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Mathematics, Volume 7, Issue 9 (September 2019) – 106 articles

Cover Story (view full-size image): The time–space–fractional diffusion equation constitutes a natural and far-reaching extension of the popular class of exponential market models. Among other things, it governs the log-normal and the spectrally negative Lévy-stable models for asset returns, and covers several non-trivial phenomena such as price jumps, memory, and subtle volatility patterns. View this paper.
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17 pages, 310 KiB  
Article
Existence of Solutions for Nonhomogeneous Choquard Equations Involving p-Laplacian
by Xiaoyan Shi, Yulin Zhao and Haibo Chen
Mathematics 2019, 7(9), 871; https://doi.org/10.3390/math7090871 - 19 Sep 2019
Cited by 2 | Viewed by 2508
Abstract
This paper is devoted to investigating a class of nonhomogeneous Choquard equations with perturbation involving p-Laplacian. Under suitable hypotheses about the perturbation term, the existence of at least two nontrivial solutions for the given problems is obtained using Nehari manifold and minimax methods. [...] Read more.
This paper is devoted to investigating a class of nonhomogeneous Choquard equations with perturbation involving p-Laplacian. Under suitable hypotheses about the perturbation term, the existence of at least two nontrivial solutions for the given problems is obtained using Nehari manifold and minimax methods. Full article
(This article belongs to the Special Issue Nonlinear Functional Analysis and Its Applications)
8 pages, 432 KiB  
Article
Classification of the State of Manufacturing Process under Indeterminacy
by Muhammad Aslam and Osama Hasan Arif
Mathematics 2019, 7(9), 870; https://doi.org/10.3390/math7090870 - 19 Sep 2019
Cited by 2 | Viewed by 2293
Abstract
In this paper, the diagnosis of the manufacturing process under the indeterminate environment is presented. The similarity measure index was used to find the probability of the in-control and the out-of-control of the process. The average run length (ARL) was also computed for [...] Read more.
In this paper, the diagnosis of the manufacturing process under the indeterminate environment is presented. The similarity measure index was used to find the probability of the in-control and the out-of-control of the process. The average run length (ARL) was also computed for various values of specified parameters. An example from the Juice Company is considered under the indeterminate environment. From this study, it is concluded that the proposed diagnosis scheme under the neutrosophic statistics is quite simple and effective for the current state of the manufacturing process under uncertainty. The use of the proposed method under the uncertainty environment in the Juice Company may eliminate the non-conforming items and alternatively increase the profit of the company. Full article
(This article belongs to the Special Issue New Challenges in Neutrosophic Theory and Applications)
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<p>The operational process of the proposed method.</p>
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18 pages, 291 KiB  
Article
Syzygies, Betti Numbers, and Regularity of Cover Ideals of Certain Multipartite Graphs
by A. V. Jayanthan and Neeraj Kumar
Mathematics 2019, 7(9), 869; https://doi.org/10.3390/math7090869 - 19 Sep 2019
Cited by 2 | Viewed by 2454
Abstract
Let G be a finite simple graph on n vertices. Let J G K [ x 1 , , x n ] be the cover ideal of G. In this article, we obtain syzygies, Betti numbers, and Castelnuovo–Mumford regularity of [...] Read more.
Let G be a finite simple graph on n vertices. Let J G K [ x 1 , , x n ] be the cover ideal of G. In this article, we obtain syzygies, Betti numbers, and Castelnuovo–Mumford regularity of J G s for all s 1 for certain classes of graphs G. Full article
(This article belongs to the Special Issue Current Trends on Monomial and Binomial Ideals)
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<p><math display="inline"><semantics> <mrow> <msub> <mi>K</mi> <mrow> <msub> <mi>U</mi> <mn>1</mn> </msub> <mo>,</mo> <mi>V</mi> </mrow> </msub> <mo>∪</mo> <msub> <mi>K</mi> <mrow> <msub> <mi>U</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>V</mi> <mn>2</mn> </msub> </mrow> </msub> </mrow> </semantics></math>.</p>
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25 pages, 444 KiB  
Article
Algebraic Properties of Arbitrage: An Application to Additivity of Discount Functions
by Salvador Cruz Rambaud
Mathematics 2019, 7(9), 868; https://doi.org/10.3390/math7090868 - 19 Sep 2019
Cited by 2 | Viewed by 2558
Abstract
Background: This paper aims to characterize the absence of arbitrage in the context of the Arbitrage Theory proposed by Kreps (1981) and Clark (2000) which involves a certain number of well-known financial markets. More specifically, the framework of this model is a linear [...] Read more.
Background: This paper aims to characterize the absence of arbitrage in the context of the Arbitrage Theory proposed by Kreps (1981) and Clark (2000) which involves a certain number of well-known financial markets. More specifically, the framework of this model is a linear (topological) space X in which a (convex) cone C defines a vector ordering. There exist markets for only some of the contingent claims of X which assign a price p i to the marketed claim m i . The main purpose of this paper is to provide some novel algebraic characterizations of the no arbitrage condition and specifically to derive the decomposability of discount functions with this approach. Methods: Traditionally, this topic has been focused from a topological or probabilistic point of view. However, in this manuscript the treatment of this topic has been by using purely algebraic tools. Results: We have characterized the absence of arbitrage by only using algebraic concepts, properties and structures. Thus, we have divided these characterizations into those concerning the preference relation and those involving the cone. Conclusion: This paper has provided some novel algebraic properties of the absence of arbitrage by assuming the most general setting. The additivity of discount functions has been derived as a particular case of the general theory. Full article
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<p>Structure of <a href="#sec2-mathematics-07-00868" class="html-sec">Section 2</a>, <a href="#sec3-mathematics-07-00868" class="html-sec">Section 3</a> and <a href="#sec4-mathematics-07-00868" class="html-sec">Section 4</a>. Source: Own elaboration.</p>
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<p>Triangular arbitrage. Source: [<a href="#B14-mathematics-07-00868" class="html-bibr">14</a>].</p>
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<p>Diagram with the main sets in the arbitrage theory. Source: Own elaboration.</p>
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<p>In yellow, elements in <span class="html-italic">M</span> with a unique (positive) price not in <span class="html-italic">C</span>. In orange, elements in <math display="inline"><semantics> <mrow> <mi>C</mi> <mo>∩</mo> <mi>M</mi> </mrow> </semantics></math> with a unique (positive) price. In green, elements in <math display="inline"><semantics> <mrow> <mi>C</mi> <mo>∩</mo> <mi>F</mi> </mrow> </semantics></math> with a unique (negative or null) price. In blue, elements in <math display="inline"><semantics> <mrow> <mi>C</mi> <mo>∩</mo> <mi>F</mi> </mrow> </semantics></math> with infinite prices. In pink, elements in <span class="html-italic">F</span> with infinite prices not in <span class="html-italic">C</span>. In white, elements in <span class="html-italic">F</span> with a unique (negative or null) price. Source: Own elaboration.</p>
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<p>In yellow, elements in <span class="html-italic">M</span> with a unique (positive) price. In orange, elements in <math display="inline"><semantics> <mrow> <mi>C</mi> <mo>∩</mo> <mi>M</mi> </mrow> </semantics></math> with a unique (positive) price. In white, elements in <span class="html-italic">F</span> with a unique (negative or null) price. Source: Own elaboration.</p>
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<p>Indifference lines (case in which <math display="inline"><semantics> <mrow> <mi>I</mi> <mo>=</mo> <mo>{</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>}</mo> </mrow> </semantics></math>). Source: Own elaboration.</p>
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<p>In yellow, elements in <span class="html-italic">M</span> with a unique (positive) price. In orange, elements in <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>∩</mo> <mi>M</mi> </mrow> </semantics></math> with a unique (positive) price. In white, elements in <span class="html-italic">F</span> with a unique (negative or null) price. Source: Own elaboration.</p>
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<p>In yellow, elements in <span class="html-italic">M</span> with a unique (positive) price. In orange, elements in <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>(</mo> <mi>a</mi> <mo>)</mo> <mo>∩</mo> <mi>M</mi> </mrow> </semantics></math> with a unique (positive) price. In white, elements in <span class="html-italic">F</span> with a unique (negative or null) price. Source: Own elaboration.</p>
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<p>Additivity of the discount function <math display="inline"><semantics> <mrow> <mi>F</mi> <mo>(</mo> <mi>t</mi> <mo>,</mo> <mi>a</mi> <mo>)</mo> </mrow> </semantics></math>. Source: Own elaboration.</p>
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<p>Neighborhood of a point in the topological space. Source: Own elaboration.</p>
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21 pages, 823 KiB  
Article
A New Global Optimization Algorithm for a Class of Linear Fractional Programming
by X. Liu, Y.L. Gao, B. Zhang and F.P. Tian
Mathematics 2019, 7(9), 867; https://doi.org/10.3390/math7090867 - 19 Sep 2019
Cited by 29 | Viewed by 3031
Abstract
In this paper, we propose a new global optimization algorithm, which can better solve a class of linear fractional programming problems on a large scale. First, the original problem is equivalent to a nonlinear programming problem: It introduces p auxiliary variables. At the [...] Read more.
