气象条件和排放控制区规定的船速多目标优化

Multi-Objective Optimization of Ship Speed Under Given Sea Condition and Emission Control Area Regulations

摘要: 针对(Encission Control Area, ECA)法规背景下燃油价格升高的问题,以船舶营运成本和航行时间为目标,综合考虑ECA内外使用燃油的价格差以及气象条件的影响,提出一种船舶航速多目标优化模型。采用非支配排序遗传算法(Non-Dominated Sorting Genetic Algorithm-II, NSGA-II)寻找Pareto最优解集,利用TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution)算法从Pareto最优解集中筛选出最佳折中解。选定天津—宁波航线进行案例分析,结果表明:综合考虑ECA法规和气象条件能够有效减少船舶航行时间和航行总成本,并能帮助船公司更好地应对燃油价格上涨。此外,制定改变船速的最佳时间间隔,同样可有效减少航行成本。

Abstract: This optimization is aimed at reducing costs and sailing time for shipping companies in the context of rising of fuel prices and development in ECA（Emission Control Area） NAFA-Ⅱ.（Non-Dominated Sorting Genetic Algorithm-II） is used to find the Pareto optimal solutions set, from which the best compromise is chosen. The Tianjin-Ningbo line is analyzed as an example, which demonstrates the effectiveness of the optimization in reducing sailing time and total cost. It is also shown that adjusting the speed management plan is an effective measure to reduce the costs.