具有供应不确定性的随机循环库存路由:绿色氢气物流案例

IF 4.4 2区 工程技术 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Transportation Science Pub Date : 2024-01-04 DOI:10.1287/trsc.2022.0435
Umur Hasturk, Albert H. Schrotenboer, Evrim Ursavas, Kees Jan Roodbergen
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引用次数: 0

摘要

利用电力可以从水中生产氢气。与电力本身不同,氢气随后可以大量储存。这使得太阳能和风能的生产与使用不同步。因此,氢有望成为实现气候中和经济的关键要素。然而,氢的物流非常复杂。必须确定网络中多个地点的库存政策,还必须安排从生产地点到客户的氢气运输。同时,氢气的生产模式是间歇性的,这影响了实现计划运输和库存水平的可能性。为了提供高效运输和储存氢气的策略,本文针对随机循环库存路由问题提出了一种参数化成本函数近似方法。首先,我们的方法包括一个参数化混合整数编程(MIP)模型,该模型可生成氢气车辆运输的固定和重复时间表。其次,考虑到生产量和需求量的不确定性,通过马尔可夫决策过程(MDP)模型进一步优化生产不足或生产过剩情况下的买卖决策。为了联合优化参数化 MIP 和 MDP 模型,我们的方法包括一种算法,通过迭代求解 MIP 和 MDP 模型来搜索参数空间。我们进行了计算实验,在各种问题设置中验证了我们的模型,并证明它能提供接近最优的解决方案。此外,我们还在荷兰两个氢气生产基地的专家评审案例研究中测试了我们的方法。我们为该地区的利益相关者提供了见解,并分析了这些案例研究中各种问题要素的影响:本项目得到了燃料电池和氢气 2 联合企业(现为清洁氢伙伴关系)的资助,资助协议为[875090]。该联合事业得到了欧盟地平线 2020 研究与创新计划、欧洲氢能计划和欧洲氢能研究计划的支持。A. H. Schrotenboer 通过[VI.Veni.211E.043号拨款]获得了荷兰科学基金会(Nederlandse Organisatie voor Wetenschappelijk Onderzoek; NWO)的支持。
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Stochastic Cyclic Inventory Routing with Supply Uncertainty: A Case in Green-Hydrogen Logistics
Hydrogen can be produced from water, using electricity. The hydrogen can subsequently be kept in inventory in large quantities, unlike the electricity itself. This enables solar and wind energy generation to occur asynchronously from its usage. For this reason, hydrogen is expected to be a key ingredient for reaching a climate-neutral economy. However, the logistics for hydrogen are complex. Inventory policies must be determined for multiple locations in the network, and transportation of hydrogen from the production location to customers must be scheduled. At the same time, production patterns of hydrogen are intermittent, which affects the possibilities to realize the planned transportation and inventory levels. To provide policies for efficient transportation and storage of hydrogen, this paper proposes a parameterized cost function approximation approach to the stochastic cyclic inventory routing problem. Firstly, our approach includes a parameterized mixed integer programming (MIP) model which yields fixed and repetitive schedules for vehicle transportation of hydrogen. Secondly, buying and selling decisions in case of underproduction or overproduction are optimized further via a Markov decision process (MDP) model, taking into account the uncertainties in production and demand quantities. To jointly optimize the parameterized MIP and the MDP model, our approach includes an algorithm that searches the parameter space by iteratively solving the MIP and MDP models. We conduct computational experiments to validate our model in various problem settings and show that it provides near-optimal solutions. Moreover, we test our approach on an expert-reviewed case study at two hydrogen production locations in the Netherlands. We offer insights for the stakeholders in the region and analyze the impact of various problem elements in these case studies.Funding: This project received funding from the Fuel Cells and Hydrogen 2 Joint Undertaking (now Clean Hydrogen Partnership) under [Grant Agreement 875090]. The Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme, Hydrogen Europe and Hydrogen Europe Research. A. H. Schrotenboer received support from the Dutch Science Foundation (Nederlandse Organisatie voor Wetenschappelijk Onderzoek; NWO) through [Grant VI.Veni.211E.043].
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来源期刊
Transportation Science
Transportation Science 工程技术-运筹学与管理科学
CiteScore
8.30
自引率
10.90%
发文量
111
审稿时长
12 months
期刊介绍: Transportation Science, published quarterly by INFORMS, is the flagship journal of the Transportation Science and Logistics Society of INFORMS. As the foremost scientific journal in the cross-disciplinary operational research field of transportation analysis, Transportation Science publishes high-quality original contributions and surveys on phenomena associated with all modes of transportation, present and prospective, including mainly all levels of planning, design, economic, operational, and social aspects. Transportation Science focuses primarily on fundamental theories, coupled with observational and experimental studies of transportation and logistics phenomena and processes, mathematical models, advanced methodologies and novel applications in transportation and logistics systems analysis, planning and design. The journal covers a broad range of topics that include vehicular and human traffic flow theories, models and their application to traffic operations and management, strategic, tactical, and operational planning of transportation and logistics systems; performance analysis methods and system design and optimization; theories and analysis methods for network and spatial activity interaction, equilibrium and dynamics; economics of transportation system supply and evaluation; methodologies for analysis of transportation user behavior and the demand for transportation and logistics services. Transportation Science is international in scope, with editors from nations around the globe. The editorial board reflects the diverse interdisciplinary interests of the transportation science and logistics community, with members that hold primary affiliations in engineering (civil, industrial, and aeronautical), physics, economics, applied mathematics, and business.
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