In this paper, we propose a new global optimization algorithm, which can better solve a class of linear fractional programming problems on a large scale. First, the original problem is equivalent to a nonlinear programming problem: It introduces p auxiliary variables. At the same time, p new nonlinear equality constraints are added to the original problem. By classifying the coefficient symbols of all linear functions in the objective function of the original problem, four sets are obtained, which are I i + , I i , J i + and J i . Combined with the multiplication rule of real number operation, the objective function and constraint conditions of the equivalent problem are linearized into a lower bound linear relaxation programming problem. Our lower bound determination method only needs e i T x + f i 0 , and there is no need to convert molecules to non-negative forms in advance for some special problems. A output-space branch and bound algorithm based on solving the linear programming problem is proposed and the convergence of the algorithm is proved. Finally, in order to illustrate the feasibility and effectiveness of the algorithm, we have done a series of numerical experiments, and show the advantages and disadvantages of our algorithm by the numerical results. Full article
(This article belongs to the Special Issue Fixed Point, Optimization, and Applications)
15 pages, 3796 KiB  
Article
Nonlinear Operators as Concerns Convex Programming and Applied to Signal Processing
by Anantachai Padcharoen and Pakeeta Sukprasert
Mathematics 2019, 7(9), 866; https://doi.org/10.3390/math7090866 - 19 Sep 2019
Cited by 8 | Viewed by 2694
Abstract
Splitting methods have received a lot of attention lately because many nonlinear problems that arise in the areas used, such as signal processing and image restoration, are modeled in mathematics as a nonlinear equation, and this operator is decomposed as the sum of [...] Read more.
Splitting methods have received a lot of attention lately because many nonlinear problems that arise in the areas used, such as signal processing and image restoration, are modeled in mathematics as a nonlinear equation, and this operator is decomposed as the sum of two nonlinear operators. Most investigations about the methods of separation are carried out in the Hilbert spaces. This work develops an iterative scheme in Banach spaces. We prove the convergence theorem of our iterative scheme, applications in common zeros of accretive operators, convexly constrained least square problem, convex minimization problem and signal processing. Full article
(This article belongs to the Special Issue Iterative Methods for Solving Nonlinear Equations and Systems)
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<p>From top to bottom: Original signal, observation data, recovered signal by Algorithm 2 and SPGA with <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mn>4096</mn> <mo>,</mo> <mspace width="0.166667em"/> <mi>M</mi> <mo>=</mo> <mn>1024</mn> </mrow> </semantics></math> and 10 spikes, respectively.</p>
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<p>Comparison MSE of two algorithms for recovered signal with <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mn>4096</mn> <mo>,</mo> <mspace width="0.166667em"/> <mi>M</mi> <mo>=</mo> <mn>1024</mn> </mrow> </semantics></math> and 10 spikes, respectively.</p>
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<p>From top to bottom: Original signal, observation data, recovered signal by Algorithm 2 and SPGA with <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mn>4096</mn> <mo>,</mo> <mspace width="0.166667em"/> <mi>M</mi> <mo>=</mo> <mn>1024</mn> </mrow> </semantics></math> and 30 spikes, respectively.</p>
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<p>Comparison MSE of two algorithms for recovered signal with <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mn>4096</mn> <mo>,</mo> <mspace width="0.166667em"/> <mi>M</mi> <mo>=</mo> <mn>1024</mn> </mrow> </semantics></math> and 30 spikes, respectively.</p>
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<p>From top to bottom: Original signal, observation data, recovered signal by Algorithm 2 and SPGA with <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mn>4096</mn> <mo>,</mo> <mspace width="0.166667em"/> <mi>M</mi> <mo>=</mo> <mn>1024</mn> </mrow> </semantics></math> and 50 spikes, respectively.</p>
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<p>Comparison MSE of two algorithms for recovered signal with <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mn>4096</mn> <mo>,</mo> <mspace width="0.166667em"/> <mi>M</mi> <mo>=</mo> <mn>1024</mn> </mrow> </semantics></math> and 50 spikes, respectively.</p>
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13 pages, 270 KiB  
Article
Fourier Truncation Regularization Method for a Time-Fractional Backward Diffusion Problem with a Nonlinear Source
by Fan Yang, Ping Fan, Xiao-Xiao Li and Xin-Yi Ma
Mathematics 2019, 7(9), 865; https://doi.org/10.3390/math7090865 - 19 Sep 2019
Cited by 22 | Viewed by 2564
Abstract
In present paper, we deal with a backward diffusion problem for a time-fractional diffusion problem with a nonlinear source in a strip domain. We all know this nonlinear problem is severely ill-posed, i.e., the solution does not depend continuously on the measurable data. [...] Read more.
In present paper, we deal with a backward diffusion problem for a time-fractional diffusion problem with a nonlinear source in a strip domain. We all know this nonlinear problem is severely ill-posed, i.e., the solution does not depend continuously on the measurable data. Therefore, we use the Fourier truncation regularization method to solve this problem. Under an a priori hypothesis and an a priori regularization parameter selection rule, we obtain the convergence error estimates between the regular solution and the exact solution at 0 x < 1 . Full article
21 pages, 327 KiB  
Article
The Distribution Function of a Probability Measure on a Linearly Ordered Topological Space
by José Fulgencio Gálvez-Rodríguez and Miguel Ángel Sánchez-Granero
Mathematics 2019, 7(9), 864; https://doi.org/10.3390/math7090864 - 18 Sep 2019
Cited by 4 | Viewed by 2374
Abstract
In this paper, we describe a theory of a cumulative distribution function on a space with an order from a probability measure defined in this space. This distribution function plays a similar role to that played in the classical case. Moreover, we define [...] Read more.
In this paper, we describe a theory of a cumulative distribution function on a space with an order from a probability measure defined in this space. This distribution function plays a similar role to that played in the classical case. Moreover, we define its pseudo-inverse and study its properties. Those properties will allow us to generate samples of a distribution and give us the chance to calculate integrals with respect to the related probability measure. Full article
12 pages, 742 KiB  
Article
New Inequalities of Weaving K-Frames in Subspaces
by Zhong-Qi Xiang
Mathematics 2019, 7(9), 863; https://doi.org/10.3390/math7090863 - 18 Sep 2019
Viewed by 2091
Abstract
In the present paper, we obtain some new inequalities for weaving K-frames in subspaces based on the operator methods. The inequalities are associated with a sequence of bounded complex numbers and a parameter λ R . We also give a double [...] Read more.
