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An efficient heuristic to dimension large-scale hybrid optoelectronic networks

机译:大规模混合光电网络的有效启发式方法

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This paper presents a new heuristic to solve efficiently the problem of dimensioning large-size hybrid optoelectronic networks with grooming. It is modeled as a large mixed integer program which cannot be solved to optimality in a reasonable amount of time for networks larger than 10 nodes. The heuristic is based on concepts borrowed from genetic algorithm, tabu search and simulated annealing. The definition of the populations and neighborhoods are discussed in depth along with the intensification and diversification procedures. An application of this heuristic to networks of up to 50 nodes has shown excellent results: The computational time is low and the average optimality gap is generally under 1%.
机译:本文提出了一种新的启发式方法,可以有效地解决具有修饰的大型混合光电网络规模化问题。它被建模为大型混合整数程序,对于大于10个节点的网络,无法在合理的时间内将其求解为最优。启发式算法基于从遗传算法,禁忌搜索和模拟退火中借用的概念。对人口和邻里的定义以及集约化和多样化程序进行了深入讨论。这种启发式方法在最多50个节点的网络上的应用显示了出色的结果:计算时间短,平均最优差距通常在1%以下。

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