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摘要: 为系统分析和总结航运管理的研究现状与发展趋势, 针对WOS数据库和CNKI数据库收录的628篇文献, 用知识图谱分析软件VOSviewer进行航运管理共词聚类分析, 得到航运管理的3个研究热点, 即航运市场分析、航运运营管理和绿色航运; 综述了航运管理研究的范围、对象与方法, 分析了航运管理未来的主要研究方向。研究结果表明: 目前主要采用时间序列模型分析航运市场, 围绕运价研究货运市场与船舶市场的供需关系; 航运运营管理的研究多集中在以成本最小化或利润最大化为目标建立数学优化模型, 并设计启发式算法求解战略、战术和运作3个层面上的决策问题; 绿色航运研究侧重于解决实际的减排问题, 对技术性措施、营运性措施和基于市场的措施进行成本效益、减排效果的比较和分析。未来有关航运管理的研究方向主要包括: 建立多目标、多阶段数学优化模型, 满足多元化的航运管理目标, 实现不同范围和级别航运管理的协同优化; 从海运供应链的角度拓展航运管理研究, 一体化考虑内陆运输和海上运输以及各利益相关者之间的复杂关系; 研究不确定条件下的航运管理问题; 基于人工智能算法和航运大数据, 设计更准确高效的市场分析方法和模型求解算法; 研究智能航运新业态下的航运管理问题。Abstract: In order to systematically analyze and summarize the research status and development trend of shipping management, the co-word cluster analysis of shipping management based on the 628 literatures from WOS Database and CNKI Database was carried out by knowledge map analysis software VOSviewer, and three research hotspots were obtained, including shipping market analysis, shipping operation management and green shipping. According to above three hotspots, the researching areas, objectives and methods of shipping management were summarized, and the main directions of future research were put forward. Research result shows that the time-series model is mainly adopted to analyze shipping market, and the relationship between the supply and demand of freight market and shipping market is studied mainly based on the freight rate. The research of shipping operation management mostly focuses on setting up optimal mathematical model with the objectives of minimizing cost or maximizing profit, and using the heuristic algorithms to deal with the problems at the strategic, tactical and operational decision-making levels.The current research of green shipping mainly solves the practical emission reduction problem, and compares and analyzes the cost-effectivenesses and emission reduction effects of technical measures, operational measures and market-based measures. The future main research directions of shipping management are as follows: the multi-objective and multi-stage mathematical optimization model should be established to meet the various goals of shipping management in order to achieve the collaborative optimization of shipping managements with different scopes and levels; the research of shipping management should be extended from the perspective of shipping supply, and it is necessary to integrally consider the complex relationships among inland transportation, maritime transportation and stakeholders; the issues of shipping management should be investigated under uncertain conditions; the market analysis methods and model solving algorithms with higher accuracy and efficiency should be designed based on the artificial intelligent algorithms and shipping big data; and the shipping management in the new format of intelligent shipping should be researched.
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Key words:
- water transportation /
- shipping management /
- shipping market /
- operation management /
- green shipping /
- review
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图 1 全球海运贸易量和世界船队规模