In the present paper, we obtain some new inequalities for weaving K-frames in subspaces based on the operator methods. The inequalities are associated with a sequence of bounded complex numbers and a parameter λ R . We also give a double inequality for weaving K-frames with the help of two bounded linear operators induced by K-dual. Facts prove that our results cover those recently obtained on weaving frames due to Li and Leng, and Xiang. Full article
(This article belongs to the Special Issue Inequalities)
8 pages, 239 KiB  
Article
On a New Generalization of Banach Contraction Principle with Application
by Hüseyin Işık, Babak Mohammadi, Mohammad Reza Haddadi and Vahid Parvaneh
Mathematics 2019, 7(9), 862; https://doi.org/10.3390/math7090862 - 18 Sep 2019
Cited by 9 | Viewed by 2821
Abstract
The main purpose of the current work is to present firstly a new generalization of Caristi’s fixed point result and secondly the Banach contraction principle. An example and an application is given to show the usability of our results. Full article
(This article belongs to the Special Issue Fixed Point, Optimization, and Applications)
31 pages, 1512 KiB  
Article
Variational Partitioned Runge–Kutta Methods for Lagrangians Linear in Velocities
by Tomasz M. Tyranowski and Mathieu Desbrun
Mathematics 2019, 7(9), 861; https://doi.org/10.3390/math7090861 - 18 Sep 2019
Cited by 5 | Viewed by 3351
Abstract
In this paper, we construct higher-order variational integrators for a class of degenerate systems described by Lagrangians that are linear in velocities. We analyze the geometry underlying such systems and develop the appropriate theory for variational integration. Our main observation is that the [...] Read more.
In this paper, we construct higher-order variational integrators for a class of degenerate systems described by Lagrangians that are linear in velocities. We analyze the geometry underlying such systems and develop the appropriate theory for variational integration. Our main observation is that the evolution takes place on the primary constraint and the “Hamiltonian” equations of motion can be formulated as an index-1 differential-algebraic system. We also construct variational Runge–Kutta methods and analyze their properties. The general properties of Runge–Kutta methods depend on the “velocity” part of the Lagrangian. If the “velocity” part is also linear in the position coordinate, then we show that non-partitioned variational Runge–Kutta methods are equivalent to integration of the corresponding first-order Euler–Lagrange equations, which have the form of a Poisson system with a constant structure matrix, and the classical properties of the Runge–Kutta method are retained. If the “velocity” part is nonlinear in the position coordinate, we observe a reduction of the order of convergence, which is typical of numerical integration of DAEs. We verified our results through numerical experiments for various dynamical systems. Full article
(This article belongs to the Special Issue Geometric Numerical Integration)
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<p>The reference solution for Kepler’s problem computed by integrating Equation (<a href="#FD90-mathematics-07-00861" class="html-disp-formula">90</a>) until the time <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>7</mn> </mrow> </semantics></math> using Verner’s method with the time step <math display="inline"><semantics> <mrow> <mi>h</mi> <mo>=</mo> <mn>2</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>7</mn> </mrow> </msup> </mrow> </semantics></math>.</p>
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<p>Convergence of several Runge–Kutta methods for Kepler’s problem.</p>
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<p>Hamiltonian conservation for the 1-stage (<b>top row</b>), 2-stage (<b>middle row</b>) and 3-stage (<b>bottom row</b>) Gauss methods applied to Kepler’s problem with the time step <math display="inline"><semantics> <mrow> <mi>h</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math> over the time interval <math display="inline"><semantics> <mrow> <mo>[</mo> <mn>0</mn> <mo>,</mo> <mn>5</mn> <mo>×</mo> <msup> <mn>10</mn> <mn>5</mn> </msup> <mo>]</mo> </mrow> </semantics></math> (<b>right column</b>), with a close-up on the initial interval <math display="inline"><semantics> <mrow> <mo>[</mo> <mn>0</mn> <mo>,</mo> <mn>150</mn> <mo>]</mo> </mrow> </semantics></math> shown in (<b>left column</b>).</p>
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<p>Hamiltonian for the numerical solution of Kepler’s problem obtained with the 3- and 4-stage Lobatto IIIA-IIIB schemes (<b>top</b>,<b>middle</b>), respectively, and the non-variational Radau IIA method (<b>bottom</b>).</p>
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<p>The circular trajectories of the two point vortices rotating about their vorticity center at <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mi>C</mi> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>y</mi> <mi>C</mi> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.</p>
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<p>Convergence of several Runge–Kutta methods for the system of two point vortices.</p>
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<p>Hamiltonian for the 1-stage (<b>top</b>), 2-stage (<b>second</b>) and 3-stage (<b>third</b>) Gauss, and the 3-stage Radau IIA (<b>bottom</b>) methods applied to the system of two point vortices with the time step <math display="inline"><semantics> <mrow> <mi>h</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math> over the time interval <math display="inline"><semantics> <mrow> <mo>[</mo> <mn>0</mn> <mo>,</mo> <mn>5</mn> <mo>×</mo> <msup> <mn>10</mn> <mn>5</mn> </msup> <mo>]</mo> </mrow> </semantics></math>.</p>
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<p>Hamiltonian conservation for the 3-stage (<b>top</b>) and 4-stage (<b>bottom</b>) Lobatto IIIA-IIIB methods applied to the system of two point vortices with the time step <math display="inline"><semantics> <mrow> <mi>h</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math> over the time interval <math display="inline"><semantics> <mrow> <mo>[</mo> <mn>0</mn> <mo>,</mo> <mn>5</mn> <mo>×</mo> <msup> <mn>10</mn> <mn>5</mn> </msup> <mo>]</mo> </mrow> </semantics></math> (<b>right column</b>), with a close-up on the initial interval <math display="inline"><semantics> <mrow> <mo>[</mo> <mn>0</mn> <mo>,</mo> <mn>50</mn> <mo>]</mo> </mrow> </semantics></math> shown in (<b>left column</b>).</p>
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<p>The reference solution for the Lotka–Volterra equations computed by integrating Equation (<a href="#FD90-mathematics-07-00861" class="html-disp-formula">90</a>) until the time <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math> using Verner’s method with the time step <math display="inline"><semantics> <mrow> <mi>h</mi> <mo>=</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>7</mn> </mrow> </msup> </mrow> </semantics></math>.</p>
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<p>Convergence of several Runge–Kutta methods for the Lotka–Volterra model.</p>
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<p>Hamiltonian conservation for the 1-stage (<b>top row</b>) and 3-stage (<b>bottom row</b>) Gauss methods applied to the Lotka–Volterra model with the time step <math display="inline"><semantics> <mrow> <mi>h</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math> over the time interval <math display="inline"><semantics> <mrow> <mo>[</mo> <mn>0</mn> <mo>,</mo> <mn>5</mn> <mo>×</mo> <msup> <mn>10</mn> <mn>5</mn> </msup> <mo>]</mo> </mrow> </semantics></math> (<b>right column</b>), with a close-up on the initial interval <math display="inline"><semantics> <mrow> <mo>[</mo> <mn>0</mn> <mo>,</mo> <mn>100</mn> <mo>]</mo> </mrow> </semantics></math> shown in (<b>left column</b>).</p>
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<p>Hamiltonian for the numerical solution of the Lotka–Volterra model obtained with the 2-stage Gauss method (<b>top left</b>), the 3- and 4-stage Lobatto IIIA-IIIB schemes (<b>top right</b>,<b>bottom left</b>), respectively, and the non-variational Radau IIA method (<b>bottom right</b>).</p>
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19 pages, 323 KiB  
Article
Inertial-Like Subgradient Extragradient Methods for Variational Inequalities and Fixed Points of Asymptotically Nonexpansive and Strictly Pseudocontractive Mappings
by Lu-Chuan Ceng, Adrian Petruşel, Ching-Feng Wen and Jen-Chih Yao
Mathematics 2019, 7(9), 860; https://doi.org/10.3390/math7090860 - 17 Sep 2019
Cited by 15 | Viewed by 2328
Abstract
Let VIP indicate the variational inequality problem with Lipschitzian and pseudomonotone operator and let CFPP denote the common fixed-point problem of an asymptotically nonexpansive mapping and a strictly pseudocontractive mapping in a real Hilbert space. Our object in this article is to establish [...] Read more.
