将该算法与蚁群优化算法进行比较,形成路径值最小的环形拓扑

B. Supriadi, Baik Budi, Nana R. Syambas
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引用次数: 6

摘要

电信网络由一些终端组成,如节点和链路。为了使终端之间能够通信,节点之间应该通过链路连接。在设计网络时要考虑节点数量、网元类型、网元位置以及路由信息等诸多因素,从优化的角度出发,网络规划过程面临着诸多挑战。这个问题被归类为NP-Hard。这种NP-hard的一个实际问题是为光通信网络上的一些节点创建环形拓扑。这个问题称为旅行推销员问题(TSP)。在本文中,我们有兴趣提出一种求解TSP的算法。该算法的目标是找到最小解,该解用于形成具有最小权重/成本的环形拓扑。为了验证所提出的算法,将得到的结果与蚁群优化算法进行了比较,无论是最小值还是计算时间。实验结果表明,该算法优于蚁群算法。从3个不同数据的测试中可以看出,在节点数为20 ~ 50的情况下,本文算法求解TSP的最小解平均比蚁群算法提高15%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of proposed algorithm to ant colony optimization algorithm to form a ring topology with minimum path value
A telecommunication network consists of some terminal, like nodes and link. In order to enable telecommunication between the terminal, the nodes should be connected by links. Many factors are considered in designing a network, such as the number of nodes, type, position network elements, and also routing information, the network planning process has several challenges from the optimization point. This issue is classified as NP-Hard. One practical example issue of this NP-hard is creating a ring topology for some nodes on optical network telecommunication. This issue known as Travelling Salesman Problem (TSP). In this paper, we are interested to propose an algorithm to solve the TSP. The goal of this algorithm is to find the minimal solution which is used to form a ring topology that have minimum weight/cost. To test the proposed algorithm, the results obtained compared with Ant Colony Optimization algorithm, both minimum value and computational time. From the test shown that the proposed algorithm is better than ACO. From the test with three different data, it can be concluded that for the number of nodes 20 until 50, the proposed algorithm has average 15% better than ACO to find minimal solution to solve TSP.
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