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摘要: 从航速优化模型、油耗预测模型、航速优化模型求解方法与船舶能效管理系统方面, 分析了国内外航速优化研究现状, 探讨了航速优化存在的问题, 并针对这些问题提出了建议。研究结果表明: 在航运市场持续萎靡的情况下, 经济航行将被更广泛应用, 针对航速优化的研究仍然具有重要的意义; 在航速优化模型方面, 目前多集中在以碳排放政策、不确定因素的影响、排放控制区政策、船队调度等为单一优化目标建立航速优化模型, 优化目标主要为成本最小化和利润最大化, 未来应将航速与航线、纵倾、船队部署联合优化, 考虑多种不确定因素、多种优化目标建立航速优化模型; 在油耗预测模型方面, 预测模型主要分为白盒模型、黑盒模型和灰盒模型, 白盒模型具有更好的可解释性, 黑盒模型的预测性能更好, 灰盒模型弥补了白盒模型和黑盒模型的缺点, 将成为未来的研究重点, 未来应基于精确的船舶数据和先进的人工智能算法进行数据学习, 提升油耗预测模型预测准确性; 在优化算法方面, 由于航速优化模型的复杂性, 大多采用启发式算法进行优化求解, 这种算法可以减少优化求解时间和提高求解质量, 未来需要探索更加精确高效的求解算法; 在优化策略方面, 采用大数据分析可以识别天气对航行的影响, 动态优化策略可以补偿环境因素引起的扰动, 能够进一步提升船舶能效水平; 在船舶能效管理系统方面, 船舶能效管理系统主要包括航行数据采集、数据传输、数据储存、数据分析与智能决策等功能, 由于其成本高昂, 目前尚未在船舶上大规模运用。Abstract: The status of ship speed optimization research in domestic and overseas, including ship speed optimization models, fuel consumption prediction methods, solutions of ship speed optimization models, and ship energy efficiency management systems, were summarized and analyzed. The existing problems in speed optimization research were discussed, and suggestions were made to solve these problems. Analysis result shows that, under the condition in which the shipping market continues to be depressed, economic navigation will be used more widely, and research on speed optimization will remain of great significance.In terms of speed optimization models, most speed optimization models are established with carbon emission policy, influence of uncertain factors, emission control area(ECA) policy and fleet scheduling as a single optimization objective. The main optimization objectives of speed optimization models are to minimize the cost and maximize the profit. Speed should be combined with route, trim and fleet deployment optimization, and a model of speed optimization should be established considering various uncertain factors and optimization objectives in the future.In terms of fuel consumption prediction model, prediction models are mainly divided into white box, black box, and gray box models. The white box model is better in terms of model interpretability, the black box model offers better prediction performance, and the gray box model compensates for the disadvantages of the white box model and the black box model and will become the focus of future research.Data learning should be based on accurate ship data and advanced artificial intelligence algorithms to improve the prediction accuracy of fuel consumption prediction model.In terms of optimization algorithm, due to the complexity of speed optimization model, heuristic algorithm is mostly used for optimization solution. This algorithm can reduce the optimization solution time and improve the solution quality. More accurate and efficient solution algorithms need to be explored in the future.In terms of optimization strategy, the use of big data analysis can identify the influence of weather on navigation, and the use of dynamic optimization strategies can compensate for disturbances caused by environmental factors, enabling further improvement in the energy efficiency of ships.In terms of ship energy efficiency management system, the ship energy efficiency management system mainly includes navigation data acquisition, data transmission, data storage, data analysis and intelligent decision making, it has not been applied on a large scale on ships as its high cost.
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表 1 航速优化模型分类