Let VIP indicate the variational inequality problem with Lipschitzian and pseudomonotone operator and let CFPP denote the common fixed-point problem of an asymptotically nonexpansive mapping and a strictly pseudocontractive mapping in a real Hilbert space. Our object in this article is to establish strong convergence results for solving the VIP and CFPP by utilizing an inertial-like gradient-like extragradient method with line-search process. Via suitable assumptions, it is shown that the sequences generated by such a method converge strongly to a common solution of the VIP and CFPP, which also solves a hierarchical variational inequality (HVI). Full article
(This article belongs to the Special Issue Applied Functional Analysis and Its Applications)
18 pages, 324 KiB  
Article
Algebraic Algorithms for Even Circuits in Graphs
by Huy Tài Hà and Susan Morey
Mathematics 2019, 7(9), 859; https://doi.org/10.3390/math7090859 - 17 Sep 2019
Cited by 1 | Viewed by 2342
Abstract
We present an algebraic algorithm to detect the existence of and to list all indecomposable even circuits in a given graph. We also discuss an application of our work to the study of directed cycles in digraphs. Full article
(This article belongs to the Special Issue Current Trends on Monomial and Binomial Ideals)
31 pages, 2071 KiB  
Review
Applications of Game Theory in Project Management: A Structured Review and Analysis
by Mahendra Piraveenan
Mathematics 2019, 7(9), 858; https://doi.org/10.3390/math7090858 - 17 Sep 2019
Cited by 23 | Viewed by 15170
Abstract
This paper provides a structured literature review and analysis of using game theory to model project management scenarios. We select and review thirty-two papers from Scopus, present a complex three-dimensional classification of the selected papers, and analyse the resultant citation network. According to [...] Read more.
This paper provides a structured literature review and analysis of using game theory to model project management scenarios. We select and review thirty-two papers from Scopus, present a complex three-dimensional classification of the selected papers, and analyse the resultant citation network. According to the industry-based classification, the surveyed literature can be classified in terms of construction industry, ICT industry or unspecified industry. Based on the types of players, the literature can be classified into papers that use government-contractor games, contractor–contractor games, contractor-subcontractor games, subcontractor–subcontractor games or games involving other types of players. Based on the type of games used, papers using normal-form non-cooperative games, normal-form cooperative games, extensive-form non-cooperative games or extensive-form cooperative games are present. Also, we show that each of the above classifications plays a role in influencing which papers are likely to cite a particular paper, though the strongest influence is exerted by the type-of-game classification. Overall, the citation network in this field is sparse, implying that the awareness of authors in this field about studies by other academics is suboptimal. Our review suggests that game theory is a very useful tool for modelling project management scenarios, and that more work needs to be done focusing on project management in ICT domain, as well as by using extensive-form cooperative games where relevant. Full article
(This article belongs to the Special Issue Game Theory)
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<p>The classification of papers reviewed based on the application domain.</p>
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<p>The classification of papers reviewed based on the players of the games.</p>
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<p>The classification of papers reviewed based on the type of game played.</p>
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<p>Some examples of papers which were not classified, as they were not project management-specific.</p>
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<p>The citation network of papers reviewed—no classification shown.</p>
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<p>The citation network of papers reviewed—domain-based classification shown. Bright pink: construction domain; blue: ICT domain; brownish-pink: other domains or generic project management.</p>
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<p>The citation network of papers reviewed—player-based classification shown. Blue: government sector—private sector game; pink: contractor—contractor game; red: contractor— subcontractor game; yellow: subcontractor—subcontractor game; green: other types of players.</p>
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<p>The citation network of papers reviewed—game-based classification shown. Blue: normal-form non-cooperative game; yellow: normal-form cooperative game; red: extensive-form non-cooperative game; green: extensive-form cooperative game.</p>
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<p>Citation counts of the papers classified according to Google scholar, as accessed on the 4 April 2019. The number of references in each paper is also shown; that is, the incoming citations and outgoing citations of each paper we reviewed are shown. The publication year of the paper is mentioned as part of the paper name.</p>
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25 pages, 413 KiB  
Article
Time-Consistent Investment-Reinsurance Strategies for the Insurer and the Reinsurer under the Generalized Mean-Variance Criteria
by Helu Xiao, Tiantian Ren, Yanfei Bai and Zhongbao Zhou
Mathematics 2019, 7(9), 857; https://doi.org/10.3390/math7090857 - 17 Sep 2019
Cited by 4 | Viewed by 2424
Abstract
Most of the existing literature on optimal investment-reinsurance only studies from the perspective of insurers and also treats the investment-reinsurance decision as a continuous process. However, in practice, the benefits of reinsurers cannot be ignored, nor can decision-makers engage in continuous trading. Under [...] Read more.
Most of the existing literature on optimal investment-reinsurance only studies from the perspective of insurers and also treats the investment-reinsurance decision as a continuous process. However, in practice, the benefits of reinsurers cannot be ignored, nor can decision-makers engage in continuous trading. Under the discrete-time framework, we first propose a multi-period investment-reinsurance optimization problem considering the joint interests of the insurer and the reinsurer, among which their performance is measured by two generalized mean-variance criteria. We derive the time-consistent investment-reinsurance strategies for the proposed model by maximizing the weighted sum of the insurer’s and the reinsurer’s mean-variance objectives. We discuss the time-consistent investment-reinsurance strategies under two special premium principles. Finally, we provide some numerical simulations to show the impact of the intertemporal restrictions on the time-consistent investment-reinsurance strategies. These results indicate that the intertemporal restrictions will urge the insurer and the reinsurer to shrink the position invested in the risky asset; however, for the time-consistent reinsurance strategy, the impact of the intertemporal restrictions depends on who is the leader in the proposed model. Full article
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<p>Time-consistent investment strategies for the insurer and the reinsurer (<math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math>).</p>
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<p>Time-consistent investment strategy for the insurer (<math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.6</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math>).</p>
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<p>Time-consistent reinsurance strategy under the expected value principle (<math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math>).</p>
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<p>Time-consistent reinsurance strategy under the expected value principle (<math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.6</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math>).</p>
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<p>Time-consistent reinsurance strategy under the variance value principle (<math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math>).</p>
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<p>Time-consistent reinsurance strategy under the variance value principle (<math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.6</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math>).</p>
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<p>Time-consistent reinsurance strategy under the expected value principle (<math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math>).</p>
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<p>Time-consistent reinsurance strategy under the expected value principle (<math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.6</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math>).</p>
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<p>Time-consistent reinsurance strategy under the variance value principle (<math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math>).</p>
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<p>Time-consistent reinsurance strategy under the variance value principle (<math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.6</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math>).</p>
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9 pages, 231 KiB  
Article
Existence Results for Block Matrix Operator of Fractional Orders in Banach Algebras
by Hind Hashem, Ahmed El-Sayed and Dumitru Baleanu
Mathematics 2019, 7(9), 856; https://doi.org/10.3390/math7090856 - 17 Sep 2019
Cited by 4 | Viewed by 2011
Abstract
This paper is concerned with proving the existence of solutions for a coupled system of quadratic integral equations of fractional order in Banach algebras. This result is a direct application of a fixed point theorem of Banach algebras. Some particular cases, examples and [...] Read more.
This paper is concerned with proving the existence of solutions for a coupled system of quadratic integral equations of fractional order in Banach algebras. This result is a direct application of a fixed point theorem of Banach algebras. Some particular cases, examples and remarks are illustrated. Finally, the stability of solutions for that coupled system are studied. Full article
(This article belongs to the Section Mathematics and Computer Science)
12 pages, 769 KiB  
Article
High Convergence Order Iterative Procedures for Solving Equations Originating from Real Life Problems
by Ramandeep Behl, Ioannis K. Argyros and Ali Saleh Alshomrani
Mathematics 2019, 7(9), 855; https://doi.org/10.3390/math7090855 - 17 Sep 2019
Cited by 2 | Viewed by 2108
Abstract
The foremost aim of this paper is to suggest a local study for high order iterative procedures for solving nonlinear problems involving Banach space valued operators. We only deploy suppositions on the first-order derivative of the operator. Our conditions involve the Lipschitz or [...] Read more.
