The multi-point dynamic aggregation problem (MPDAP) that arises in practical applications is characterized by a group of robots that have to cooperate in executing a set of tasks distributed over multiple locations, in which the demand for each task grows over time. To minimize the completion time of all tasks, one needs to schedule the robots and plan the routes. Hence, the problem is essentially a combinatorial optimization problem. The manuscript presented a new MPDAP in which the priority of the task was considered that is to say, some tasks must be first completed before others begin to be executed. When the tasks were located at different priority levels, some additional constraints were added to express the priorities of tasks. Since route selection of robots depends on the priorities of tasks, these additional constraints caused the presented MPDAP to be more complex than ever. To efficiently solve this problem, an improved optimization algorithm, called the multi-strategy genetic algorithm (MSGA), was developed. First of all, a two-stage hybrid matrix coding scheme was proposed based on the priorities of tasks, then to generate more route combinations, a hybrid crossover operator based on 0-1 matrix operations was proposed. Furthermore, to improve the feasibility of individuals, a repair schedule was designed based on constraints. Meanwhile, a q-tournament selection operator was adopted so that better individuals can be kept into the next generation. Finally, experimental results showed that the proposed algorithm is feasible and effective for solving the MPDAP.
Citation: Yu Shen, Hecheng Li. A multi-strategy genetic algorithm for solving multi-point dynamic aggregation problems with priority relationships of tasks[J]. Electronic Research Archive, 2024, 32(1): 445-472. doi: 10.3934/era.2024022
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The multi-point dynamic aggregation problem (MPDAP) that arises in practical applications is characterized by a group of robots that have to cooperate in executing a set of tasks distributed over multiple locations, in which the demand for each task grows over time. To minimize the completion time of all tasks, one needs to schedule the robots and plan the routes. Hence, the problem is essentially a combinatorial optimization problem. The manuscript presented a new MPDAP in which the priority of the task was considered that is to say, some tasks must be first completed before others begin to be executed. When the tasks were located at different priority levels, some additional constraints were added to express the priorities of tasks. Since route selection of robots depends on the priorities of tasks, these additional constraints caused the presented MPDAP to be more complex than ever. To efficiently solve this problem, an improved optimization algorithm, called the multi-strategy genetic algorithm (MSGA), was developed. First of all, a two-stage hybrid matrix coding scheme was proposed based on the priorities of tasks, then to generate more route combinations, a hybrid crossover operator based on 0-1 matrix operations was proposed. Furthermore, to improve the feasibility of individuals, a repair schedule was designed based on constraints. Meanwhile, a q-tournament selection operator was adopted so that better individuals can be kept into the next generation. Finally, experimental results showed that the proposed algorithm is feasible and effective for solving the MPDAP.
In 1922, S. Banach [15] provided the concept of Contraction theorem in the context of metric space. After, Nadler [28] introduced the concept of set-valued mapping in the module of Hausdroff metric space which is one of the potential generalizations of a Contraction theorem. Let (X,d) is a complete metric space and a mapping T:X→CB(X) satisfying
H(T(x),T(y))≤γd(x,y) |
for all x,y∈X, where 0≤γ<1, H is a Hausdorff with respect to metric d and CB(X)={S⊆X:S is closed and bounded subset of X equipped with a metric d}. Then T has a fixed point in X.
In the recent past, Matthews [26] initiate the concept of partial metric spaces which is the classical extension of a metric space. After that, many researchers generalized some related results in the frame of partial metric spaces. Recently, Asadi et al. [4] introduced the notion of an M-metric space which is the one of interesting generalizations of a partial metric space. Later on, Samet et al. [33] introduced the class of mappings which known as (α,ψ)-contractive mapping. The notion of (α,ψ) -contractive mapping has been generalized in metric spaces (see more [10,12,14,17,19,25,29,30,32]).
Throughout this manuscript, we denote the set of all positive integers by N and the set of real numbers by R. Let us recall some basic concept of an M-metric space as follows:
Definition 1.1. [4] Let m:X×X→R+be a mapping on nonempty set X is said to be an M-metric if for any x,y,z in X, the following conditions hold:
(i) m(x,x)=m(y,y)=m(x,y) if and only if x=y;
(ii) mxy≤m(x,y);
(iii) m(x,y)=m(y,x);
(iv) m(x,y)−mxy≤(m(x,z)−mxz)+(m(z,y)−mz,y) for all x,y,z∈X. Then a pair (X,m) is called M-metric space. Where
mxy=min{m(x,x),m(y,y)} |
and
Mxy=max{m(x,x),m(y,y)}. |
Remark 1.2. [4] For any x,y,z in M-metric space X, we have
(i) 0≤Mxy+mxy=m(x,x)+m(y,y);
(ii) 0≤Mxy−mxy=|m(x,x)−m(y,y)|;
(iii) Mxy−mxy≤(Mxz−mxz)+(Mzy−mzy).
