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Optimization of ring-star transmission problem in telecommunication systems based on Ant Colony algorithms

机译:基于蚁群算法的电信系统中环星传输问题的优化

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Solving complex combinatorial optimization problems using classical algorithms is not efficient related to resources and time. To overcome the problem, we used optimal parameters selection based on Ant Colony Optimization (ACO) algorithms. In this paper, we present algorithm for solving telecommunication network using ACO for searching optimal ring star network topology. We analyzed ant's optimization ability based on shortest path between the nest and food location. In our research we used: Ant System, Elitist Ant System, Rank-Based Ant System, and MAX-MIN Ant System. The program is developed using GNU C++ to prove the algorithm theoretical convergence through simulation on variety of topologies regarding to node numbers. The algorithm was adapted to solve design of telecommunication network, which connects terminals to concentrators using point-to-point connections. The algorithm's output is a star topology showing connections of concentrators in a ring creating Digital Data Service. Algorithm uses seventeen parameters, with thirteen metrics to evaluate configurations. Program validation is performed using three different network node configurations for all four ACO algorithms, only changing two control parameters: speed of pheromone evaporation and existence of local search. The best path was evaluated based on: total time, number of iterations, ring size, and value of topology.
机译:使用经典算法解决复杂的组合优化问题与资源和时间无关。为了解决该问题,我们使用了基于蚁群优化(ACO)算法的最优参数选择。在本文中,我们提出了一种使用ACO来搜索最佳环形星网络拓扑的电信网络求解算法。我们基于巢和食物位置之间的最短路径分析了蚂蚁的优化能力。在我们的研究中,我们使用了:蚂蚁系统,Elitist蚂蚁系统,基于排名的蚂蚁系统和MAX-MIN蚂蚁系统。该程序是使用GNU C ++开发的,旨在通过对节点编号相关的各种拓扑进行仿真来证明算法的理论收敛性。该算法适用于解决电信网络的设计,该电信网络使用点对点连接将终端连接到集中器。该算法的输出是星形拓扑,显示了环形创建数字数据服务中集中器的连接。算法使用17个参数和13个度量标准来评估配置。程序验证是针对所有四种ACO算法使用三种不同的网络节点配置执行的,仅更改了两个控制参数:信息素蒸发的速度和本地搜索的存在。最佳路径的评估基于:总时间,迭代次数,环大小和拓扑值。

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