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首页> 外文期刊>Sadhana: Academy Proceedings in Engineering Science >A P-hub median network design problem with preventive reliability approach for before and after hub failure
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A P-hub median network design problem with preventive reliability approach for before and after hub failure

机译:一种P-Hub中位数网络设计问题,具有预防性可靠性方法,在集线器故障之前和之后

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摘要

Hubs are vital elements of communication and transportation networks and play an important role in interchanging the flows of information/passenger/goods. For this purpose, designing a highly reliable hub network is very critical, because inefficiency of even a single hub across the network tends to reduce the efficiency of the whole network in transferring the flow appropriately. In this research, a bi-objective mathematical model was designed to study the situations before and after hub failure. Considering reliability, the first objective was to maximize the flow through the network, and the second objective was to prevent wasting the flow due to a possible hub failure. The lexicographic method was used to solve this multi-objective problem with dependent objectives. This method represents an appropriate solution for problems whose objective functions are of different priorities or depend on one another. Various cases of different sizes were used to evaluate the model in terms of reliability. Since the hub location problem is an NP-Hard problem of commonly large dimensions, a hybrid meta-heuristic algorithm called memetic algorithm was used to have it solved. The algorithm was a combination of genetic algorithm with simulated annealing algorithm, where simulated annealing algorithm was used for local neighborhood search. Findings indicated that, consideration of the backup hub tends to enhance route reliability, thereby increasing the flow through the network, as compared to the case with no backup hub.
机译:集线器是通信和运输网络的重要元素,并在互换信息/乘客/货物的流量方面发挥着重要作用。为此目的,设计高度可靠的集线器网络非常关键,因为即使在网络上均匀的单个集线器的低效率趋于降低整个网络适当地转移流动的效率。在这项研究中,设计了一种双目标数学模型,旨在研究集线器故障前后的情况。考虑到可靠性,第一个目标是通过网络最大化流量,第二个目标是防止由于可能的集线器故障而浪费流量。利用依赖目标来解决词典方法来解决这种多目标问题。该方法代表了一个适当的解决方案,其目的函数具有不同优先级或彼此依赖。在可靠性方面,使用各种不同尺寸的案例来评估模型。由于集线器位置问题是通常大尺寸的NP难题,因此使用称为MECET算法的混合元启发式算法来解决。该算法是具有模拟退火算法的遗传算法的组合,其中模拟退火算法用于本地邻域搜索。结果表明,与没有备份集线器的情况相比,备份集线器的考虑趋于提高路径可靠性,从而增加通过网络的流量。

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