Example 1.3. [4] Let (X,m) be an M-metric space. Define mw, ms:X×X→R+ by:
(i)
mw(x,y)=m(x,y)−2mx,y+Mx,y, |
(ii)
ms={m(x,y)−mx,y, if x≠y0, if x=y. |
Then mw and ms are ordinary metrics. Note that, every metric is a partial metric and every partial metric is an M-metric. However, the converse does not hold in general. Clearly every M-metric on X generates a T0 topology τm on X whose base is the family of open M -balls
{Bm(x,ϵ):x∈X, ϵ>0}, |
where
Bm(x,ϵ)={y∈X:m(x,y)<mxy+ϵ} |
for all x∈X, ε>0. (see more [3,4,23]).
Definition 1.4. [4] Let (X,m) be an M-metric space. Then,
(i) A sequence {xn} in (X,m) is said to be converges to a point x in X with respect to τm if and only if
limn→∞(m(xn,x)−mxnx)=0. |
(ii) Furthermore, {xn} is said to be an M-Cauchy sequence in (X,m) if and only if
limn,m→∞(m(xn,xm)−mxnxm), and limn,m→∞(Mxn,xm−mxnxm) |
exist (and are finite).
(iii) An M-metric space (X,m) is said to be complete if every M-Cauchy sequence {xn} in (X,m) converges with respect to τm to a point x∈X such that
limn→∞m(xn,x)−mxnx=0, and limn→∞(Mxn,x−mxnx)=0. |
Lemma 1.5. [4] Let (X,m) be an M-metric space. Then:
(i) {xn} is an M-Cauchy sequence in (X,m) if and only if {xn} is a Cauchy sequence in a metric space (X,mw).
(ii) An M-metric space (X,m) is complete if and only if the metric space (X,mw) is complete. Moreover,
limn→∞mw(xn,x)=0 if and only if (limn→∞(m(xn,x)−mxnx)=0, limn→∞(Mxnx−mxnx)=0). |
Lemma 1.6. [4] Suppose that {xn} convergesto x and {yn} converges to y as n approaches to ∞ in M-metric space (X,m). Then we have
limn→∞(m(xn,yn)−mxnyn)=m(x,y)−mxy. |
Lemma 1.7. [4] Suppose that {xn} converges to xas n approaches to ∞ in M-metric space (X,m).Then we have
limn→∞(m(xn,y)−mxny)=m(x,y)−mxy for all y∈X. |
Lemma 1.8. [4] Suppose that {xn} converges to xand {xn} converges to y as n approaches to ∞ in M-metric space (X,m). Then m(x,y)=mxymoreover if m(x,x)= m(y,y), then x=y.
Definition 1.9. Let α:X×X→[0,∞). A mapping T:X→X is said to be an α-admissible mapping if for all x,y∈X
α(x,y)≥1⇒α(T(x),T(y))≥1. |
Let Ψ be the family of the (c)-comparison functions ψ:R+∪{0}→R+∪{0} which satisfy the following properties:
(i) ψ is nondecreasing,
(ii) ∑∞n=0ψn(t)<∞ for all t>0, where ψn is the n-iterate of ψ (see [7,8,10,11]).
Definition 1.10. [33] Let (X,d) be a metric space and α:X×X→[0,∞). A mapping T:X→X is called (α,ψ)-contractive mapping if for all x,y∈X, we have
α(x,y)d(T(x),T(x))≤ψ(d(x,y)), |
where ψ∈Ψ.
A subset K of an M-metric space X is called bounded if for all x∈K, there exist y∈X and r>0 such that x∈Bm(y,r). Let ¯K denote the closure of K. The set K is closed in X if and only if ¯K=K.
Definition 1.11. [31] Define Hm:CBm(X)×CBm(X)→[0,∞) by
Hm(K,L)=max{∇m(K,L),∇m(L,K)}, |
where
m(x,L)=inf{m(x,y):y∈L} and∇m(L,K)=sup{m(x,L):x∈K}. |
Lemma 1.12. [31] Let F be any nonempty set in M-metric space (X,m), then
x∈¯F if and only if m(x,F)=supa∈F{mxa}. |
Proposition 1.13. [31] Let A,B,C∈CBm(X), then
(i) ∇m(A,A)=supx∈A{supy∈Amxy},
(ii) (∇m(A,B)−supx∈Asupy∈Bmxy)≤(∇m(A,C)−infx∈Ainfz∈Cmxz)+
(∇m(C,B)−infz∈Cinfy∈Bmzy).
