The approximation algorithm to the tensor Green's function calculation in the D'Alembert equation for the polarization potential in the circular waveguide is proposed. The tensor Green's function is presen...
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ISBN:
(纸本)9781479985579
The approximation algorithm to the tensor Green's function calculation in the D'Alembert equation for the polarization potential in the circular waveguide is proposed. The tensor Green's function is presented in the sourcewise form as the sum of the Green's function for free space and the regular part caused by reflections from the waveguide walls. The circular waveguide is a circular cylinder with a directrix in the form of a circle. The directrix in the form of a circle is approximated by a broken line in the form of an inscribed rectilinear polygon. This approximation allows one to use the method of specular reflections and get the tensor Green's function as an infinite sum of tensor divergent spherical waves with a delta-shaped front. The resulting representation of the Green's function can be used to solve the nonstationary intrinsic boundary-value problems of electrodynamics in the case of a circular waveguide with consideration for the reflections from the walls.
In this paper, we first consider a dynamic k-level facility location problem, which is a generalization of the k-level facility location problem when considering time factor. We present a combinatorial primal-dual app...
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In this paper, we first consider a dynamic k-level facility location problem, which is a generalization of the k-level facility location problem when considering time factor. We present a combinatorial primal-dual approximation algorithm for this problem which finds a constant factor approximate solution. Then, we investigative the dynamic k-level facility location problem with submodular penalties and outliers, which extend the existing problem on two fronts, namely from static to dynamic and from without penalties (outliers) to penalties (outliers) allowed. Based on primal-dual technique and the triangle inequality property, we also give two constant factor approximation algorithms for the dynamic problem with submodular penalties and outliers, respectively. (C) 2020 Elsevier B.V. All rights reserved.
Given a strongly connected mixed graph G=(V,E,A)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{...
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Given a strongly connected mixed graph G=(V,E,A)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G=(V,E,A)$$\end{document}, where V represents the vertex set, E is the undirected edge set, and A is the directed arc set, R subset of E\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R \subseteq E$$\end{document} is a subset of required edges and is divided into p clusters R1,R2,& ctdot;,Rp\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_1,R_2,\dots ,R_p$$\end{document}, and A is a set of required arcs and is partitioned into q clusters A1,A2,& mldr;,Aq\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$A_1,A_2,\ldots ,A_q$$\end{document}. Each edge in E and each arc in A are associated with a nonnegative weight and the weight function satisfies the triangle inequality. In this paper we consider two clustered arc routing problems. The first is the Clustered Rural Postman Problem, in which A is empty and the objective is to find a minimum-weight closed walk such that all the edges in R are serviced and the edges in Ri\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_i$$\end{document
As the demand for mobile data services increases, telecom companies need to develop wise strategies to retain existing customers. For instance, in a multicast scenario, satisfying individual user's quality of serv...
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As the demand for mobile data services increases, telecom companies need to develop wise strategies to retain existing customers. For instance, in a multicast scenario, satisfying individual user's quality of service (QoS), data demand at varying rates, etc. are complicated tasks. Earlier works on device-to-device (D2D) multicast have majorly discussed the cases of throughput maximisation without considering the individual user's data request rates. In this paper, we propose two algorithms to maximise the telecom operator's profit collected from the users in a two-hop D2D multicast network, when users have different channel qualities and data request rates while receiving multicast data through a single transmission session. First, we model our multicast scheme for the proposed scenario as a budgeted maximum coverage problem. Later, we propose two approximation algorithms that guarantee approximation ratios of 1-1/root e and 1 - 1/e, respectively, where e denotes the base of the natural logarithm. Numerical results show that the proposed algorithms perform better than the other candidate algorithms and nearly approximates the optimal solution.
The general position-dependent scheduling problems are studied in this paper. A 2-approximation algorithm is proposed for the learning scheduling problem on a single machine with release time to minimize the makespan....
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The general position-dependent scheduling problems are studied in this paper. A 2-approximation algorithm is proposed for the learning scheduling problem on a single machine with release time to minimize the makespan. To minimize the total completion time on a single machine with release time and learning effect, we design a 2-approximation algorithm and a PTAS. Moreover, for the deteriorating scheduling problem to minimize the makespan on parallel machines, a 2-approximation algorithm is provided. (C) 2020 Elsevier B.V. All rights reserved.
