| 液化天然气库存路径问题建模与算法 |
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| 引用本文： | 巫威眺,王殿雷,马昌喜. 液化天然气库存路径问题建模与算法[J]. 中国公路学报, 2022, 35(11): 252-270. DOI: 10.19721/j.cnki.1001-7372.2022.11.023 |
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| 作者姓名： | 巫威眺 王殿雷 马昌喜 |
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| 作者单位： | 1. 华南理工大学 土木与交通学院, 广东 广州 510641;2. 兰州交通大学 交通运输学院, 甘肃 兰州 730070 |
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| 基金项目： | 国家自然科学基金项目（72071079,52272310,71861023） |
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| 摘 要： | 考虑液化天然气（LNG）的在途挥发、转移挥发与库存挥发对配送成本与风险的影响,根据LNG风险特性采用蒸汽爆炸模型量化库存和运输风险,并针对传统单因素风险评估方法的不足,结合多源数据（兴趣点密度、土地生产总值产出率和人口密度）构建多因素复合风险评估指标反映事故严重程度的空间异质性,建立库存路径问题双目标优化模型,实现多周期LNG库存和配送方案的联合优化。根据问题的特征,设计基于贪婪策略预优化并结合变邻域搜索（VNS）的多目标粒子群（MOPSO）混合优化算法,且通过标准测试函数对改进前后的MOPSO算法和非支配遗传算法（NSGA-Ⅱ）进行比较;与NSGA-Ⅱ相比,MOPSO在结合VNS前后分别具有32%和42%的收敛性优势,结合VNS混合优化相比原始MOPSO有15%的收敛性优势。最后,以广州地区LNG加气站供应体系进行案例分析。研究结果表明：库存与运输成本存在利益背反关系,且在短暂缺货时总成本较低;忽略挥发的影响会导致小批量频繁补货,从而增加不必要的运输成本;LNG挥发成本占总成本的10%~20%,库存挥发率对成本影响较大,但对风险影响很小,当库存挥发率低于2%时投资降低挥发率带来的经济效益较大,当超过2%时,投入产出比迅速降低;风险限值约束对路径选择和成本影响较大,20%风险限值的降低带来了10%总成本的提高,但20%风险限值的提高仅降低5%的总成本,说明总成本在逐步接近不考虑风险时的最低值,存在优化上限。
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| 关 键 词： | 交通工程 LNG 混合优化算法 危险品运输管理 多因素风险评估 库存路径问题 |
| 收稿时间： | 2021-04-28 |
Model and Algorithm for Inventory Routing Problem of Liquified Natural Gas |
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| WU Wei-tiao,WANG Dian-lei,MA Chang-xi. Model and Algorithm for Inventory Routing Problem of Liquified Natural Gas[J]. China Journal of Highway and Transport, 2022, 35(11): 252-270. DOI: 10.19721/j.cnki.1001-7372.2022.11.023 |
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| Authors: | WU Wei-tiao WANG Dian-lei MA Chang-xi |
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| Affiliation: | 1. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510641, Guangdong, China;2. School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China |
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| Abstract: | In this study, we considered the impact of in-transit, transfer, and inventory volatilization of liquefied natural gas (LNG) on distribution costs and risks. According to the risk characteristics of LNG, a steam explosion model was adopted to quantify the inventory and transportation risks. To overcome the drawbacks of traditional single-factor risk assessment methods, we developed a multi-factor compound risk assessment index combining multi-source data (point of interest density, gross domestic product output rate, and population density) to capture the spatial heterogeneity of accidents. In this study, a two-objective optimization model of the inventory routing problem was developed to jointly optimize the multi-period LNG inventory and distribution schemes. Based on the characteristics of the problem, a hybrid optimization algorithm of multi-objective particle swarm optimization (MOPSO) based on greedy strategy pre-optimization and integration of variable neighborhood search (VNS) was designed. The MOPSO algorithm and NSGA-Ⅱ (non-dominated sorting genetic algorithm II) algorithm were tested using the standard test functions. Compared to NSGA-Ⅱ, MOPSO shows a convergence advantage of 32% before combining VNS, which increases to 42% when VNS is combined. Combining the VNS hybrid optimization also leads to a 15% convergence advantage over the original MOPSO. Finally, the case analysis of the LNG filling station supply system in Guangzhou shows the existence of a trade-off between the inventory and transportation costs; when there is a short-term shortage, the total cost is lower. Neglecting volatilization leads to frequent small-volume replenishment, which increases unnecessary transportation costs. The cost of LNG volatilization accounts for 10%-20% of the total cost. The inventory volatilization rate has a significant impact on the cost but has little impact on the risk. When the inventory volatilization rate is lower than 2%, the economic benefit, brought by the investment reduction in the volatilization rate, is greater, and when it exceeds 2%, the input-output ratio decreases rapidly, and the risk limit constraint has a greater impact on routing and cost. The 20% risk limit reduction results in a 10% increase in the total cost, but the 20% risk limit increase only reduces the total cost by 5%. This indicates that the total cost gradually approaches the lowest value without considering the risk factor, and that there is an upper limit for optimization. |
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| Keywords: | traffic engineering LNG hybrid optimization algorithm hazmat transportation management multi-factor risk assessment inventory routing problem |
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