Proposition 1.14. [31] Let A,B,C∈CBm(X) followingare hold
(i) Hm(A,A)=∇m(A,A)=supx∈A{supy∈Amxy},
(ii) Hm(A,B)=Hm(B,A),
(iii) Hm(A,B)−supx∈Asupy∈Amxy)≤Hm(A,C)+Hm(B,C)−infx∈Ainfz∈Cmxz−infz∈Cinfy∈Bmzy.
Lemma 1.15. [31] Let A,B∈CBm(X) and h>1.Then for each x∈A, there exist at the least one y∈B such that
m(x,y)≤hHm(A,B). |
Lemma 1.16. [31] Let A,B∈CBm(X) and l>0.Then for each x∈A, there exist at least one y∈B such that
m(x,y)≤Hm(A,B)+l. |
Theorem 1.17. [31] Let (X,m) be a complete M-metric space and T:X→CBm(X). Assume that there exist h∈(0,1) such that
Hm(T(x),T(y))≤hm(x,y), | (1.1) |
for all x,y∈X. Then T has a fixed point.
Proposition 1.18. [31] Let T:X→CBm(X) be a set-valued mapping satisfying (1.1) for all x,y inan M-metric space X. If z∈T(z) for some z in Xsuch that m(x,x)=0 for x∈T(z).
We start with the following definition:
Definition 2.1. Assume that Ψ is a family of non-decreasing functions ϕM:R+→R+ such that
(i) ∑+∞nϕnM(x)<∞ for every x>0 where ϕnM is a nth-iterate of ϕM,
(ii) ϕM(x+y)≤ϕM(x)+ϕM(y) for all x,y∈R+,
(iii) ϕM(x)<x, for each x>0.
Remark 2.2. If ∑αn|n=∞ =0 is a convergent series with positive terms then there exists a monotonic sequence (βn)|n=∞ such that βn|n=∞=∞ and ∑αnβn|n=∞=0 converges.
Definition 2.3. Let (X,m) be an M-metric pace. A self mapping T:X→X is called (α∗,ϕM)-contraction if there exist two functions α∗:X×X→[0,∞) and ϕM∈Ψ such that
α∗(x,y)m(T(x),T(y))≤ϕM(m(x,y)), |
for all x,y∈X.
Definition 2.4. Let (X,m) be an M-metric space. A set-valued mapping T:X→CBm(X) is said to be (α∗,ϕM)-contraction if for all x,y∈X, we have
α∗(x,y)Hm(T(x),T(x))≤ϕM(m(x,y)), | (2.1) |
where ϕM∈Ψ and α∗:X×X→[0,∞).
A mapping T is called α∗-admissible if
α∗(x,y)≥1⇒α∗(a1,b1)≥1 |
for each a1∈T(x) and b1∈T(y).
Theorem 2.5. Let (X,m) be a complete M-metric space.Suppose that (α∗,ϕM) contraction and α∗-admissible mapping T:X→CBm(X)satisfies the following conditions:
(i) there exist x0∈X such that α∗(x0,a1)≥1 for each a1∈T(x0),
(ii) if {xn}∈X is a sequence such that α∗(xn,xn+1)≥1 for all n and {xn}→x∈X as n→∞, then α∗(xn,x)≥1 for all n∈N. Then T has a fixed point.
Proof. Let x1∈T(x0) then by the hypothesis (i) α∗(x0,x1)≥1. From Lemma 1.16, there exist x2∈T(x1) such that
m(x1,x2)≤Hm(T(x0),T(x1))+ϕM(m(x0,x1)). |
Similarly, there exist x3∈T(x2) such that
m(x2,x3)≤Hm(T(x1),T(x2))+ϕ2M(m(x0,x1)). |
Following the similar arguments, we obtain a sequence {xn}∈X such that there exist xn+1∈T(xn) satisfying the following inequality
m(xn,xn+1)≤Hm(T(xn−1),T(xn))+ϕnM(m(x0,x1)). |
Since T is α∗-admissible, therefore α∗(x0,x1)≥1⇒α∗(x1,x2)≥1. Using mathematical induction, we get
