利用欧洲中期天气预报中心(European Centre for MediumRange Weather Forecasts,ECMWF)提供的ERA5再分析资料和中国气象局热带气旋资料中心提供的CMA热带气旋最佳路径数据集资料,对浙江海域的风、浪和热带气旋等水文气象环境的特征进...利用欧洲中期天气预报中心(European Centre for MediumRange Weather Forecasts,ECMWF)提供的ERA5再分析资料和中国气象局热带气旋资料中心提供的CMA热带气旋最佳路径数据集资料,对浙江海域的风、浪和热带气旋等水文气象环境的特征进行了分析,为保障船舶在浙江海域航行安全提供了参考。展开更多
Considering the effects of increased economic globalization and global warming,developing methods for reducing shipping costs and greenhouse gas emissions in ocean transportation has become crucial.Owing to its key ro...Considering the effects of increased economic globalization and global warming,developing methods for reducing shipping costs and greenhouse gas emissions in ocean transportation has become crucial.Owing to its key role in modern navigation technology,ship weather routing is the research focus of several scholars in this field.This study presents a hybrid genetic algorithm for the design of an optimal ship route for safe transoceanic navigation under complicated sea conditions.On the basis of the basic genetic algorithm,simulated annealing algorithm is introduced to enhance its local search ability and avoid premature convergence,with the ship’s voyage time and fuel consumption as optimization goals.Then,a mathematical model of ship weather routing is developed based on the grid system.A measure of fitness calibration is proposed,which can change the selection pressure of the algorithm as the population evolves.In addition,a hybrid crossover operator is proposed to enhance the ability to find the optimal solution and accelerate the convergence speed of the algorithm.Finally,a multi-population technique is applied to improve the robustness of the algorithm using different evolutionary strategies.展开更多
文摘利用欧洲中期天气预报中心(European Centre for MediumRange Weather Forecasts,ECMWF)提供的ERA5再分析资料和中国气象局热带气旋资料中心提供的CMA热带气旋最佳路径数据集资料,对浙江海域的风、浪和热带气旋等水文气象环境的特征进行了分析,为保障船舶在浙江海域航行安全提供了参考。
基金funded by the Russian Foundation for Basic Research(RFBR)(No.20-07-00531).
文摘Considering the effects of increased economic globalization and global warming,developing methods for reducing shipping costs and greenhouse gas emissions in ocean transportation has become crucial.Owing to its key role in modern navigation technology,ship weather routing is the research focus of several scholars in this field.This study presents a hybrid genetic algorithm for the design of an optimal ship route for safe transoceanic navigation under complicated sea conditions.On the basis of the basic genetic algorithm,simulated annealing algorithm is introduced to enhance its local search ability and avoid premature convergence,with the ship’s voyage time and fuel consumption as optimization goals.Then,a mathematical model of ship weather routing is developed based on the grid system.A measure of fitness calibration is proposed,which can change the selection pressure of the algorithm as the population evolves.In addition,a hybrid crossover operator is proposed to enhance the ability to find the optimal solution and accelerate the convergence speed of the algorithm.Finally,a multi-population technique is applied to improve the robustness of the algorithm using different evolutionary strategies.