Figure 1. International maritime trade volumes and world fleet scales
图 3 航运管理关键词共现叠加图谱
Figure 3. Keywords co-occurrence overlay mapping of shipping management
表 1 航运市场的研究总结
Table 1. Research summary on shipping market
研究范围 研究主题 研究对象 研究方法 文献来源 货运市场 运价波动性 干散货市场 向量自回归(Vector Autoregression, VAR)模型、向量误差校正模型(Vector Error Correction Model, VECM)、自回归广义自回归条件异方差(Autoregressive-Generalized Autoregressive Conditional Heteroskedasticity, AR-GARCH)模型、集成连续自回归(Integrated Continuous Autoregressive, ICAR)模型、经验模态分解-小波分析(Empirical Mode Decomposition-Wavelet Analysis, EMD-WA)模型 [12]~[15] 运价预测 干散货市场 自回归移动平均(Autoregressive Moving Average, ARMA)模型、霍尔特-温特(Holt-Winters)非季节模型、非线性自回归动态网络(Non-linear Autoregressive Dynamic Network, NARNET)模型、具有外部输入的非线性自回归神经网络(Non-linear Autoregressive Neural Network with External Input, NARXNET)模型 [16]、[19] 班轮市场 差分整合移动平均自回归(Autoregressive Integrated Moving Average, ARIMA)模型、自回归条件异方差(Autoregressive Conditional Heteroscedasticity, ARCH)模型 [17] 油运市场 人工神经网络(Artificial Neural Network, ANN)模型、自适应遗传算法(Adaptive Genetic Algorithm, AGA) [18] 市场定价及影响机制 班轮市场 合作博弈理论、价格方程和回归分析、二元广义自回归条件异方差(Generalized Autoregressive Conditional Heteroscedasticity, GARCH)模型 [20]、[21]、[23] 干散货市场 价格博弈理论 [22] 船舶市场 运价与船舶市场价格的相互影响 造船市场、二手船市场、拆船市场 GARCH模型、单方程模型、结构方程建模 [24]~[26] 
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表 2 航运运营管理的研究总结
Table 2. Research summary on shipping operation management
研究范围 研究主题 研究目标 模型类型 求解算法 文献来源 战略层 新组建船队规划 总成本最小化 整数规划、动态规划、非线性规划 遗传算法、动态规划算法、集合划分算法 [28]、[30]、[32] 总收益最大化 动态规划 最短路径算法、技术经济性分析 [29]、[31] 船队更新 总成本最小化 随机规划、随机混合整数规划 Xpress-MP软件、滚动时域算法 [33]、[34]、[36] 多目标最优 动态规划 多目标离散粒子群优化算法 [35] 总收益最大化 整数规划 设计求解算法 [38] 战术层 分支航线网络 总成本最小化 整数规划、随机VRP、混合整数线性规划 遗传算法、适应邻域搜索算法 [39]~[41] 货运需求最大化 整数规划 智能启发式算法 [42] 多港挂靠航线网络 总成本最小化 混合整数非线性规划、混合整数规划 CPLEX软件、滚动时域算法、GAMS/OSICPLEX求解器 [44]、[46]、[48]~[50] 总收益最大化 混合整数规划、两阶段模型 遗传算法、CPLEX软件、BCB算法 [43]、[45]、[47] 轴辐式航线网络 总成本最小化 整数规划、混合整数规划 遗传算法、CPLEX软件 [54]~[57] 总收益最大化 混合整数线性规划 分解算法 [52] 市场份额最大化 混合整数线性规划 拉格朗日分解算法 [51] 多目标最优 博弈论 区间分支定界法 [53] 混合式航线网络 总成本最小化 混合整数线性规划、混合整数非线性规划 CPLEX软件、分段线性逼近函数、分支定界法、拉格朗日分解算法 [58]~[62] 总收益最大化 混合整数非线性规划 二阶锥规划(Second-Order Cone Programming, SOCP)算法、禁忌搜索算法 [63] 运作层 大宗工业物资运输 总成本最小化 混合整数规划 Xpress-MP软件、基于滚动时域和松弛-固定的启发式算法、动态规划算法 [64]、[66]、[67] 多目标最优 混合整数规划 CPLEX软件 [65] 不定期船运输 总收益最大化 混合整数非线性规划、非线性规划、混合整数规划 集合划分算法、多起始点局部搜索启发式算法、遗传算法 [68]~[71] 班轮运输 总成本最小化 整数规划、随机规划、混合整数规划 最短路和两阶段启发式算法、基于向后价值迭代的最优控制策略、加速粒子群优化(Accelerated Particle Swarm Optimization, APSO)算法 [74]~[75] 总收益最大化 混合整数非线性规划 分支定界法 [73] 多目标最优 整数规划、混合整数规划 蚁群算法和邻域搜索技术、CPLEX软件 [72]~[77]
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表 3 绿色航运的研究总结
Table 3. Research summary on green shipping
研究范围 研究主题 研究对象 研究方法 文献来源 技术性措施 成本效益比较 SOx、碳减排措施 减排成本估计、现金流建模、净现值估计、两阶段随机优化模型、边际减排成本曲线 [82]、[83]、[85]、[86]、[88] 减排效果比较 SOx减排措施 年燃油消耗量估计 [84] 综合评价 SOx、NOx减排措施 TOPSIS、AHP、FAHP、证据理论 [87]、[89]、[90] 营运性措施 减排效果分析 减速航行 利润最大化方程、实证分析、t检验 [91]、[92]、[97] 绿色航运运营管理优化 航速、船舶配载、燃油切换位置、网络结构 GSRSP、航速优化模型、航运网络设计模型 [93]~[96]、[98] 基于市场的措施 实施效果分析 国际碳税、航运燃油税 GTAP-E模型、蛛网原理 [99]、[100] 运营管理优化 海事排放贸易计划、欧盟的排放收费计划 船队规划模型、航运网络设计模型、船队构成和航线配船优化模型 [101]~[103]
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