α∗(xn,xn+1)≥1. | (2.2) |
By (2.1) and (2.2), we have
m(xn,xn+1)≤Hm(T(xn−1),T(xn))+ϕnM(m(x0,x1))≤α∗(xn,xn+1)Hm(T(xn−1),T(xn))+ϕnM(m(x0,x1))≤ϕM(m(xn−1,xn))+ϕnM(m(x0,x1))=ϕM[(m(xn−1,xn))+ϕn−1M(m(x0,x1))]≤ϕM[Hm(T(xn−2),T(xn−1))+ϕn−1M(m(x0,x1))]≤ϕM[α∗(xn−1,xn)Hm(T(xn−1),T(xn))+ϕn−1M(m(x0,x1))]≤ϕM[ϕM(m(xn−2,xn−1))+ϕn−1M(m(x0,x1))+ϕn−1M(m(x0,x1))]≤ϕ2M(m(xn−2,xn−1))+2ϕnM(m(x0,x1)).... |
m(xn,xn+1)≤ϕnM(m(x0,x1))+nϕnM(m(x0,x1))m(xn,xn+1)≤(n+1)ϕnM(m(x0,x1)). |
Let us assume that ϵ>0, then there exist n0∈N such that
∑n≥n0(n+1)ϕnM(m(x0,x1))<ϵ. |
By the Remarks (1.2) and (2.2), we get
limn→∞m(xn,xn+1)=0. |
Using the above inequality and (m2), we deduce that
limn→∞m(xn,xn)=limn→∞min{m(xn,xn),m(xn+1,xn+1)}=limn→∞mxnxn+1≤limn→∞m(xn,xn+1)=0. |
Owing to limit, we have limn→∞m(xn,xn)=0,
limn,m→∞mxnxm=0. |
Now, we prove that {xn} is M-Cauchy in X. For m,n in N with m>n and using the triangle inequality of an M-metric we get
m(xn,xm)−mxnxm≤m(xn,xn+1)−mxnxn+1+m(xn+1,xm)−mxn+1xm≤m(xn,xn+1)−mxnxn+1+m(xn+1,xn+2)−mxn+1xn+1+m(xn+2,xm)−mxn+2xm≤m(xn,xn+1)−mxnxn+1+m(xn+1,xn+2)−mxn+1xn+2+⋅⋅⋅+m(xm−1,xm)−mxm−1xm≤m(xn,xn+1)+m(xn+1,xn+2)+⋅⋅⋅+m(xm−1,xm)=m−1∑r=nm(xr,xr+1)≤m−1∑r=n(r+1)ϕrM(m(x0,x1))≤m−1∑r≥n0(r+1)ϕrM(m(x0,x1))≤m−1∑r≥n0(r+1)ϕrM(m(x0,x1))<ϵ. |
m(xn,xm)−mxnxm→0, as n→∞, we obtain limm,n→∞(Mxnxm−mxnxm)=0. Thus {xn} is a M-Cauchy sequence in X. Since (X,m) is M-complete, there exist x⋆∈X such that
limn→∞(m(xn,x⋆)−mxnx⋆)=0 andlimn→∞(Mxnx⋆−mxnx⋆)=0. |
Also, limn→∞m(xn,xn)=0 gives that
limn→∞m(xn,x⋆)=0 and limn→∞Mxnx⋆=0, | (2.3) |
limn→∞{max(m(xn,x⋆),m(x⋆,x⋆))}=0, |
which implies that m(x⋆,x⋆)=0 and hence we obtain mx⋆T(x⋆)=0. By using (2.1) and (2.3) with
limn→∞α∗(xn,x⋆)≥1. |
Thus,
limn→∞Hm(T(xn),T(x⋆))≤limn→∞ϕM(m(xn,x⋆))≤limn→∞m(xn,x⋆). |
limn→∞Hm(T(xn),T(x⋆))=0. | (2.4) |
Now from (2.3), (2.4), and xn+1∈T(xn), we have
m(xn+1,T(x⋆))≤Hm(T(xn),T(x⋆))=0. |
Taking limit as n→∞ and using (2.4), we obtain that
limn→∞m(xn+1,T(x⋆))=0. | (2.5) |
Since mxn+1T(x⋆)≤m(xn+1,T(x⋆)) which gives
limn→∞mxn+1T(x⋆)=0. | (2.6) |
Using the condition (m4), we obtain
m(x⋆,T(x⋆))−supy∈T(x⋆)mx⋆y≤m(x⋆,T(x⋆))−mx⋆,T(x⋆)≤m(x⋆,xn+1)−mx⋆xn+1+m(xn+1,T((x⋆))−mxn+1T(x⋆). |
Applying limit as n→∞ and using (2.3) and (2.6), we have
m(x⋆,T(x⋆))≤supy∈T(x⋆)mx⋆y. | (2.7) |
From (m2), mx⋆y≤m(x⋆y) for each y∈T(x⋆) which implies that
mx⋆y−m(x⋆,y)≤0. |
Hence,
sup{mx⋆y−m(x⋆,y):y∈T(x⋆)}≤0. |
Then
supy∈T(x⋆)mx⋆y−infy∈T(x⋆)m(x⋆,y)≤0. |
Thus
supy∈T(x⋆)mx⋆y≤m(x⋆,T(x⋆)). | (2.8) |
Now, from (2.7) and (2.8), we obtain
m(T(x⋆),x⋆)=supy∈T(x⋆)mx⋆y. |
Consequently, owing to Lemma (1.12), we have x⋆∈¯T(x⋆)=T(x⋆).