This paper presents a simple and fast polynomial time algorithm, the clever, steady strategy algorithm (CSSA). The proposed algorithm consists of three stages which produces optimal or approximate vertex cover for any...
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ISBN:
(纸本)9781509003297
This paper presents a simple and fast polynomial time algorithm, the clever, steady strategy algorithm (CSSA). The proposed algorithm consists of three stages which produces optimal or approximate vertex cover for any unknown un-weighted and undirected G = (V, E). In the first step the degree of each node of the given graph is calculated. In second step the minimum degree node(s) is find and also the adjacent nodes of minimum degree nodes are find. In the third stage the minimum degree node in all adjacent nodes of minimum degree is searched out and is selected as a candidate for MVC and all its edges are deleted. These three steps are processed repeatedly until no edge remains in the graph. The CSSA is tested on small as well as on large benchmark instances. The experimental results and comparative analysis show that the CSSA yields better and fast solution than those approximation algorithms found in literature for solving minimum vertex cover problem.
As a kind of important soft clustering model, the fuzzy C-means method is widely applied in many fields. In this method, instead of the strict distributive ability in the classical k-means method, all the sample point...
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As a kind of important soft clustering model, the fuzzy C-means method is widely applied in many fields. In this method, instead of the strict distributive ability in the classical k-means method, all the sample points are endowed with degrees of membership to each center to depict the fuzzy clustering. In this paper, we show that the fuzzy C-means++ algorithm, which introduces the k-means++ algorithm as a seeding strategy, gives a solution for which the approximation guarantee is O(k(2) ln k). A novel seeding algorithm is then designed based on the contribution of the fuzzy potential function, which improves the approximation ratio to O(k lnk). Preliminary numerical experiments are proposed to support the theoretical results of this paper. (C) 2021 Elsevier B.V. All rights reserved.
Given a connected graph G = (V, E), we seek to partition the vertex set V into k non-empty parts such that the subgraph induced by each part is connected, and the partition is maximally balanced in the way that the ma...
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Given a connected graph G = (V, E), we seek to partition the vertex set V into k non-empty parts such that the subgraph induced by each part is connected, and the partition is maximally balanced in the way that the maximum cardinality of these k parts is minimized. We refer this problem to as min-max balanced connected graph partition into k parts and denote it as k-BGP. The vertex-weighted version of this problem on trees has been studied since about four decades ago, which admits a linear time exact algorithm. The vertex-weighted 2-BGP and 3-BGP admit a 5/4-approximation and a 3/2-approximation, respectively. When k >= 4, no approximability result exists for k-BGP, i.e., the vertex unweighted variant, except a trivial k-approximation. In this paper, we present another 3/2-approximation for the 3-BGP and then extend it to become a k/2-approximation for k-BGP, for any fixed k >= 3. Furthermore, for 4-BGP, we propose an improved 24/13-approximation. To these purposes, we have designed several local improvement operations, which could find more applications in related graph partition problems.
In this paper, we introduce a model of distributionally robust facility location problem (DRFLP) under moment constraints up to the second order. We show, via duality theory of moment problems, that the linear relaxat...
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ISBN:
(纸本)9783319083773;9783319083766
In this paper, we introduce a model of distributionally robust facility location problem (DRFLP) under moment constraints up to the second order. We show, via duality theory of moment problems, that the linear relaxation of the DRFLP is equivalent to that of the standard uncapacitated facility location problem (UFLP). Consequently, any LP-based approximation algorithm for the UFLP implies an approximation algorithm for the DRFLP with the same approximation ratio.
In this paper, we consider multiprocessor scheduling with submodular penalties to extend multiprocessor scheduling with rejection to submodular function. An instance of the problem is given by n jobs and m machines wi...
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In this paper, we consider multiprocessor scheduling with submodular penalties to extend multiprocessor scheduling with rejection to submodular function. An instance of the problem is given by n jobs and m machines with each job having a certain processing time on a machine. We aim to find a subset R of rejected jobs, and assign each of other jobs to one of the m machines. The objective is to minimize the sum of the makespan of the m machines and the rejection penalty R, where the rejection penalty is determined by a submodular function. For this problem, we design a non-combinatorial Lovasz rounding algorithm that achieves a worst-case guarantee of 3+52. Then, we consider a special case of this problem in which all the machines are identical, i.e. each job has the same processing time on any machine, and we design a combinatorial (2-1m-approximation algorithm based on the greedy method and list scheduling (LS) algorithm.
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