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Lagrangean heuristic for primary routes assignment in survivable connection-oriented networks

机译:Lagrangean启发式可生存的面向连接的网络中的主要路由分配

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Our discussion in this article centers on the application of a Lagrangean relaxation and a subgradient optimization technique to the problem of primary route assignment (PRA) in survivable connection-oriented networks. The PRA problem consists in a static optimization of primary routes minimizing the Lost Flow in Node (LFN) function. The major contribution of this work is a combination of the Lagrangean relaxation with other heuristic algorithms. We evaluate the performance of the proposed Lagrangean-based heuristic by making a comparison with their counterparts including evolutionary algorithm and GRASP using various network topologies and demand patterns. The results of simulation tests show that the new algorithm provides sub-optimal results, which are better than other heuristics.
机译:本文中的讨论集中在拉格朗日松弛和次梯度优化技术在可生存的面向连接的网络中的主路由分配(PRA)问题上的应用。 PRA问题在于主要路由的静态优化,从而最大程度减少了节点丢失流量(LFN)功能。这项工作的主要贡献是拉格朗日松弛与其他启发式算法的结合。通过与使用各种网络拓扑和需求模式的进化算法和GRASP进行比较,我们评估了基于拉格朗日启发式算法的性能。仿真测试结果表明,该新算法提供了次优的结果,优于其他启发式算法。

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