Corollary 2.6. Let (X,m) be a complete M-metric space and anself mapping T:X→X an α∗-admissible and (α∗,ϕM)-contraction mapping. Assume that thefollowing properties hold:
(i) there exists x0∈X such that α∗(x0,T(x0))≥1,
(ii) either T is continuous or for any sequence {xn}∈X with α∗(xn,xn+1)≥1 for all n∈N and {xn}→x as n → ∞, we have α∗(xn,x)≥1 for all n∈N. Then T has a fixed point.
Some fixed point results in ordered M-metric space.
Definition 2.7. Let (X,⪯) be a partially ordered set. A sequence {xn}⊂X is said to be non-decreasing if xn⪯xn+1 for all n.
Definition 2.8. [16] Let F and G be two nonempty subsets of partially ordered set (X,⪯). The relation between F and G is defined as follows: F≺1G if for every x∈F, there exists y∈G such that x⪯y.
Definition 2.9. Let (X,m,⪯) be a partially ordered set on M-metric. A set-valued mapping T:X→CBm(X) is said to be ordered (α∗,ϕM)-contraction if for all x,y∈X, with x⪯y we have
Hm(T(x),T(y))≤ϕM(m(x,y)) |
where ϕM∈Ψ. Suppose that α∗:X×X→[0,∞) is defined by
α∗(x,y)={1 if Tx≺1Ty0 otherwise. |
A mapping T is called α∗-admissible if
α(x,y)≥1⇒α∗(a1,b1)≥1, |
for each a1∈T(x) and b1∈T(y).
Theorem 2.10. Let (X,m,⪯) be a partially orderedcomplete M-metric space and T:X→CBm(X) an α∗-admissible ordered (α∗,ϕM)-contraction mapping satisfying the following conditions:
(i) there exist x0∈X such that {x0}≺1{T(x0)}, α∗(x0,a1)≥1 for each a1∈T(x0),
(ii) for every x,y∈X, x⪯y implies T(x)≺1T(y),
(iii) If {xn}∈X is a non-decreasing sequence such that xn⪯xn+1 for all n and {xn}→x∈X as n →∞ gives xn⪯x for all n∈N. Then T has a fixed point.
Proof. By assumption (i) there exist x1∈T(x0) such that x0⪯x1 and α∗(x0,x1)≥1. By hypothesis (ii), T(x0)≺1T(x1). Let us assume that there exist x2∈T(x1) such that x1⪯x2 and we have the following
m(x1,x2)≤Hm(T(x0),T(x1))+ϕM(m(x0,x1)). |
In the same way, there exist x3∈T(x2) such that x2⪯x3 and
m(x2,x3)≤Hm(T(x1),T(x2))+ϕ2M(m(x0,x1)). |
Following the similar arguments, we have a sequence {xn}∈X and xn+1∈T(xn) for all n≥0 satisfying x0⪯x1⪯x2⪯x3⪯...xn⪯xn+1. The proof is complete follows the arguments given in Theorem 2.5.
Example 2.11. Let X=[16,1] be endowed with an M -metric given by m(x,y)=x+y2. Define T:X→CBm(X) by
T(x)={{12x+16,14}, if x=16{x2,x3}, if 14≤x≤13{23,56}, if 12≤x≤1. |
Define a mapping α∗:X×X→[0,∞) by
α∗(x,y)={1 if x,y∈[14,13]0 otherwise. |
Let ϕM:R+→R+ be given by ϕM(t)=1710 where ϕM∈Ψ, for x,y∈X. If x=16, y=14 then m(x,y)=524, and
Hm(T(x),T(y))=Hm({312,14},{18,112})=max(∇m({312,14},{18,112}),∇m({18,112},{312,14}))=max{316,212}=316≤ϕM(t)m(x,y). |
If x=13, y=12 then m(x,y)=512, and
Hm(T(x),T(y))=Hm({16,19},{23,1})=max(∇m({16,19},{23,1}),∇m({23,1},{16,19}))=max{1736,718}=1736≤ϕM(t)m(x,y). |
If x=16, y=1, then m(x,y)=712 and
Hm(T(x),T(y))=Hm({312,14},{23,56})=max(∇m({312,14},{23,56}),∇m({23,56},{312,14}))=max{1124,1324}=1324≤ϕM(t)m(x,y). |
In all cases, T is (α∗,ϕM)-contraction mapping. If x0=13, then T(x0)={x2,x3}.Therefore α∗(x0,a1)≥1 for every a1∈T(x0). Let x,y∈X be such that α∗(x,y)≥1, then x,y∈[x2,x3] and T(x)={x2,x3} and T(y)= {x2,x3} which implies that α∗(a1,b1)≥1 for every a1∈T(x) and b1∈T(x). Hence T is α∗-admissble.
