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Multiperiod transshipment location-allocation problem with flow synchronization under stochastic handling operations

机译:随机处理操作下流动同步的多级转运位置分配问题

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The transshipment location-allocation problem consists of locating transshipment facilities (e.g., intermodal hubs) of a transportation network and allocating freight flows through them, from several origins to several destinations, to satisfy demand and supply constraints. The objective is to maximize the total net transportation utility given by the total shipping utility minus the total cost to locate the facilities. Moreover, flow synchronization at the facilities must also be ensured. Unfortunately, the flow synchronization depends on a broad set of unknown events, which could cause both unexpected reductions of the facility capacity and uncertain utility of handling operations. In this paper, we first want to evaluate how uncertainty on facility capacity and handling operations utility affects the transshipment location-allocation problem in terms of complexity, net gain, and optimal solutions. Moreover, we extend the problem from a single to a multi-period setting to have a wider view of future scenarios realizations and consequently synchronize the flows by using different facilities on different periods. We propose a two-stage stochastic programming formulation with recourse and analyze, over a ground set of instances, some well-known economic indicators to derive managerial insights on the importance of addressing uncertainty for the problem. Finally, given the computational burden of solving the deterministic equivalent problem, we propose several heuristics based on progressive hedging and test their performance.
机译:转运地点分配问题包括定位运输网络的转运设施(例如,多式联运集线器),并从几个起源到几个目的地,分配货运流量,以满足需求和供应限制。目标是最大限度地提高总送货效用的总净运输效用减去总成本来定位设施。此外,还必须确保设施的流量同步。不幸的是,流量同步取决于广泛的未知事件,这可能导致设备容量的意外减少和处理操作的不确定效用。在本文中,我们首先要评估设施容量和处理操作的不确定性如何在复杂性,净增益和最佳解决方案方面影响转运位置分配问题。此外,我们将问题从单个到多个时段设置扩展到多个时期设置,以便对未来的情景实现更广泛的视图,从而通过在不同时段上使用不同的设施来同步流动。我们提出了一个两阶段随机编程配方,通过追索和分析,在地面实例上,一些知名的经济指标,以获得对解决问题不确定性的重要性的管理洞察力。最后,鉴于解决确定性等同物问题的计算负担,我们提出了几个基于渐进对冲和测试其性能的启发式方法。

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