基于多目标优化算法NSGA Ⅱ的极地穿梭油轮型线设计

Polar vessel hullform design based on the multi-objective optimization NSGA Ⅱ

[目的]随着北极丰富油气资源的不断开采,需要大量满足极地航行要求的船舶。[方法]将非支配排序遗传算法(NSGA Ⅱ)应用于船体型线优化设计,提出极地船舶多目标优化方法。以船舶无冰静水阻力以及冰区航行阻力为优化目标,通过极地船舶排水量以及船舶能效设计指数EEDI两项标准进行船型筛选,快速实现满足冰区船舶装载量与EEDI排放要求的船型优化。以常规6.5万吨穿梭油轮为研究对象,采用全参数化建模方式,通过极地船舶多目标优化方法分别对3种不同艏部形式的船型进行优化,[结果]优化后的船型均满足冰区IA级航行要求,其中无冰静水阻力最大减小约12.94%,冰区最小推进功率最大减小约27.36%,[结论]有效验证了基于NSGA Ⅱ的极地船舶多目标优化方法的可行性与合理性。

[Objectives] With the increasing exploitation of the Arctic abundant oil and gas resources,a large number of ships which meet the polar navigational requirements are needed. [Methods] In this paper, the fast elitist Non-Dominated Sorting Genetic Algorithm （NSGA II） is applied to the hull optimization, and the multi-objective optimization method of polar vessel design is proposed. With the optimization goal of resistance and icebreaking resistance, filtering hull forms through the standard of polar vessel displacement and EEDI, fast ship hull optimization that satisfy the ice-ship dead weight and EEDI requirements has been achieved. Taking a 65 000 t shuttle tanker as an example, full parametric modeling method is adopted, the hull optimization of three different bow forms is conducted through the polar vessel multi-objective optimization method. [Results] The ship hull after optimization can satisfy the IA class navigation require, where the resistance in calm water decreases up to 12.94% , and the minimum propulsion power in ice field has a 27.36% reduction. [Conclusions] The feasibility and validity of the NSGA II applying in polar vessel design is verified.