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A SUSTAINABLE MODEL FOR OPTIMAL DYNAMIC ALLOCATION OF PATROL TUGS TO OIL TANKERS

机译:一种可持续的模型,可持续地动态分配巡逻拖船对油轮

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Oil tanker traffic constitutes a vital part of the maritime operations in the High North and is associated with considerable risk to the environment. As a consequence, the Norwegian Coastal Administration (NCA) administers a number of vessel traffic services (VTS) centers along the Norwegian coast, one of which is located in the town of Vardo, in the extreme northeast part of Norway. The task of the operators at the VTS center in Vardo is to command a fleet of tug vessels patrolling the northern Norwegian coastline such that the risk of oil tanker drifting accidents is reduced. Currently, these operators do not use computer algorithms or mathematical models to solve this dynamic resource allocation problem but rely on their own knowledge and experience when faced with constantly changing weather and traffic conditions. We therefore propose a novel sustainable model called the receding horizon mixed integer programming (RHMIP) model for optimal dynamic allocation of patrol vessels to oil tankers. The model combines features from model predictive control and linear programming. Simulations run with real-world parameters highlight the performance and quality of our method. The developed RHMIP model can be implemented as an operational decision support tool to the NCA.
机译:油轮运输构成了高北低的海运业务的重要组成部分,并与相当大的风险环境有关。因此,挪威海岸管理局(NCA)负责在挪威的最东北部的一些船舶交通服务(VTS)沿挪威海岸中心,其中一个位于Vardo的镇。在Vardo的VTS中心运营商的任务是指挥拖轮船舶的巡逻挪威北部海岸线,使得油轮漂流事故的风险被降低一个舰队。目前,这些运营商不要使用计算机算法或数学模型来解决这一动态资源分配问题,但面对不断变化的天气和交通状况依靠自己的知识和经验。因此,我们建议呼吁巡逻舰的最优动态分配油轮滚动时域混合整数规划(RHMIP)模型的新型可持续的模式。该模型结合了模型预测控制和线性规划的特点。与现实世界的参数运行模拟突出我们的方法的性能和质量。发达RHMIP模型可以实现为运营决策支持工具的NCA。

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