The foremost aim of this paper is to suggest a local study for high order iterative procedures for solving nonlinear problems involving Banach space valued operators. We only deploy suppositions on the first-order derivative of the operator. Our conditions involve the Lipschitz or Hölder case as compared to the earlier ones. Moreover, when we specialize to these cases, they provide us: larger radius of convergence, higher bounds on the distances, more precise information on the solution and smaller Lipschitz or Hölder constants. Hence, we extend the suitability of them. Our new technique can also be used to broaden the usage of existing iterative procedures too. Finally, we check our results on a good number of numerical examples, which demonstrate that they are capable of solving such problems where earlier studies cannot apply. Full article
16 pages, 429 KiB  
Article
Optimal Sliced Latin Hypercube Designs with Slices of Arbitrary Run Sizes
by Jing Zhang, Jin Xu, Kai Jia, Yimin Yin and Zhengming Wang
Mathematics 2019, 7(9), 854; https://doi.org/10.3390/math7090854 - 16 Sep 2019
Cited by 5 | Viewed by 3053
Abstract
Sliced Latin hypercube designs (SLHDs) are widely used in computer experiments with both quantitative and qualitative factors and in batches. Optimal SLHDs achieve better space-filling property on the whole experimental region. However, most existing methods for constructing optimal SLHDs have restriction on the [...] Read more.
Sliced Latin hypercube designs (SLHDs) are widely used in computer experiments with both quantitative and qualitative factors and in batches. Optimal SLHDs achieve better space-filling property on the whole experimental region. However, most existing methods for constructing optimal SLHDs have restriction on the run sizes. In this paper, we propose a new method for constructing SLHDs with arbitrary run sizes, and a new combined space-filling measurement describing the space-filling property for both the whole design and its slices. Furthermore, we develop general algorithms to search for the optimal SLHD with arbitrary run sizes under the proposed measurement. Examples are presented to illustrate that effectiveness of the proposed methods. Full article
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<p>The within-slice exchange procedure. Left: The original FSLH(4,6;2,2). Right: The neighbour of the FSLH after exchanging 6 and 30 in the second slice and in the second column of the design.</p>
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<p>(<b>a</b>) the different-slice procedure: exchange 54 in <math display="inline"><semantics> <mrow> <mi mathvariant="bold-italic">M</mi> <mo>(</mo> <mn>1</mn> <mo>:</mo> <mn>4</mn> <mo>,</mo> <mn>1</mn> <mo>)</mo> </mrow> </semantics></math> with 60 of <math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>(</mo> <mi>b</mi> <mo>)</mo> </mrow> </semantics></math> in <math display="inline"><semantics> <mrow> <mi mathvariant="bold-italic">M</mi> <mo>(</mo> <mn>5</mn> <mo>:</mo> <mn>10</mn> <mo>,</mo> <mn>1</mn> <mo>)</mo> </mrow> </semantics></math>; (<b>b</b>) the out-slice procedure: replace 54 in <math display="inline"><semantics> <mrow> <mi mathvariant="bold-italic">M</mi> <mo>(</mo> <mn>1</mn> <mo>:</mo> <mn>4</mn> <mo>,</mo> <mn>1</mn> <mo>)</mo> </mrow> </semantics></math> with 49 of <math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>(</mo> <mi>b</mi> <mo>)</mo> </mrow> </semantics></math> in the out-slice elements.</p>
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<p>A poor design with some repeating rows. (<b>a</b>) the two-dimensional input region is divided into <math display="inline"><semantics> <mrow> <mn>4</mn> <mo>×</mo> <mn>4</mn> </mrow> </semantics></math> cells, and some repeating rows lie in the same cell; (<b>b</b>) the two-dimensional input region is divided into <math display="inline"><semantics> <mrow> <mn>6</mn> <mo>×</mo> <mn>6</mn> </mrow> </semantics></math> cells, and some repeating rows lie in the same cell.</p>
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<p>A resulting design with design points spread out. (<b>a</b>) the <span class="html-italic">n</span> design points fall into different cells in the <math display="inline"><semantics> <mrow> <mn>4</mn> <mo>×</mo> <mn>4</mn> </mrow> </semantics></math> grid; (<b>b</b>) the <span class="html-italic">n</span> design points fall into different cells in the <math display="inline"><semantics> <mrow> <mn>6</mn> <mo>×</mo> <mn>6</mn> </mrow> </semantics></math> grid.</p>
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<p>Optimization results for finding optimal FSLHD. (<b>a</b>) the initial FSLHD<math display="inline"><semantics> <mrow> <mo>(</mo> <mn>4</mn> <mo>,</mo> <mn>8</mn> <mo>,</mo> <mn>12</mn> <mo>;</mo> <mn>3</mn> <mo>,</mo> <mn>2</mn> <mo>)</mo> </mrow> </semantics></math> in Example 1, different types of points denote difference three slices, respectively; (<b>b</b>) the optimization results of FSLHD<math display="inline"><semantics> <mrow> <mo>(</mo> <mn>4</mn> <mo>,</mo> <mn>8</mn> <mo>,</mo> <mn>12</mn> <mo>;</mo> <mn>3</mn> <mo>,</mo> <mn>2</mn> <mo>)</mo> </mrow> </semantics></math> after using the SESE algorithm.</p>
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21 pages, 1121 KiB  
Article
Numerical Integral Transform Methods for Random Hyperbolic Models with a Finite Degree of Randomness
by M. Consuelo Casabán, Rafael Company and Lucas Jódar
Mathematics 2019, 7(9), 853; https://doi.org/10.3390/math7090853 - 16 Sep 2019
Cited by 3 | Viewed by 2324
Abstract
This paper deals with the construction of numerical solutions of random hyperbolic models with a finite degree of randomness that make manageable the computation of its expectation and variance. The approach is based on the combination of the random Fourier transforms, the random [...] Read more.
