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Ship Route Optimization Considering On-Time Arrival Probability Under Environmental Uncertainty

机译:考虑环境不确定性准时到达概率的船舶航路优化

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摘要

As international regulations for commercial ships regarding environmental pollution and global warming are being reinforced, worldwide efforts are growing to reduce the fuel consumption of ships; this is directly related to the emissions of environmental pollutants and greenhouse gases. A common method to reduce the fuel consumption of ships is to find a ship route that consumes less fuel. In many existing ship route optimization studies, the desired ship routes are calculated using a single objective optimization algorithm such as A * to minimize the path length, travel time, or fuel consumption. However, it is practically more important to reach the destination no later than the alloted time slot at a port even under weather uncertainties. In this study, a multi-objective optimization algorithm is employed to calculate the Pareto set with two objective functions: the fuel consumption and the expected time of arrival. Subsequently, using the Pareto set, the uncertainty of the arrival time and the probability that the ship will arrive within the specified time are estimated. Finally, the route to reach the port on time is determined with more certainty while minimizing fuel consumption. In order to verify the validity of the proposed method, a set of simulations were performed, and their results are discussed.
机译:随着有关环境污染和全球变暖的国际商船法规的不断完善,世界范围内为减少船舶燃料消耗所做的努力正在不断增加。这直接与环境污染物和温室气体的排放有关。减少船舶燃料消耗的一种常用方法是找到消耗较少燃料的船舶航线。在许多现有的船舶路线优化研究中,使用单个目标优化算法(例如A *)来计算所需的船舶路线,以使路径长度,行驶时间或燃料消耗最小化。但是,即使在天气不确定的情况下,不迟于在港口分配的时隙到达目的地实际上更重要。在这项研究中,采用多目标优化算法来计算具有两个目标函数的帕累托集:燃料消耗和预期到达时间。随后,使用帕累托集,估算到达时间的不确定性和船舶将在指定时间内到达的概率。最后,在最大程度降低燃油消耗的同时,确定了准时到达港口的路线。为了验证该方法的有效性,进行了一组仿真,并讨论了其结果。

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