OPTIMIZATION PROBLEMS OF MODERNIZATION OF THE CAPACITY OF ARCS OF FAULT-TOLERANT NETWORKS

P. Stetsyuk, O. Lykhovyd, V. Zhydkov, A. Suprun
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Abstract

Mathematical models of two classes of problems of modernization of the capacity of arcs of fault-tolerant oriented networks are considered. A network is considered to be fault-tolerant for which it is possible to satisfy all the demands for the transmission of flows when there will be one, but any failure, from all possible single network failures. For the first class of problems (problem A), all possible paths in the network can be used for the transmission of flows. For the second class of problems (problem P), only paths from a predetermined set of paths are used to transfer flows. Mathematical models are represented by linear, Boolean and nonlinear programming problems with a block structure of the constraint matrix.The material of the article is presented in five sections. The first section describes the concepts of a single failure and the scenario of network failures, the content of optimization problems A and P for modernization of capacity of arcs of a fault-tolerant network, a test network (6 vertices and 19 arcs) to test algorithms for solving the problems of modernization of fault-tolerant networks. In the second section, basic models of linear programming problems for finding the capacities of arcs of the fault-tolerant physical structure of a network (problem A) and the fault-tolerant logical structure of a network (problem P) are described, and their properties are considered. The third section describes problems A and P in the form of mixed Boolean linear programming models. Optimal solutions of problem A for various failure scenarios are given for the example of the test network. The solutions were found using the Gurobi program from the NEOS server, where the mathematical model of problem A is described in the AMPL modeling language.The fourth section describes nonlinear convex programming models for problems A and P, developed to find the optimal capacities of fault-tolerant networks according to the selected criterion, and a decomposition algorithm for their solution. The fifth section describes software in the FORTRAN programming language for the decomposition algorithm based on efficient implementations of Shor’s r-algorithms. The decomposition algorithm is compared with the IPOPT program based on the results of solving test problems.
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容错网络弧容量现代化的优化问题
考虑了两类面向容错网络的弧线容量现代化问题的数学模型。一个网络被认为是容错的,因为它有可能满足流传输的所有需求,当所有可能的单个网络故障中有一个故障时,但任何故障。对于第一类问题(问题A),网络中所有可能的路径都可以用于流的传输。对于第二类问题(问题P),只使用预定路径集合中的路径来传输流。数学模型用约束矩阵的块结构的线性、布尔和非线性规划问题来表示。这篇文章的材料分为五个部分。第一部分介绍了单故障的概念和网络故障的场景,容错网络弧线容量现代化的优化问题a和P的内容,以及解决容错网络现代化问题的测试网络(6个顶点和19个弧线)的测试算法。在第二部分中,描述了用于寻找网络容错物理结构(问题a)和网络容错逻辑结构(问题P)的弧线容量的线性规划问题的基本模型,并考虑了它们的性质。第三部分以混合布尔线性规划模型的形式描述问题A和问题P。以试验网络为例,给出了A问题在各种故障情况下的最优解。使用NEOS服务器上的Gurobi程序找到了解决方案,其中用AMPL建模语言描述了问题A的数学模型。第四部分描述了问题A和P的非线性凸规划模型,该模型是根据所选标准找到容错网络的最优容量的,并给出了其解的分解算法。第五部分描述了基于Shor r-算法的有效实现的分解算法的FORTRAN编程语言软件。根据测试问题的求解结果,将分解算法与IPOPT程序进行了比较。
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来源期刊
Journal of Automation and Information Sciences
Journal of Automation and Information Sciences AUTOMATION & CONTROL SYSTEMS-
自引率
0.00%
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审稿时长
6-12 weeks
期刊介绍: This journal contains translations of papers from the Russian-language bimonthly "Mezhdunarodnyi nauchno-tekhnicheskiy zhurnal "Problemy upravleniya i informatiki". Subjects covered include information sciences such as pattern recognition, forecasting, identification and evaluation of complex systems, information security, fault diagnosis and reliability. In addition, the journal also deals with such automation subjects as adaptive, stochastic and optimal control, control and identification under uncertainty, robotics, and applications of user-friendly computers in management of economic, industrial, biological, and medical systems. The Journal of Automation and Information Sciences will appeal to professionals in control systems, communications, computers, engineering in biology and medicine, instrumentation and measurement, and those interested in the social implications of technology.
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