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An efficient genetic algorithm approach for solving routing and spectrum assignment problem

机译:解决路由和频谱分配问题的有效遗传算法

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In flex-grid optical network, routing and spectrum assignment (RSA) problem is a crucial task for planning and operating. Due to the non-deterministic polynomial time (NP-hard) complexity of problem, efficient computing techniques are always sought out with the aim to not only achieve good solutions but also in an efficient time span. In this context, this paper addresses the static version of RSA problem in a single objective scenario. We propose efficient meta-heuristic based on genetic algorithm (GA) to provide (near-) optimal solutions to the problem. The effectiveness of GA-based heuristic is bench-marked with exact approach based on integer linear programming (ILP) and other traditional heuristics for a set of scenarios. It is shown that the proposed GA heuristic exhibits better performance than typical heuristics and indeed could achieve optimal solutions in most cases while the running time is still highly manageable.
机译:在柔性网格光网络中,路由和频谱分配(RSA)问题是规划和运营的关键任务。由于问题的不确定性多项式时间(NP-hard)复杂性,人们一直在寻求有效的计算技术,以期不仅获得良好的解决方案,而且能够在有效的时间跨度内实现目标。在这种情况下,本文在单个客观场景中解决了RSA问题的静态版本。我们提出基于遗传算法(GA)的有效元启发式算法,以提供(接近)该问题的最佳解决方案。基于GA的启发式方法的有效性通过基于整数线性规划(ILP)和其他传统启发式方法的精确方法针对一组场景进行了基准测试。结果表明,提出的GA启发式算法比典型的启发式算法具有更好的性能,并且在大多数情况下,尽管运行时间仍可高度管理,但确实可以实现最佳解决方案。

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