Let {xn}∈X be a sequence such that α∗(xn,xn+1)≥1 for all n in N and xn converges to x as n converges to ∞, then xn∈[x2,x3]. By definition of α∗ -admissblity, therefore x∈[x2,x3] and hence α∗(xn,x)≥1. Thus all the conditions of Theorem 2.3 are satisfied. Moreover, T has a fixed point.
Example 2.12. Let X={(0,0),(0,−15),(−18,0)} be the subset of R2 with order ⪯ defined as: For (x1,y1),(x2,y2)∈X, (x1,y1)⪯(x2,y2) if and only if x1≤x2, y1≤y2. Let m:X×X→R+ be defined by
m((x1,y1),(x2,y2))=|x1+x22|+|y1+y22|, for x=(x1,y1), y=(x2,y2)∈X. |
Then (X,m) is a complete M-metric space. Let T:X→CBm(X) be defined by
T(x)={{(0,0)}, if x=(0,0),{(0,0),(−18,0)}, if x∈(0,−15){(0,0)}, if x∈(−18,0). |
Define a mapping α∗:X×X→[0,∞) by
α∗(x,y)={1 if x,y∈X0 otherwise. |
Let ϕM:R+→R+ be given by ϕM(t)=12. Obviously, ϕM∈Ψ. For x,y∈X,
if x=(0,−15) and y=(0,0), then Hm(T(x),T(y))=0 and m(x,y)=110 gives that
Hm(T(x),T(y))=Hm({(0,0),(−18,0)},{(0,0)})=max(∇m({(0,0),(−18,0)},{(0,0)}),∇m({(0,0)},{(0,0),(−18,0)}))=max{0,0}=0≤ϕM(t)m(x,y). |
If x=(−18,0) and y=(0,0) then Hm(T(x),T(y))=0, and m(x,y)=116 implies that
Hm(T(x),T(y))≤ϕM(t)m(x,y). |
If x=(0,0) and y=(0,0) then Hm(T(x),T(y))=0, and m(x,y)=0 gives
Hm(T(x),T(y))≤ϕM(t)m(x,y). |
If x=(0,−15) and y=(0,−15) then Hm(T(x),T(y))=0, and m(x,y)=15 implies that
Hm(T(x),T(y))≤ϕM(t)m(x,y). |
If x=(0,−18) and y=(0,−18) then Hm(T(x),T(y))=0, and m(x,y)=18 gives that
Hm(T(x),T(y))≤ϕM(t)m(x,y). |
Thus all the condition of Theorem 2.10 satisfied. Moreover, (0,0) is the fixed point of T.
In this section, we present an application of our result in homotopy theory. We use the fixed point theorem proved for set-valued (α∗,ϕM)-contraction mapping in the previous section, to establish the result in homotopy theory. For further study in this direction, we refer to [6,35].
Theorem 3.1. Suppose that (X,m) is a complete M-metricspace and A and B are closed and open subsets of X respectively, suchthat A⊂B. For a,b∈R, let T:B×[a,b]→CBm(X) be aset-valued mapping satisfying the following conditions:
(i) x∉T(y,t) for each y∈B/Aand t∈[a,b],
(ii) there exist ϕM∈Ψ and α∗:X×X→[0,∞) such that
α∗(x,y)Hm(T(x,t),T(y,t))≤ϕM(m(x,y)), |
for each pair (x,y)∈B×B and t∈[a,b],
(iii) there exist a continuous function Ω:[a,b]→R such that for each s,t∈[a,b] and x∈B, we get
Hm(T(x,s),T(y,t))≤ϕM|Ω(s)−Ω(t)|, |
(iv) if x⋆∈T(x⋆,t),then T(x⋆,t)={x⋆},
(v) there exist x0 in X such that x0∈T(x0,t),
(vi) a function ℜ:[0,∞)→[0,∞) defined by ℜ(x)=x−ϕM(x) is strictly increasing and continuous if T(.,t⊺) has a fixed point in B for some t⊺∈[a,b], then T(.,t) has afixed point in A for all t∈[a,b]. Moreover, for a fixed t∈[a,b], fixed point is unique provided that ϕM(t)=12t where t>0.