This paper deals with the construction of numerical solutions of random hyperbolic models with a finite degree of randomness that make manageable the computation of its expectation and variance. The approach is based on the combination of the random Fourier transforms, the random Gaussian quadratures and the Monte Carlo method. The recovery of the solution of the original random partial differential problem throughout the inverse integral transform allows its numerical approximation using Gaussian quadratures involving the evaluation of the solution of the random ordinary differential problem at certain concrete values, which are approximated using Monte Carlo method. Numerical experiments illustrating the numerical convergence of the method are included. Full article
(This article belongs to the Special Issue Stochastic Differential Equations and Their Applications)
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<p>(<b>a</b>) Surface of the expectation <math display="inline"><semantics> <mrow> <mi mathvariant="double-struck">E</mi> <mo>[</mo> <mi>u</mi> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>t</mi> <mo>)</mo> <mo>]</mo> </mrow> </semantics></math>; and (<b>b</b>) surface of the standard deviation <math display="inline"><semantics> <msqrt> <mrow> <mi>Var</mi> <mo>[</mo> <mi>u</mi> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>t</mi> <mo>)</mo> <mo>]</mo> </mrow> </msqrt> </semantics></math>. Both statistical moment functions correspond to the exact solution s.p. in Equations (<a href="#FD56-mathematics-07-00853" class="html-disp-formula">56</a>) and (<a href="#FD57-mathematics-07-00853" class="html-disp-formula">57</a>) of the random IVP in Equations (<a href="#FD52-mathematics-07-00853" class="html-disp-formula">52</a>)–(<a href="#FD55-mathematics-07-00853" class="html-disp-formula">55</a>) on the domain <math display="inline"><semantics> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>t</mi> <mo>)</mo> <mo>∈</mo> <mrow> <mo>[</mo> <mn>0</mn> <mo>,</mo> <mn>2</mn> <mo>.</mo> <mn>5</mn> <mo>]</mo> <mo>×</mo> <mo>[</mo> <mn>0</mn> <mo>,</mo> <mn>2</mn> <mo>]</mo> </mrow> </mrow> </semantics></math> considering <math display="inline"><semantics> <mrow> <mi>a</mi> <mo>∼</mo> <msub> <mi>N</mi> <mrow> <mo>[</mo> <mn>0</mn> <mo>.</mo> <mn>9</mn> <mo>,</mo> <mn>1</mn> <mo>.</mo> <mn>1</mn> <mo>]</mo> </mrow> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>;</mo> <mn>0</mn> <mo>.</mo> <mn>05</mn> <mo>)</mo> </mrow> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>b</mi> <mo>∼</mo> <msub> <mi>Beta</mi> <mrow> <mo>[</mo> <mn>0</mn> <mo>.</mo> <mn>4</mn> <mo>,</mo> <mn>0</mn> <mo>.</mo> <mn>6</mn> <mo>]</mo> </mrow> </msub> <mrow> <mo>(</mo> <mn>2</mn> <mo>;</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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<p>(<b>a</b>) Expectation, <math display="inline"><semantics> <mrow> <mi mathvariant="double-struck">E</mi> <mo>[</mo> <mi>u</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>]</mo> </mrow> </semantics></math>, of the exact solution s.p. in Equations (<a href="#FD56-mathematics-07-00853" class="html-disp-formula">56</a>) and (<a href="#FD57-mathematics-07-00853" class="html-disp-formula">57</a>) vs. their corresponding numerical approximations, <math display="inline"><semantics> <mrow> <mi mathvariant="double-struck">E</mi> <mfenced separators="" open="[" close="]"> <msubsup> <mi>u</mi> <mi>N</mi> <mrow> <mi mathvariant="normal">G</mi> <mo>−</mo> <mi mathvariant="normal">H</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <mn>1</mn> <mo>)</mo> </mrow> </mfenced> </mrow> </semantics></math> (Equation (<a href="#FD64-mathematics-07-00853" class="html-disp-formula">64</a>)), by random Gauss–Hermite quadrature using Hermite’s polynomials of degree <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>∈</mo> <mo>{</mo> <mn>2</mn> <mo>,</mo> <mn>4</mn> <mo>,</mo> <mn>10</mn> <mo>}</mo> </mrow> </semantics></math>, at the time instant <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and on the spatial domain <math display="inline"><semantics> <mrow> <mn>0</mn> <mo>≤</mo> <mi>x</mi> <mo>≤</mo> <mn>2</mn> <mo>.</mo> <mn>5</mn> </mrow> </semantics></math>. (<b>b</b>) Relative errors of the expectation, <math display="inline"><semantics> <mrow> <mi>RelErr</mi> <mfenced separators="" open="[" close="]"> <msubsup> <mi mathvariant="double-struck">E</mi> <mi>N</mi> <mrow> <mi mathvariant="normal">G</mi> <mo>−</mo> <mi mathvariant="normal">H</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <mn>1</mn> <mo>)</mo> </mrow> </mfenced> </mrow> </semantics></math> (Equation (<a href="#FD67-mathematics-07-00853" class="html-disp-formula">67</a>)) when it is considered Hermite’s polynomials of degree <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>∈</mo> <mo>{</mo> <mn>2</mn> <mo>,</mo> <mn>4</mn> <mo>,</mo> <mn>10</mn> <mo>}</mo> </mrow> </semantics></math> and the spatial domain <math display="inline"><semantics> <mrow> <mn>0</mn> <mo>≤</mo> <mspace width="3.33333pt"/> <mi>x</mi> <mspace width="3.33333pt"/> <mo>≤</mo> <mspace width="3.33333pt"/> <mn>2</mn> <mo>.</mo> <mn>5</mn> </mrow> </semantics></math>.</p>
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<p>(<b>a</b>) Standard deviation, <math display="inline"><semantics> <msqrt> <mrow> <mi>Var</mi> <mo>[</mo> <mi>u</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>]</mo> </mrow> </msqrt> </semantics></math>, of the exact solution s.p. in Equations (<a href="#FD56-mathematics-07-00853" class="html-disp-formula">56</a>) and (<a href="#FD57-mathematics-07-00853" class="html-disp-formula">57</a>) vs. their corresponding numerical approximations, <math display="inline"><semantics> <msqrt> <mrow> <mi>Var</mi> <mo>[</mo> <msubsup> <mi>u</mi> <mi>N</mi> <mrow> <mi mathvariant="normal">G</mi> <mo>−</mo> <mi mathvariant="normal">H</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>]</mo> </mrow> </msqrt> </semantics></math> (Equations (<a href="#FD64-mathematics-07-00853" class="html-disp-formula">64</a>)–(<a href="#FD66-mathematics-07-00853" class="html-disp-formula">66</a>)), by random Gauss–Hermite quadrature using Hermite’s polynomials of degree <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>∈</mo> <mo>{</mo> <mn>2</mn> <mo>,</mo> <mn>4</mn> <mo>,</mo> <mn>10</mn> <mo>}</mo> </mrow> </semantics></math>, at the time instant <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> and on the spatial domain <math display="inline"><semantics> <mrow> <mn>0</mn> <mo>≤</mo> <mi>x</mi> <mo>≤</mo> <mn>2</mn> <mo>.</mo> <mn>5</mn> </mrow> </semantics></math>. (<b>b</b>) Relative errors of the standard deviation, <math display="inline"><semantics> <mrow> <mi>RelErr</mi> <mfenced open="[" close="]"> <msqrt> <mrow> <msubsup> <mi>Var</mi> <mi>N</mi> <mrow> <mi mathvariant="normal">G</mi> <mo>−</mo> <mi mathvariant="normal">H</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </msqrt> </mfenced> </mrow> </semantics></math> (Equation (68)) when it is considered Hermite’s polynomials of degree <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>∈</mo> <mo>{</mo> <mn>2</mn> <mo>,</mo> <mn>4</mn> <mo>,</mo> <mn>10</mn> <mo>}</mo> </mrow> </semantics></math> and the spatial domain <math display="inline"><semantics> <mrow> <mn>0</mn> <mo>≤</mo> <mi>x</mi> <mo>≤</mo> <mn>2</mn> <mo>.</mo> <mn>5</mn> </mrow> </semantics></math>.</p>
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<p>Simulations of the evolution along the time instants <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>0</mn> <mo>.</mo> <mn>5</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>1</mn> <mo>.</mo> <mn>5</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>2</mn> </mrow> </semantics></math> of the approximated expectation, <math display="inline"><semantics> <mrow> <mi mathvariant="double-struck">E</mi> <mo>[</mo> <msubsup> <mi>u</mi> <mrow> <mi>N</mi> <mo>,</mo> <mi>K</mi> </mrow> <mrow> <mi mathvariant="normal">G</mi> <mo>−</mo> <mi mathvariant="normal">L</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>]</mo> </mrow> </semantics></math> (Equation (<a href="#FD85-mathematics-07-00853" class="html-disp-formula">85</a>)), of the solution s.p. <math display="inline"><semantics> <mrow> <msubsup> <mi>u</mi> <mrow> <mi>N</mi> </mrow> <mrow> <mi mathvariant="normal">G</mi> <mo>−</mo> <mi mathvariant="normal">L</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> (Equation (<a href="#FD84-mathematics-07-00853" class="html-disp-formula">84</a>)) on the spatial domain <math display="inline"><semantics> <mrow> <mn>0</mn> <mo>≤</mo> <mi>x</mi> <mo>≤</mo> <mn>1</mn> </mrow> </semantics></math> for <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>1000</mn> </mrow> </semantics></math> realizations via Monte Carlo and <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mn>10</mn> </mrow> </semantics></math> the degree of the Laguerre polynomial.</p>
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<p>(<b>a</b>) Comparative graphics of the absolute deviations for successive approximations to the expectation <math display="inline"><semantics> <mrow> <mi mathvariant="double-struck">E</mi> <mo>[</mo> <msubsup> <mi>u</mi> <mrow> <msub> <mi>N</mi> <mi>ℓ</mi> </msub> <msub> <mi>N</mi> <mrow> <mi>ℓ</mi> <mo>+</mo> <mn>1</mn> </mrow> </msub> <mo>,</mo> <mi>K</mi> </mrow> <mrow> <mi mathvariant="normal">G</mi> <mo>−</mo> <mi mathvariant="normal">L</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>]</mo> </mrow> </semantics></math> (Equation (<a href="#FD93-mathematics-07-00853" class="html-disp-formula">93</a>)). (<b>b</b>) Comparative graphics of the absolute deviations for successive approximations to the standard deviation <math display="inline"><semantics> <msqrt> <mrow> <mi>Var</mi> <mo>[</mo> <msubsup> <mi>u</mi> <mrow> <msub> <mi>N</mi> <mi>ℓ</mi> </msub> <msub> <mi>N</mi> <mrow> <mi>ℓ</mi> <mo>+</mo> <mn>1</mn> </mrow> </msub> <mo>,</mo> <mi>K</mi> </mrow> <mrow> <mi mathvariant="normal">G</mi> <mo>−</mo> <mi mathvariant="normal">L</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>]</mo> </mrow> </msqrt> </semantics></math> (Equation (<a href="#FD93-mathematics-07-00853" class="html-disp-formula">93</a>)). Both graphics correspond to the time <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> on the spatial interval <math display="inline"><semantics> <mrow> <mn>0</mn> <mo>≤</mo> <mi>x</mi> <mo>≤</mo> <mn>1</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>1000</mn> </mrow> </semantics></math> realizations and the degrees <math display="inline"><semantics> <mrow> <mi>N</mi> <mo>=</mo> <mo>{</mo> <mn>4</mn> <mo>,</mo> <mn>6</mn> <mo>,</mo> <mn>8</mn> <mo>,</mo> <mn>10</mn> <mo>}</mo> </mrow> </semantics></math> for the Laguerre polynomials.</p>
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9 pages, 267 KiB  
Article
Analytical Solution of Urysohn Integral Equations by Fixed Point Technique in Complex Valued Metric Spaces
by Hasanen A. Hammad and Manuel De la Sen
Mathematics 2019, 7(9), 852; https://doi.org/10.3390/math7090852 - 15 Sep 2019
Cited by 24 | Viewed by 2994
Abstract
The purpose of this article is to introduce a fixed point result for a general contractive condition in the context of complex valued metric spaces. Also, some important corollaries under this contractive condition are obtained. As an application, we find a unique solution [...] Read more.
