − 2d(σ, σ, σ).
Clearly, every S-metric space can be considered as a partial S-metric space. However, it is important to note that the converse is not always true in general. In other words, not every partial S-metric space can be regarded as an S-metric space. The distinction between the two lies in the specific conditions and properties that they satisfy, making them distinct concepts within the realm of mathematical spaces.
Now, we introduce the following definition of PIV-S-metric space.
Let V ≠ ∅. A PIV-S-metric on V is a function d : V × V × V → 𝔹+ that satisfies the following (for all χ, ϱ, θ, σ ∈ V):
- (i)
d(χ, χ, χ) = d(ϱ, ϱ, ϱ) = d(χ, χ, ϱ) ⇔ χ = ϱ;
- (ii)
d(χ, χ, χ) ≤⊕ d(χ, ϱ, θ);
- (iii)
d(χ, χ, ϱ) = d(ϱ, ϱ, χ);
- (iv)
d(χ, ϱ, θ) ≤⊕ d(χ, χ, σ) ⊕ d(ϱ, ϱ, σ) ⊕ d(θ, θ, σ).
Let V = [0, ∞), 𝔹 = ℝ endowed with the operation χ⊕ϱ= max{χ, ϱ}. Define a mapping d : V × V × V → 𝔹+ by
Then the triplet (V, 𝔹, d) is a PIV-S-metric space. When we connect points χ, ϱ, θ with lines, forming a triangle, and choose a point σ inside this triangle, the inequality
Let Y ≠ ∅ and V = B(Y, [0, ∞)) be the set of bounded mappings with order-bounded range. Suppose 𝔹 = B(V, (ℝ, ⊕)) with (T1 ⊕ T2)(χ) = T1(χ) ⊕ T2(χ) and χ ⊕ ϱ = max{χ, ϱ}. Define a mapping d : V × V × V → 𝔹+ by
Let V ≠ ∅, dI endowed with the operation ⊕ PIV-metric on V. Then
Let (V, 𝔹, d) be a PIV-S-metric space. Then the open ball with radius ɛ >⊕ 0𝔹 and center χ is defined by
Let (V, 𝔹, d) be a PIV-S-metric space. We say that
- (i)
A sequence {χn} ⊂ V is called convergent to χ if and only if
\mathop {\lim}\limits_{n \to \infty} d({\chi_n},{\chi_n},\chi) = d(\chi,\chi,\chi). - (ii)
A sequence {χn} ⊂ V is called Cauchy if and only if
exists and is finite.\mathop {\lim}\limits_{n,m \to \infty} d\left({{\chi_n},{\chi_n},{\chi_m}} \right) - (iii)
The PIV-S-metric space (V, 𝔹, d) is said to be complete if every Cauchy sequence {χn} in V converges to a point χ ∈ V such that
d(\chi,\chi,\chi) = \mathop {\lim}\limits_{n \to \infty} d({\chi_n},{\chi_n},\chi) = \mathop {\lim}\limits_{n,m \to \infty} d({\chi_n},{\chi_n},{\chi_m}).
Let (V, 𝔹, d) be a PIV-S-metric space. A mapping f : V → V is called a continuous at point χ ∈ V if for any χn → χ implies that fχn → fχ.
Our main result runs as follows:
Let (V, 𝔹, d) be a complete PIV-S-metric space and f : V → V satisfy the following:
Choose χ0 ∈ V and define χn+1 = fχn for all n ∈ ℕ0. For any n ∈ ℕ0, we have
For the uniqueness part, let us assume that there exist two points ξ and ξ∗ in the space V such that fξ = ξ and fξ∗ = ξ∗. In other words, ξ and ξ∗ are fixed points of the mapping f. Then by employing (3.1), we have
Finally, we show that d(ξ, ξ, ξ) = 0𝔹. Let us suppose, d(ξ, ξ, ξ) >⊕ 0𝔹.