Proof. Define a mapping α∗:X×X→[0,∞) by
α∗(x,y)={1 if x∈T(x,t), y∈T(y,t) 0 otherwise. |
We show that T is α∗-admissible. Note that α∗(x,y)≥1 implies that x∈T(x,t) and y∈T(y,t) for all t∈[a,b]. By hypothesis (iv), T(x,t)={x} and T(y,t)={y}. It follows that T is α∗ -admissible. By hypothesis (v), there exist x0∈X such that x0∈(x0,t) for all t, that is α∗(x0,x0)≥1. Suppose that α∗(xn,xn+1)≥1 for all n and xn converges to q as n approaches to ∞ and xn∈T(xn,t) and xn+1∈T(xn+1,t) for all n and t∈[a,b] which implies that q∈T(q,t) and thus α∗(xn,q)≥1. Set
D={t∈[a,b]: x∈T(x,t) for x∈A}. |
So T(.,t⊺) has a fixed point in B for some t⊺∈[a,b], there exist x∈B such that x∈T(x,t). By hypothesis (i) x∈T(x,t) for t∈[a,b] and x∈A so D≠ϕ. Now we now prove that D is open and close in [a,b]. Let t0∈D and x0∈A with x0∈T(x0,t0). Since A is open subset of X, ¯Bm(x0,r)⊆A for some r>0. For ϵ=r+mxx0−ϕ(r+mxx0) and a continuous function Ω on [a,b], there exist δ>0 such that
ϕM|Ω(t)−Ω(t0)|<ϵ for all t∈(t0−δ,t0+δ). |
If t∈(t0−δ,t0+δ) for x∈Bm(x0,r)={x∈X:m(x0,x)≤mx0x+r} and l∈T(x,t), we obtain
m(l,x0)=m(T(x,t),x0)=Hm(T(x,t),T(x0,t0)). |
Using the condition (iii) of Proposition 1.13 and Proposition 1.18, we have
m(l,x0)≤Hm(T(x,t),T(x0,t0))+Hm(T(x,t),T(x0,t0)) | (2.9) |
as x∈T(x0,t0) and x∈Bm(x0,r)⊆A⊆B, t0∈[a,b] with α∗(x0,x0)≥1. By hypothesis (ii), (iii) and (2.9)
m(l,x0)≤ϕM|Ω(t)−Ω(t0)|+α∗(x0,x0)Hm(T(x,t),T(x0,t0))≤ϕM|Ω(t)−Ω(t0)|+ϕM(m(x,x0))≤ϕM(ϵ)+ϕM(mxx0+r)≤ϕM(r+mxx0−ϕM(r+mxx0))+ϕM(mxx0+r)<r+mxx0−ϕM(r+mxx0)+ϕM(mxx0+r)=r+mxx0. |
Hence l∈¯Bm(x0,r) and thus for each fixed t∈(t0−δ,t0+δ), we obtain T(x,t)⊂¯Bm(x0,r) therefore T:¯Bm(x0,r)→CBm(¯Bm(x0,r)) satisfies all the assumption of Theorem (3.1) and T(.,t) has a fixed point ¯Bm(x0,r)=Bm(x0,r)⊂B. But by assumption of (i) this fixed point belongs to A. So (t0−δ,t0+δ)⊆D, thus D is open in [a,b]. Next we prove that D is closed. Let a sequence {tn}∈D with tn converges to t0∈[a,b] as n approaches to ∞. We will prove that t0 is in D.
Using the definition of D, there exist {tn} in A such that xn∈T(xn,tn) for all n. Using Assumption (iii)–(v), and the condition (iii) of Proposition 1.13, and an outcome of the Proposition 1.18, we have
m(xn,xm)≤Hm(T(xn,tn),T(xm,tm))≤Hm(T(xn,tn),T(xn,tm))+Hm(T(xn,tm),T(xm,tm))≤ϕM|Ω(tn)−Ω(tm)|+α∗(xn,xm)Hm(T(xn,tm),T(xm,tm))≤ϕM|Ω(tn)−Ω(tm)|+ϕM(m(xn,xm))⇒m(xn,xm)−ϕM(m(xn,xm))≤ϕM|Ω(tn)−Ω(tm)|⇒ℜ(m(xn,xm))≤ϕM|Ω(tn)−Ω(tm)|ℜ(m(xn,xm))<|Ω(tn)−Ω(tm)|m(xn,xm)<1ℜ|Ω(tn)−Ω(tm)|. |
So, continuity of 1ℜ, ℜ and convergence of {tn}, taking the limit as m,n→∞ in the last inequality, we obtain that
limm,n→∞m(xn,xm)=0. |
Sine mxnxm≤m(xn,xm), therefore
limm,n→∞mxnxm=0. |
Thus, we have limn→∞m(xn,xn)=0=limm→∞m(xm,xm). Also,
limm,n→∞(m(xn,xm)−mxnxm)=0, limm,n→∞(Mxnxm−mxnxm). |
Hence {xn} is an M-Cauchy sequence. Using Definition 1.4, there exist x∗ in X such that
limn→∞(m(xn,x∗)−mxnx∗)=0 and limn→∞(Mxnx∗−mxnx∗)=0. |
As limn→∞m(xn,xn)=0, therefore
limn→∞m(xn,x∗)=0 and limn→∞Mxnx∗=0. |
Thus, we have m(x,x∗)=0. We now show that x∗∈T(x∗,t∗). Note that
