基于萤火虫群优化的多约束组播树生成算法

Wen Li, Wenbo Wang, Xiaojun Jing, Jie Liu, Y. Tian, Wei Feng
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引用次数: 1

摘要

在通信网络中,多约束组播通信是提高网络运行效率和服务质量的重要途径。一些启发式算法被应用于求解多约束下的组播路由问题,如模拟退火算法、遗传算法、蚁群算法和粒子群优化算法。然而,这些算法在求解多约束组播路由问题时存在收敛速度慢、计算复杂度高的问题。萤火虫群优化算法(GSO)是最近出现的一种很有前途的算法,它可以克服这些缺点。提出了一种基于GSO的多约束组播(GSO- mcm)算法,该算法能够有效地生成满足多约束要求的组播路由树。仿真结果表明,本文提出的GSO-MCM算法在搜索速度、收敛速度和自适应规模等方面具有良好的性能。
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A glowworm swarm optimization based multi-constraint multicast tree spanning algorithm
In communication networks, the multi-constraint multicast communication is an important way to improve the efficiency of network operation and quality of service. Some heuristic algorithms are applied in solving multicast routing problem under multiple constraints, such as simulated annealing, genetic algorithm, ant colony algorithm and particle swarm optimization algorithm. However, these algorithms suffer from low convergence rate and high computational complexity in solving multi-constraint multicast routing problems. The glowworm swarm optimization (GSO) algorithm is a promising algorithm recently arisen, which can overcome such shortcomings. This paper proposes a GSO based multi-constraint multicast (GSO-MCM) algorithm, which can efficiently generate multicast routing tree to meet the multi-constraint requirements. The simulation result manifests that the GSO-MCM algorithm proposed in this paper performs well in searching, converging speed and adaptability scale.
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