The purpose of this article is to introduce a fixed point result for a general contractive condition in the context of complex valued metric spaces. Also, some important corollaries under this contractive condition are obtained. As an application, we find a unique solution for Urysohn integral equations, and some illustrative examples are given to support our obtaining results. Our results extend and generalize the results of Azam et al. Previous known related results in the literarure and some other known results in the literature. Full article
(This article belongs to the Special Issue Fixed Point Theory and Related Nonlinear Problems with Applications)
6 pages, 215 KiB  
Article
Faces of 2-Dimensional Simplex of Order and Chain Polytopes
by Aki Mori
Mathematics 2019, 7(9), 851; https://doi.org/10.3390/math7090851 - 14 Sep 2019
Viewed by 2138
Abstract
Each of the descriptions of vertices, edges, and facets of the order and chain polytope of a finite partially ordered set are well known. In this paper, we give an explicit description of faces of 2-dimensional simplex in terms of vertices. Namely, it [...] Read more.
Each of the descriptions of vertices, edges, and facets of the order and chain polytope of a finite partially ordered set are well known. In this paper, we give an explicit description of faces of 2-dimensional simplex in terms of vertices. Namely, it will be proved that an arbitrary triangle in 1-skeleton of the order or chain polytope forms the face of 2-dimensional simplex of each polytope. These results mean a generalization in the case of 2-faces of the characterization known in the case of edges. Full article
(This article belongs to the Special Issue Current Trends on Monomial and Binomial Ideals)
10 pages, 270 KiB  
Article
A Lyapunov-Type Inequality for a Laplacian System on a Rectangular Domain with Zero Dirichlet Boundary Conditions
by Mohamed Jleli and Bessem Samet
Mathematics 2019, 7(9), 850; https://doi.org/10.3390/math7090850 - 14 Sep 2019
Cited by 2 | Viewed by 2329
Abstract
We consider a coupled system of partial differential equations involving Laplacian operator, on a rectangular domain with zero Dirichlet boundary conditions. A Lyapunov-type inequality related to this problem is derived. This inequality provides a necessary condition for the existence of nontrivial positive solutions. [...] Read more.
We consider a coupled system of partial differential equations involving Laplacian operator, on a rectangular domain with zero Dirichlet boundary conditions. A Lyapunov-type inequality related to this problem is derived. This inequality provides a necessary condition for the existence of nontrivial positive solutions. Full article
(This article belongs to the Special Issue Mathematical Analysis and Boundary Value Problems)
7 pages, 258 KiB  
Article
Set-Valued Interpolative Hardy–Rogers and Set-Valued Reich–Rus–Ćirić-Type Contractions in b-Metric Spaces
by Pradip Debnath and Manuel de La Sen
Mathematics 2019, 7(9), 849; https://doi.org/10.3390/math7090849 - 14 Sep 2019
Cited by 29 | Viewed by 3208
Abstract
In this paper, using an interpolative approach, we investigate two fixed point theorems in the framework of a b-metric space whose all closed and bounded subsets are compact. One of the theorems is for set-valued Hardy–Rogers-type and the other one is for [...] Read more.
In this paper, using an interpolative approach, we investigate two fixed point theorems in the framework of a b-metric space whose all closed and bounded subsets are compact. One of the theorems is for set-valued Hardy–Rogers-type and the other one is for set-valued Reich–Rus–Ćirić-type contractions. Examples are provided to validate the results. Full article
(This article belongs to the Special Issue Fixed Point Theory and Related Nonlinear Problems with Applications)
10 pages, 271 KiB  
Article
Upper Bound of the Third Hankel Determinant for a Subclass of Close-to-Convex Functions Associated with the Lemniscate of Bernoulli
by Hari M. Srivastava, Qazi Zahoor Ahmad, Maslina Darus, Nazar Khan, Bilal Khan, Naveed Zaman and Hasrat Hussain Shah
Mathematics 2019, 7(9), 848; https://doi.org/10.3390/math7090848 - 14 Sep 2019
Cited by 32 | Viewed by 2903
Abstract
In this paper, our aim is to define a new subclass of close-to-convex functions in the open unit disk U that are related with the right half of the lemniscate of Bernoulli. For this function class, we obtain the upper bound of the [...] Read more.
In this paper, our aim is to define a new subclass of close-to-convex functions in the open unit disk U that are related with the right half of the lemniscate of Bernoulli. For this function class, we obtain the upper bound of the third Hankel determinant. Various other related results are also considered. Full article
(This article belongs to the Special Issue Mathematical Analysis and Analytic Number Theory 2019)
17 pages, 6213 KiB  
Article
Optimising Parameters for Expanded Polystyrene Based Pod Production Using Taguchi Method
by Sheikh Imran Ishrat, Zahid Akhtar Khan, Arshad Noor Siddiquee, Irfan Anjum Badruddin, Ali Algahtani, Shakeel Javaid and Rajan Gupta
Mathematics 2019, 7(9), 847; https://doi.org/10.3390/math7090847 - 14 Sep 2019
Cited by 14 | Viewed by 4761
Abstract
Expanded polystyrene (EPS) is used in the building and construction industry for insulation and under flooring purposes. The objective of the study is to investigate the impact of the application of the total quality management (TQM) technique on the significant parameters of the [...] Read more.