m(xn,T(x∗,t∗))≤Hm(T(xn,tn),T(x∗,t∗))≤Hm(T(xn,tn),T(xn,t∗))+Hm(T(xn,t∗),T(x∗,t∗))≤ϕM|Ω(tn)−Ω(t∗)|+α∗(xn,t∗)Hm(T(xn,t∗),T(x∗,t∗))≤ϕM|Ω(tn)−Ω(t∗)|+ϕM(m(xn,t∗)). |
Applying the limit n→∞ in the above inequality, we have
limn→∞m(xn,T(x∗,t∗))=0. |
Hence
limn→∞m(xn,T(x∗,t∗))=0. | (2.10) |
Since m(x∗,x∗)=0, we obtain
supy∈T(x∗,t∗)mx∗y=supy∈T(x∗,t∗)min{m(x∗,x∗),m(y,y)}=0. | (2.11) |
From above two inequalities, we get
m(x∗,T(x∗,t∗))=supy∈T(x∗,t∗)mx∗y. |
Thus using Lemma 1.12 we get x∗∈T(x∗,t∗). Hence x∗∈A. Thus x∗∈D and D is closed in [a,b], D=[a,b] and D is open and close in [a,b]. Thus T(.,t) has a fixed point in A for all t∈[a,b]. For uniqueness, t∈[a,b] is arbitrary fixed point, then there exist x∈A such that x∈T(x,t). Assume that y is an other point of T(x,t), then by applying condition 4, we obtain
m(x,y)=Hm(T(x,t),T(y,t))≤αM(x,y)Hm(T(x,t),T(y,t))≤ϕM(m(x,y)). |
ForϕM(t)=12t, where t>0, the uniqueness follows.
In this section we will apply the previous theoretical results to show the existence of solution for some integral equation. For related results (see [13,20]). We see for non-negative solution of (3.1) in X=C([0,δ],R). Let X=C([0,δ],R) be a set of continuous real valued functions defined on [0,δ] which is endowed with a complete M-metric given by
m(x,y)=supt∈[0,δ](|x(t)+x(t)2|) for all x,y∈X. |
Consider an integral equation
v1(t)=ρ(t)+∫δ0h(t,s)J(s,v1(s))ds for all 0≤t≤δ. | (3.1) |
Define g:X→X by
g(x)(t)=ρ(t)+∫δ0h(t,s)J(s,x(s))ds |
where
(i) for δ>0, (a) J:[0,δ]×R→R, (b) h:[0,δ]×[0,δ]→[0,∞), (c) ρ:[0,δ]→R are all continuous functions
(ii) Assume that σ:X×X→R is a function with the following properties,
(iii) σ(x,y)≥0 implies that σ(T(x),T(y))≥0,
(iv) there exist x0∈X such that σ(x0,T(x0))≥0,
(v) if {xn}∈X is a sequence such that σ(xn,xn+1)≥0 for all n∈N and xn→x as n→∞, then σ(x,T(x))≥0
(vi)
supt∈[0,δ]∫δ0h(t,s)ds≤1 |
where t∈[0,δ], s∈R,
(vii) there exist ϕM∈Ψ, σ(y,T(y))≥1 and σ(x,T(x))≥1 such that for each t∈[0,δ], we have
|J(s,x(t))+J(s,y(t))|≤ϕM(|x+y|). | (3.3) |
Theorem 4.1. Under the assumptions (i)−(vii) theintegral Eq (3.1) has a solution in {X=C([0,δ],R) for all t∈[0,δ]}.
Proof. Using the condition (vii), we obtain that
m(g(x),g(y))=|g(x)(t)+g(y)(t)2|=|∫δ0h(t,s)[J(s,x(s))+J(s,y(s))2]ds|≤∫δ0h(t,s)|J(s,x(s))+J(s,y(s))2|ds≤∫δ0h(t,s)[ϕM|x(s)+y(s)2|]ds≤(supt∈[0,δ]∫δ0h(t,s)ds)(ϕM|x(s)+y(s)2|)≤ϕM(|x(s)+y(s)2|) |
m(g(x),g(y))≤ϕ(m(x,y)) |
Define α∗:X×X→[0,+∞) by
α∗(x,y)={1 if σ(x,y)≥0 0 otherwise |
which implies that
m(g(x),g(y))≤ϕM(m(x,y)). |
Hence all the assumption of the Corollary 2.6 are satisfied, the mapping g has a fixed point in X=C([0,δ],R) which is the solution of integral Eq (3.1).
In this study we develop some set-valued fixed point results based on (α∗,ϕM)-contraction mappings in the context of M-metric space and ordered M-metric space. Also, we give examples and applications to the existence of solution of functional equations and homotopy theory.
The authors declare that they have no competing interests.
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