用群智能算法求解再生器定位问题

Pedro Ferreira, Rodrigo Pessoa, A. Bernardino, E. Bernardino, Beatriz Piedade, Alexandrino Gonçalves
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引用次数: 0

摘要

在光网络中,由于光纤的缺陷(衰减、色散、转换),信号强度随着距离信号源越来越远而恶化。因此,信号在不丢失或损坏信息的情况下传播的距离是有限的。因此,有必要使用再生器周期性地再生信号。给定一个光网络,再生器位置问题试图以尽可能小的成本安装再生器子集,以使每对节点能够相互通信。本文采用蚁群算法和蜜蜂算法两种群体优化算法来解决这一问题。我们将我们的结果与文献中用于解决相同问题的其他算法进行比较。在480个不同实例上的仿真结果证明了该方法在解决蓄热器定位问题上的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Solving the Regenerator Location Problem using Swarm Intelligence Algorithms
In optical networks, due to deficiencies in the fibre (attenuation, dispersion, conversion)the signal strength deteriorates as it gets further away from its source. For that reason, the distance that a signal can travel without losing or corrupting information is limited. Therefore, it is necessary to regenerate the signals periodically using regenerators. Given an optical network, the regenerator location problem tries to install a subset of regenerators with the minimum possible cost, in a way that each pair of nodes can communicate with each other. In this paper, two swarm optimisation algorithms: Ant Colony Optimisation and Bees Algorithm are used to solve this problem. We compare our results with other algorithms used in literature to solve the same problem. Simulation results obtained using 480 different instances prove their efficiency in solving the regenerator location problem.
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