Expanded polystyrene (EPS) is used in the building and construction industry for insulation and under flooring purposes. The objective of the study is to investigate the impact of the application of the total quality management (TQM) technique on the significant parameters of the pod production process in a New Zealand based EPS manufacturing facility. In this work, Taguchi’s L27 orthogonal array (OA) is considered for conducting experiments through three input parameters i.e., weight of untreated beads, batch duration, and temperature is investigated. Based on the results, the analyses are carried out while using statistical approaches, such as analysis of the means (ANOM) and analysis of variance (ANOVA). The results from confirmatory experiment indicate that, at optimal parameters setting (17 kg of untreated bead, 130 s of batch duration and 155 °F of temperature), a reasonably streamlined pod manufacturing process can be achieved for sustainable operations. Full article
(This article belongs to the Special Issue Applied Mathematical Methods in Mechanical Engineering)
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Figure 1
<p>Scanning Electron Microscope (SEM) image of an untreated bead at magnification 100× and accelerating voltage of 5 kV.</p>
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<p>A bag containing expanded polystyrene (EPS) resins.</p>
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<p>The bead expander machine.</p>
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<p>Flow chart of the bead production process.</p>
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<p>Large tanks used to cool the beads.</p>
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<p>SEM view of an over exposed bead.</p>
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<p>A pod in the making through the shape moulding machine.</p>
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<p>Front portion of a finished pod.</p>
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<p>Pods laid at a construction site.</p>
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<p>Main effects plot for S/N ratios.</p>
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<p>Normal probability plot for S/N ratios.</p>
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<p>Experiment 14, SEM image of the treated bead at the initial parameter setting of A<sub>2</sub>B<sub>2</sub>C<sub>3</sub> at magnification 100× and acceleration voltage of 5 kV.</p>
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<p>Experiment 19, SEM image of the treated bead at the optimal parameter setting of A<sub>1</sub>B<sub>1</sub>C<sub>3</sub> atmagnification 100× and acceleration voltage of 5 kV.</p>
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<p>SEM image of the treated bead at the confirmation experiment at the optimal parameter setting of A<sub>1</sub>B<sub>1</sub>C<sub>3</sub> at magnification 100× and acceleration voltage of 5 kV.</p>
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10 pages, 910 KiB  
Article
Stability and Bifurcation of a Delayed Time-Fractional Order Business Cycle Model with a General Liquidity Preference Function and Investment Function
by Yingkang Xie, Zhen Wang and Bo Meng
Mathematics 2019, 7(9), 846; https://doi.org/10.3390/math7090846 - 13 Sep 2019
Cited by 14 | Viewed by 3267
Abstract
In this paper, the business cycle (BC) is described by a delayed time-fractional-order model (DTFOM) with a general liquidity preference function and an investment function. Firstly, the existence and uniqueness of the DTFOM solution are proven. Then, some conditions are presented to guarantee [...] Read more.
In this paper, the business cycle (BC) is described by a delayed time-fractional-order model (DTFOM) with a general liquidity preference function and an investment function. Firstly, the existence and uniqueness of the DTFOM solution are proven. Then, some conditions are presented to guarantee that the positive equilibrium point of DTFOM is locally stable. In addition, Hopf bifurcation is obtained by a new method, where the time delay is regarded as the bifurcation parameter. Finally, a numerical example of DTFOM is given to verify the effectiveness of the proposed model and methods. Full article
(This article belongs to the Special Issue Mathematical Economics: Application of Fractional Calculus)
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Figure 1
<p><math display="inline"><semantics> <msup> <mi>E</mi> <mo>*</mo> </msup> </semantics></math> is asymptotically stable, when <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.98</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>3</mn> </mrow> </semantics></math>.</p>
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<p>Stable periodic orbit of System (<a href="#FD28-mathematics-07-00846" class="html-disp-formula">28</a>), when <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.98</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>3.2</mn> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <msup> <mi>E</mi> <mo>*</mo> </msup> </semantics></math> is asymptotically stable, when <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>0.9</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>3.2</mn> </mrow> </semantics></math>.</p>
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12 pages, 268 KiB  
Article
Hermite–Hadamard-Type Inequalities for Convex Functions via the Fractional Integrals with Exponential Kernel
by Xia Wu, JinRong Wang and Jialu Zhang
Mathematics 2019, 7(9), 845; https://doi.org/10.3390/math7090845 - 12 Sep 2019
Cited by 24 | Viewed by 3230
Abstract
In this paper, we establish three fundamental integral identities by the first- and second-order derivatives for a given function via the fractional integrals with exponential kernel. With the help of these new fractional integral identities, we introduce a few interesting Hermite–Hadamard-type inequalities involving [...] Read more.
In this paper, we establish three fundamental integral identities by the first- and second-order derivatives for a given function via the fractional integrals with exponential kernel. With the help of these new fractional integral identities, we introduce a few interesting Hermite–Hadamard-type inequalities involving left-sided and right-sided fractional integrals with exponential kernels for convex functions. Finally, some applications to special means of real number are presented. Full article
10 pages, 750 KiB  
Article
Viscosity Methods and Split Common Fixed Point Problems for Demicontractive Mappings
by Yaqin Wang, Xiaoli Fang and Tae-Hwa Kim
Mathematics 2019, 7(9), 844; https://doi.org/10.3390/math7090844 - 12 Sep 2019
Cited by 5 | Viewed by 2386
Abstract
We, first, propose a new method for solving split common fixed point problems for demicontractive mappings in Hilbert spaces, and then establish the strong convergence of such an algorithm, which extends the Halpern type algorithm studied by Wang and Xu to a viscosity [...] Read more.
We, first, propose a new method for solving split common fixed point problems for demicontractive mappings in Hilbert spaces, and then establish the strong convergence of such an algorithm, which extends the Halpern type algorithm studied by Wang and Xu to a viscosity iteration. Above all, the step sizes in this algorithm are chosen without a priori knowledge of the operator norms. Full article
(This article belongs to the Special Issue Fixed Point Theory and Related Nonlinear Problems with Applications)
22 pages, 638 KiB  
Article
Exponential Stability Results on Random and Fixed Time Impulsive Differential Systems with Infinite Delay
by Xiaodi Li, A. Vinodkumar and T. Senthilkumar
Mathematics 2019, 7(9), 843; https://doi.org/10.3390/math7090843 - 12 Sep 2019
Cited by 8 | Viewed by 2353
Abstract
In this paper, we investigated the stability criteria like an exponential and weakly exponential stable for random impulsive infinite delay differential systems (RIIDDS). Furthermore, we proved some extended exponential and weakly exponential stability results for RIIDDS by using the Lyapunov function and Razumikhin [...] Read more.
In this paper, we investigated the stability criteria like an exponential and weakly exponential stable for random impulsive infinite delay differential systems (RIIDDS). Furthermore, we proved some extended exponential and weakly exponential stability results for RIIDDS by using the Lyapunov function and Razumikhin technique. Unlike other studies, we show that the stability behavior of the random time impulses is faster than the fixed time impulses. Finally, two examples were studied for comparative results of fixed and random time impulses it shows by simulation. Full article
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<p>Shows that fixed impulsive effects, random impulsive effects and without impulsive effects of system (23).</p>
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<p>Comparative results between fixed and random time impulsive effects of system (23).</p>
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<p>Shows that fixed impulsive effects, random impulsive effects and without impulsive effects of system (24).</p>
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<p>Comparative results between fixed and random time impulsive effects of system (24).</p>
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11 pages, 245 KiB  
Article
An Optimal Pursuit Differential Game Problem with One Evader and Many Pursuers
by Idris Ahmed, Poom Kumam, Gafurjan Ibragimov, Jewaidu Rilwan and Wiyada Kumam
Mathematics 2019, 7(9), 842; https://doi.org/10.3390/math7090842 - 11 Sep 2019
Cited by 6 | Viewed by 3390
Abstract
The objective of this paper is to study a pursuit differential game with finite or countably number of pursuers and one evader. The game is described by differential equations in l 2 -space, and integral constraints are imposed on the control function of [...] Read more.
The objective of this paper is to study a pursuit differential game with finite or countably number of pursuers and one evader. The game is described by differential equations in l 2 -space, and integral constraints are imposed on the control function of the players. The duration of the game is fixed and the payoff functional is the greatest lower bound of distances between the pursuers and evader when the game is terminated. However, we discuss the condition for finding the value of the game and construct the optimal strategies of the players which ensure the completion of the game. An important fact to note is that we relaxed the usual conditions on the energy resources of the players. Finally, some examples are provided to illustrate our result. Full article
(This article belongs to the Special Issue Game Theory)
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