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首页> 外文期刊>Transportation Research Part B: Methodological >A deteriorating inventory routing problem for an inland liquefied natural gas distribution network
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A deteriorating inventory routing problem for an inland liquefied natural gas distribution network

机译:内陆液化天然气分销网络的不断恶化的库存路由问题

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Liquefied Natural Gas (LNG) is natural gas that is converted into its liquid state for logistical benefits. It is also becoming a more viable alternative energy source due to its price competitiveness and environmental friendliness. We study an inventory routing problem for inland distribution of LNG from a storage facility to several filling stations. Here, a transport planner is responsible for the inventory management at the storage facility and filling stations, as well as for the routing and scheduling of a heterogeneous fleet of vehicles. LNG evaporates at a constant rate over time at the storage facility and at the filling stations, and this characteristic relates to the inventory management problems with deterioration described in the literature. Therefore, the problem under study is denoted an LNG Deteriorating Inventory Routing Problem (LNG-DIRP). As a solution method, we propose a matheuristic that combines a mixed integer programming formulation and an adaptive large neighborhood search algorithm. Results of extensive computational experiments confirm the efficiency of the proposed solution method and provide managerial insights to promote LNG as an alternative clean energy solution for the future of transportation. Furthermore, we examine several replenishment policies that are of interest to practitioners and regulatory bodies. (C) 2019 Elsevier Ltd. All rights reserved.
机译:液化天然气(LNG)是为了后勤利益而转换成液态的天然气。由于其价格竞争力和环境友好性,它也正成为一种更可行的替代能源。我们研究了将LNG从存储设施向多个加油站进行内陆配送的库存路由问题。在这里,运输计划员负责存储设施和加油站的库存管理,以及各种车队的路线安排和调度。随着时间的推移,LNG在存储设施和加油站以恒定的速率蒸发,该特性与文献中描述的变质的库存管理问题有关。因此,正在研究的问题称为LNG恶化的库存路由问题(LNG-DIRP)。作为一种解决方法,我们提出了一种结合混合整数规划公式和自适应大邻域搜索算法的数学方法。大量计算实验的结果证实了所提出的解决方案方法的效率,并提供了管理上的见识,以促进LNG作为未来交通运输的替代清洁能源解决方案。此外,我们研究了从业人员和监管机构感兴趣的几种补货政策。 (C)2019 Elsevier Ltd.保留所有权利。

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