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A bi objective dynamic reliable hub location problem with congestion effects

机译:BIA目标动态可靠的集线器位置问题拥塞效果

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摘要

In this paper, a new model of hub locating has been solved considering reliability and importance of flow congestion on hub nodes in a dynamic environment. Each of nodes considered as hubs and their communication paths with other non-hubs nodes have specific reliability. In order to reduce input flow to any hub and avoid creation unsuitable environmental and traffic conditions in that area, efficiency capacity is allocated to each hub, which is subject to a penalty in case of exceeding this amount. Another capability of this model is the ability of deciding whether hubs are active or inactive in each period, so hub facilities can be established or closed due to different conditions (such as changes in demand, legislative, etc.). The model is non-linear and bi-objective that the first goal is reducing transportation costs, hub rental fees and extra flow congestion penalties on hub nodes and the second goal is to increase the minimum designed network reliability. After linearization of the model, using -constraint method, optimal boundary is obtained. Also, to demonstrate the performance of the model, we use IAD dataset for solving problem. To evaluate the model, sensitivity analysis is presented for some of important parameters of the model.
机译:在本文中,已经解决了一种新的集线器定位模型,考虑了动态环境中集线器节点对流动拥塞的可靠性和重要性。作为集线器的每个节点及其与其他非集线器节点的通信路径具有特定的可靠性。为了减少任何集线器的输入流程,避免创造不适合的环境和交通条件在该领域,效率容量被分配给每个集线器,这在超过此金额的情况下受到惩罚。该模型的另一个能力是决定集线器是否在每个时段中处于活动状态或无效的能力,因此由于不同的条件(例如需求,立法等的变化,例如需求变化,立法等),可以建立或关闭集线器设施。该模型是非线性和双目标的,即第一个目标是降低运输成本,集线器租赁服务和集线器节点的额外流动性处罚,第二个目标是增加最低设计的网络可靠性。在模型线性化之后,使用-Co​​nstraint方法,获得最佳边界。此外,为了演示模型的性能,我们使用IAD数据集进行解决问题。为了评估模型,介绍了模型的一些重要参数的灵敏度分析。

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