Then (3.1) implies that
Let V = [1, ∞), 𝔹 = ℝ endowed with the operation χ⊕ϱ=max{χ, ϱ}. Define a mapping d : V × V × V → 𝔹+ by
Consider a complete PIV-S-metric space (V, 𝔹, d) and a mapping f : V → V that fulfills the following:
In this section, we delve into the study of best proximity points within the framework of PIV-S-metric spaces. The significance of best proximity point results lies in their relevance to best approximation outcomes from this perspective. The inception of best proximity point results can be traced back to Fan [11], who demonstrated that for a continuous mapping f : K → X defined on a nonempty compact convex subset K of a Hausdorff locally convex topological vector space V, equipped with the metric d, there exists a point χ ∈ K such that d(χ, fχ) = inf{d(ϱ, fχ) = inf{d(ϱ, fχ) : ϱ ∈ K}. Notably, when f is a self-mapping, the best proximity point transforms into a fixed point. The best approximation theorem ensures the existence of an approximate solution, while the best proximity point theorem proves instrumental in resolving the problem and offering an optimal approximate solution.
Consider two nonempty subsets, denoted as A and B, of a metric space (V, d). In the context of a mapping f : A → B, an element χ ∈ A is referred to as a fixed point if fχ = χ. It is important to highlight that the requirement f (A) ∩ A ≠ ∅ is a vital condition for the presence of a fixed point in the mapping f. However, it’s worth noting that this condition is necessary but not sufficient. If the intersection of A and f (A) is empty, it implies that there is no fixed point for f. In such cases, it is customary to seek an element χ that is in some way closest to fχ, with the hope of finding an approximate solution even though a fixed point may not exist.
Let (V, 𝔹, d) be a PIV-S-metric space and Sd : V ×V → 𝔹 defined as follows
Observe that the conditions (i)–(iii) are satisfied. Now to for (iv), we have
Let A and B be two nonempty subsets of (V, 𝔹, d). Denote the distance between A and B by
In the same way, we have developed the best proximity point analysis in the framework of PIV-S-metric space (V, 𝔹, d).
An element χ ∈ A is said to be best proximity point of the map f : A → B if
The fundamental objective of the best proximity point theory is to establish sufficient conditions that guarantee the existence of such points. By providing these conditions, the theory offers a valuable tool to determine when best proximity points are attainable, allowing for the identification of optimal approximate solutions in various scenarios.
In what follows, we introduce two notions.
Let (V, 𝔹, d) be a PIV-S-metric space and A, B two nonempty subsets of V. The set B is said to be approximatively compact with respect to A if every sequence {ϱn} ⊆ B satisfying the condition Sd(χ, ϱn) → Sd(χ, B) has a convergent subsequence for some χ in A.
Let A and B be two nonempty subsets of a PIV-S-metric space (V, 𝔹, d). The mapping f : A → B is said to be ⊕—proximal contraction mapping if
Consider two nonempty subsets, A and B of a complete PIV-S-metric space (V, 𝔹, d), A0 is nonempty, and B is approximately compact with respect to A. Let us assume that f : A → B is a ⊕—proximal contraction mapping satisfying f (A0) ⊆ B0. Then f has a unique best proximity point ξ ∈ A such that Sd(ξ, fξ) = Sd(A, B).
Fix an arbitrary point χ0 ∈ A0 and take fχ0 ∈ f (A0) ⊆ B0 into account. We can choose χ1 ∈ A0 such that Sd(χ1, fχ0) = Sd(A, B). Also, since fχ1 ∈ f (A0) ⊆ B0, there exists χ1 ∈ A0 such that Sd(χ2, fχ1) = Sd(A, B). Continuing this process, we can construct a sequence {χn} in A0 such that
For the uniqueness part, suppose that ξ ≠ ξ∗, Sd(ξ, fξ) = Sd(A, B) and Sd(ξ∗, fξ∗) = Sd(A, B). Employing (4.2) with x = χ = ξ and y = ϱ = ξ∗, we have
In Example 3.1, define a mapping f : V → V by
In this paper, we presented a unification of the concepts of PIV-metric space and S-metric space, by introducing the notion of PIV-S-metric space and utilizing it to establish fixed point results. Additionally, we extended our study to prove best proximity point results within the framework of PIV-S-metric space. To illustrate the practical applications of our main results, we provided several examples that showcase their relevance and utility. This unified approach not only enhances our understanding of these mathematical spaces but also opens up new avenues for exploring fixed point and best proximity point properties within a broader context.