基于运输需求时/空特征的不定期船舶运输的调度优化

考虑货主的选择行为与运输需求的时空分布特征, 把承运人的船舶运营期划分为多个连续的时间窗, 基于离散选择模型把货主的选择惯性转化为承运人在航段上的市场份额, 对不同时间窗内承运人在即期市场上应承担的货运量进行优化; 以承运人利润最大为目标构建优化模型, 求解规划期内船舶的运营调度方案, 确定船舶承运的货物和航次衔接; 选取太平洋地区包括中国、加拿大、澳大利亚、俄罗斯、印度尼西亚、巴西和美国在内的7个国家作为干散货主要进出口国, 在每个国家确定一个港口作为网络节点, 根据克拉克森官网发布的航线、运价与干散货需求等数据对不定期船舶进行调度优化, 并采用遗传算法求解模型。计算结果表明: 在相同的运输时间窗内, 在优化方案下, 船舶航行时间为58 d, 收益为3.01×105美元, 在传统调度模式下, 单纯追求每个航段的收益最大化, 船舶航行时间为56 d, 收益为2.48×105美元, 优化方案的利润高出5.30×104美元, 因此, 为了最大化运营期的利润, 在货运需求时空变化和货主选择惯性的影响下, 船舶在某些时间窗内应执行空载或利润较低的航次。 

Scheduling optimization of tramp shipping based on temporal and spatial attributes of shipping demand

The shippers' choice behaviors and the temporal and spatial distribution characteristics of shipping demand were considered, the carrier's ship operation period was divided into multiple continuous time windows, the selection inertia of the shipper was transformed into the potential market shares of the carriers on the shipping segment based on the discrete selection model, and the freight volumes of the carriers in the spot market in different time windows were optimized. An optimization model was built with the maximum profits of the carriers as the objective, and the shipping scheduling scheme was solved during the planning period, so as to determine the shipping cargo and voyage connection. Seven countries in the Pacific region, including China, Canada, Australia, Russia, Indonesia, Brazil, and America, were selected as the main importers and exporters of dry bulk cargoes, and one port of each country was selected as the node of transport network. According to the data published by Clarkson's official website, such as the routes, freight rates, and demand of dry bulk cargoes, the optimal scheduling of tramp ships be obtained by the genetic algorithm. Computation result shows that in the same shipping time window, the sailing time and profit of the ship are 58 days and 3.01×105 USD under the optimal scheduling scheme, respectively. While, in the traditional scheduling scheme maximizing the profit on each segment, the sailing time and profit of the ship are 56 days and 2.48×105 USD, respectively, and the profit is 5.30×104 USD lower than the profit under the optimal scheduling scheme. Therefore, in order to maximize the profit in the shipping period, under the influence of the temporal and spatial change of freight demand and the inertia of shipper choice, the ship should carry out the voyage without profit or with low profit in some time windows.