Table 1. Classification of speed optimization models
文献 优化准则 船队规模 船舶类型 能否调整船队规模 油耗函数 是否考虑不同航段最佳航速 航路选择 是否考虑港口 是否考虑ECA 是否考虑不确定因素 是否考虑排放 [8] 年度利润 单船 集装箱船 否 三次函数 否 固定航线 否 否 否 是 [9] 航次利润 7艘单船 集装箱、油轮、散装船 否 三次函数 否 固定航线 否 否 否 否 [10] 年度成本 单船 集装箱船 否 三次函数 是 灵活航线 否 否 否 否 [11] 航次成本、排放、时间 船队 集装箱船 否 三次函数 是 灵活航线 是 否 否 是 [12] 航次成本、托运人满意度 单船 不定期货船 否 未指定 是 固定航线 是 否 否 否 [13] 航次利润 单船 未指定 否 三次函数 是 固定航线 是 否 否 是 [14] 航线利润 船队 集装箱船 能 三次函数 否 固定航线 是 否 否 是 [15] 周营运成本 船队 集装箱船 能 三次函数 否 固定航线 否 否 否 是 [16] 单位集装箱运输成本 9艘单船 集装箱 否 三次函数 否 固定航线 否 否 否 是 [18] 航次总油耗 单船 集装箱 否 三次函数 是 固定航线 是 否 是 是 [19] 航次总油耗或碳排放 单船 集装箱船 否 三次函数 是 固定航向 是 否 是 是 [20] 航次成本 2艘单船 集装箱船 否 三次函数 是 固定航线 是 否 是 否 [21] 航线成本 船队 集装箱船 否 幂函数 否 固定航线 是 否 是 否 [22] EEOI 单船 冰区船舶 否 三次函数 否 固定航线 否 否 是 否 [23] 航次燃油成本 单船 未指定 否 线性插值函数 是 灵活航线 是 是 否 否 [24] 每日利润 单船 未指定 否 三次函数 是 灵活航线 否 是 否 否 [25] 航次燃油费用、SO2排放 单船 集装箱船 否 线性插值函数 是 灵活航线 是 是 否 是 [26] 年度成本 船队 集装箱船 能 三次函数 是 灵活航线 否 是 否 是 [27] 年度成本 船队 集装箱船 能 三次函数 否 固定航线 否 否 否 是 [28] 年度成本 船队 集装箱船 能 三次函数 否 固定航线 否 否 否 否 [29] 周营运成本 船队 集装箱船 否 幂函数 是 灵活航线 是 否 否 否 [30] 年度燃油消耗、碳排放 船队 散货船 否 未指定 否 固定航线 否 否 否 是 [31] 航线油耗 船队 散货船 否 未指定 是 固定航线 是 否 否 否 
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表 2 油耗预测模型优缺点比较
Table 2. Advantages and disadvantages comparison of fuel consumption prediction models
模型类别 模型可解释性 预测准确性 对历史数据的需求 外推能力 对专业知识的需求 白盒模型 较好 一般 不需要 较好 需要 黑盒模型 差 较好 大量 差 不需要 灰盒模型 较好 较好 少量 较好 需要
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表 3 油耗预测模型分类
Table 3. Classification of fuel consumption prediction models
文献 船舶类型 预测模型类别 理论方法 预测模型输入 预测模型输出 数据采集方法 [36] 内河船舶 白盒模型 Holtrop-Mennnen方法 主机转速、风速、浪高、流速 对地航速和单位时间油耗量 数据采集系统 [37] 内河游船 白盒模型 Holtrop-Mennnen方法 对水航速、流速 对地航速和单位时间油耗量 数据采集系统 [40] 油轮 白盒模型 Kwon方法 航速、风浪方向、风浪等级、洋流速度、洋流方向 每小时油耗量 航行日志 [41] 油轮 白盒模型 Holtrop-Mennnen方法和改进Kwon方法 对水航速、风浪方向、风浪等级 单位时间油耗量 航行日志 [42] 集装箱船 白盒模型 Kwon方法和Aertssen方法 航速、船长、风浪方向和等级 每小时油耗量 无 [43] 内河船舶 黑盒模型 BPNN 主机转速、风速、风向、水深、流速 对地航速和单位时间油耗量 数据采集系统 [44] 散货船 黑盒模型 ANN和遗传算法 发动机转速、风速、风向、浪高、流速 对地航速和单位时间油耗量 数据采集系统 [45] 冰区船舶 黑盒模型 BPNN 冰浓度、航速 EEOI 数据采集系统 [46] 内河船舶 黑盒模型和白盒模型 BPNN和Holtrop-Mennnen方法 主机转速、风速、风向、水深、流速 对地航速和单位时间油耗量 数据采集系统 [47] 集装箱船 黑盒模型 LASSO 船体数据、天气数据、海况数据等 每日油耗量 航运公司航行数据平台 [48] 散货船 多种黑盒模型 线形回归、决策树回归、随机森林回归、额外树回归、SVR、K最近邻、ANN和集成方法 航速、发动机转速、流速、风速、风向、海况、吃水等 每日油耗量 数据采集系统和航行日志 [49] 内河旅游船 黑盒模型 随机森林算法 航速、风速、风向、流速、水深 每公里油耗量 数据采集系统 [50] 特大型油轮 黑盒模型 ANN和多元回归 船舶对地航速、水深、风速、涌浪和波浪等级、海流大小等参数 每海里油耗量 船舶自动连续检测系统、自动识别系统和天气预报 [51] 集装箱船 黑盒模型 ASAE 船体数据、天气数据、主机数据等 船舶航速 数据采集系统 [52] 化学品船 白盒模型、黑盒模型和2种灰盒模型 Harvald方法、正则化最小二乘法、LASSO回归、随机森林回归 船体数据、主机数据、天气数据等 轴功率、轴扭矩和主机油耗 数据采集系统 [53] 集装箱船 灰盒模型 Kwon方法和最小二乘法 航速、排水量、波高、风浪方向、风浪等级 每日油耗量 航行日志 [54] 油轮 灰盒模型 Kwon方法和遗传算法 航速、排水量、风浪方向、风浪等级 每日油耗量 航行日志
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表 4 航速优化模型求解方法分类
Table 4. Classification of speed optimization model solution methods
文献 优化准则 优化对象 船舶类型 船队规模 优化算法 [12] 航次成本、托运人满意度 不同航段船舶航速 不定期货船 单船 粒子群算法 [56] 航次油耗量 不同航段的船舶航速 未指定 单船 最短路径算法 [57] 航线利润 船舶货物分配、船舶航线、船舶航速 不定期船 船队 多起点局部搜索算法、递归平滑算法 [58] 航次燃油成本、排放 不同航段的船舶航速 货船 单船 高效的SOP算法 [59] 航线利润 船舶航线、不同航段的船舶航速 不定期油轮 船队 一种启发式的分支定价算法 [60] 计划期限内的船队利润 船队部署、船舶航速 滚装船 船队 滚动式启发算法 [61] 航次油耗、安全性 发动机转速 散货船 单船 粒子群算法 [62] 航次燃油成本 船舶航线、不同航段的船舶航速 班轮 单船 禁忌搜索算法 [63] 航线成本 船舶航线、不同航段的船舶航速 未指定 单船 Dijkstra算法、CPLEX求解器 [65] 航次油耗量 不同时间步长下的船舶航速 旅游船 单船 动态优化优化算法设计的DOSEE控制器 [66] 给定时间段内的油耗量 不同航段的船舶纵倾、船舶航速 未指定 单船 基于动态规划的两步全局优化算法 [67] 航线燃油消耗 不同航段的船舶航速 长江旅游船、货船和集装箱船 单船 大数据分析、K-means聚类算法、粒子群算法 [68] 航线燃油消耗、服务水平 不同航段的船舶航速 班轮 单船 大数据分析、粒子群算法
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