海洋垃圾回收船舶路径多目标优化

Multi Objective Optimization of VesselRouting for Marine Debris Collection

海洋垃圾污染不仅会破坏海洋生态系统,而且对人类健康也会造成一定的威胁。派遣船舶对近海漂浮的海洋垃圾回收是减少海洋垃圾污染的一种有效方法。由于风和洋流的影响,海洋垃圾的位置是不断变化的。因此,对基于可移动时间窗的海洋垃圾回收船舶路径优化进行了研究,即对同一个垃圾点,设置多个时间跨度适当的时间窗,船舶可以选择在其中一个时间窗内执行收集任务。为了降低船舶回收成本和碳排放量,建立了船舶走行时间和碳排放量的多目标优化模型。并将改进的自适应大规模领域搜索算法作为领域搜索机制,嵌入速度优化,提出了一种基于分解策略的多目标优化算法对其进行求解,即MOEA/D ALNS算法。并通过一组数值实验验证了所提模型和算法的有效性。实验结果表明,与基于遗传算法的MOEA/D算法和NSGA II算法相比,MOEA/D ALNS算法在运行时间和结果上均有明显的优势。此外,对时间窗数量分析可得,随着可移动时间窗数量增多,船舶回收平均成本和碳排放量降低。

Marine debris pollution will not only damage the marine ecosystem,but also pose a threat to human health.Dispatching vessels to collect the floating marine debris is an effective method to reduce marine debris pollution.The location of marine debris is constantly changing due to the influence of wind and ocean currents.Therefore,research has been conducted on the optimization of marine debris collection vessel routes based on movable time windows.Specifically,multiple time spans with appropriate time windows are set for the same debris collection point,and the vessel can choose to perform the collection task in one of the time windows.In order to reduce the cost of vessel recycling and carbon emissions,a multi objective optimization model for vessel travel time and carbon emissions is established.And the improved adaptive large scale domain search algorithm is used as the domain search mechanism,embedded with speed optimization.Consequently,a multi objective optimization algorithm based on decomposition strategy is proposed to solve it,namely the MOEA/D ALNS algorithm.And the effectiveness of the proposed model and algorithm is verified through a set of numerical experiments.The experimental results show that compared with the genetic algorithm based MOEA/D algorithm and NSGA II algorithm,the MOEA/D ALNS algorithm has significant advantages in runtime and results.In addition,the analysis of the number of time windows shows that as the number of movable time windows increases,the average cost of vessel recycling and carbon emissions decrease.