一、报告时间
2023年5月6日（周六）9:30-11:00
二、报告地点
敏学楼406（原专业学位楼）
三、主讲人
Wengang Mao, Professor at Division of Marine Technology, Chalmers University of Technology, conducts research within the field of ship mechanics, such as dynamic ship structural analysis, statistical wave modelling, machine learning modelling of ship maneuverability and speed-power performance at sea, and their applications for voyage optimization and autonomous shipping. The research goal is to develop innovative measures to increase shipping energy efficiency and ensure ship safety. These projects are mainly funded by several EU Horizon 2020, EU Marie Curie, and Swedish national grants (https://research.chalmers.se/en/person/?cid=wengang).
四、内容简介
Voyage optimization systems, used to plan optimal ship sailing course and schedule, require some necessary information regarding a ship’s navigation strategy, ocean weather forecast and ship performance characteristics as inputs to a mathematical optimization algorithm. Conventional optimisation algorithms often assume either given fixed speed or fixed engine power operation, etc., to simplify the planning process into a two-dimensional optimization problem. It may result in that the estimated optimum voyage is only a locally optimal solution since a ship’s sailing is actually a three-dimensional scenario. In addition, a theoretical/semi-empirical ship’s performance models and weather forecast often contain too big uncertainties, limiting their applications for actual ship operations. In this presentation, we will present the developed a Three-Dimensional Dijkstra’s optimization algorithm, combined with improved ship performance models using machine learning methods and weather forecast (improved by spatio-temporal sea models), used for a ship’s voyage planning. The proposed Three-Dimensional Dijkstra’s algorithm can generate globally optimum ship routing encountering less harsh sea environment, leading to at least 5-10% reduction of fuel consumption. Furthermore, it can perform multi-objective voyage optimization to propose better speed profiling during the voyage, accurate ETA, as well as account for ship safety related factors in the planning process.
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人工智能学院
2023年4月26日
