20000DWT近海散货船概念设计多学科优化

以20 000 DWT近海散货船为研究对象,分别建立以船舶造价、航速、回转性指数、应舵指数为目标的多个船舶概念设计优化数学模型。应用iSIGHT软件对这些数学模型进行集成,采用非支配解排序的多目标遗传算法(NSGA-Ⅱ)求解船舶概念设计多目标问题以获得Pareto解集。优化结果证明了NSGA-Ⅱ算法解决近海散货船优化设计问题的有效性,为解决更复杂工程系统的设计优化问题奠定了基础。     

船舶初步设计的多目标优化研究(英文)

提出了应用于船舶初步设计的多目标优化策略和决策方法.详细介绍了集成模型分析和优化算法的多目标优化求解思路,并使用改进的非支配排序遗传算法获取优化问题的Pareto解集.针对多目标优化问题中各子目标之间存在相互冲突、不能同时达到最优的特性,采用多属性决策理论对设计空间进行计算分析,找出.Pareto前沿面上的最优解.以散货船的初步设计为实例,对多目标优化策略和决策方法进行了验证分析.结果表明优化策略和决策方法不仅是可靠的、实用的,而且能广泛应用于各类船舶初步设计的优化与决策分析中.该文为船舶的初步设计提供了一条新途径.     

基于组合赋权TOPSIS法和粒子群的船舶概念优化设计

船舶概念设计阶段,需要初步给定多组船型参数方案并从中优选出客观合理的某一方案。本文建立以船舶造价、螺旋桨总效率、相对回转直径为目标的船舶概念设计优化数学模型。将Li提出的最小-最大适应度多目标粒子群优化算法应用于求解船舶概念设计多目标问题以获得Pareto解集。分析主观赋权和客观赋权的优劣,提出借鉴专家经验和信息熵权的主客观组合赋权TOPSIS法,借助Matlab软件对所求Pareto解集进行方案排序。算例表明,maximinPSO在求解35 000 DWT散货船概念设计多目标优化能获得均匀分布的Pareto前沿,基于组合赋权的TOPSIS策略能给出客观、合理的决策序列。该方法可应用于船舶优化等领域。     

6万吨级新型半敞口散货船的开发设计

为满足船东的特殊使用要求,在传统系列HANDYMAX型散货船设计的基础上开发了6万吨级新型半敞口散货船。通过型线优化、节能装置安装和机桨配合优化,该船实现了市场最优的油耗率指标。货舱被设计成大舱口、BOX形式,并配备一系列性能优异的装卸设备,方便了多样化装载和多港装载。此外,设计该船时在环保和安全方面也做到了精益求精。最终,该船顺利交付,赢得了船东的好评,并获得了船东的追加订单。     

空运装载问题求解方法研究

针对空运装载问题,重点研究多目标多载具装载问题的数学模型,并提出基于重量差优先的禁忌邻域搜索优化算法来求解模型。实验结果表明该算法不仅保证目标函数值不恶化,还使得解空间搜索时间大大减少,极大地提高了模型求解速度。     

集装箱船配载问题的粒子群算法研究

针对集装箱船配载优化中的Bay位优选问题,提出以倒箱量、重心横向偏移和初稳性高为目标,以箱位与Bay位的一致和Bay位重量为约束条件的数学模型,提出一种多目标离散粒子群算法(MODPSO)求解之,得到该算法优化后的Pareto解集和Pareto解迭代过程中的变化趋势图,为集装箱船配载问题提供多种方案以供备选,从而达到在提高集装箱船装载效率、节约装载成本和时间、使集装箱船获得稳定航行状态等目标间取得更好平衡的目的。     

集装箱船配载的粒子群算法

针对集装箱船配载优化中的Bay位优选问题,提出以倒箱量、重心横向偏移和初稳性高为目标,以箱位与Bay位的一致和Bay位重量为约束条件的数学模型,提出一种多目标离散粒子群算法(MODPSO)求解之,得到该算法优化后的Pareto解集和Pareto解迭代过程中的变化趋势图,为集装箱船配载问题提供多种方案以供备选,从而达到在提高集装箱船装载效率、节约装载成本和时间、使集装箱船获得稳定航行状态等目标间取得更好平衡的目的。     

基于自适应加权的多学科多目标设计优化

针对多学科多目标设计优化存在的耦合严重、计算效率低、难以获得体现设计者使用要求的最优解等问题,提出了基于自适应加权的多学科多目标设计优化方法,阐述了该方法的基本思想并给出了设计优化流程.该方法密切结合实际工程设计经验,将多目标优化问题转换为反映设计者使用要求的综合目标优化问题,采用自适应加权的优化策略建立优化模型进行优...     

船体结构静动态协同优化设计(英文)

论文集成静态、模态和动力响应分析,建立了船体结构静、动态协同优化模型.在系统级优化模型中,以单学科最优解和多学科最优解之间的差异最小化为目标.该目标函数不仅消除了多个目标之间的量纲和数量级差异的影响,而且扩展了协同优化算法的应用范围,由原来的单目标优化扩展到了多目标优化.并与子系统级优化模型构成二级协同优化算法架构.采用多岛遗传算法进行优化求解.对集装箱船艉主甲板进行了静、动态优化设计,分析表明本文所采用的优化算法能应用于工程实际.     

B-60型干舷散货船甲板货装载设计

随着航运市场的持续低迷,BDI指数持续走低,全球散货船市场深受运力过剩和货运需求不足影响,越来越多的船东希望在散货船增加甲板货装载,以拓展散货船的利润空间,提高船舶经济效益。在散货船甲板装货,必将对船舶甲板载荷、稳性性能、视线等产生影响,需要在原有船舶设计的基础上,增加对甲板载荷、稳性计算等方面的考核。以某B-60型干舷散货船为例,详细阐述散货船装载甲板货的设计分析。     

基于改进遗传算法的集装箱装载优化问题研究

在考虑一些实际应用中的约束条件下,提出一种船用集装箱装载优化问题的改进遗传算法。实例仿真结果说明该算法的有效性和实用性,可以直接在实际中应用。     

改进遗传算法在船舶自由浮态计算中的应用

为了更快、更准确地计算船舶自由浮态问题,对原有计算方法进行改进。根据船舶自由漂浮的平衡条件,将自由浮态计算归结为多目标约束优化问题,并引入一种改进遗传算法对该优化问题进行求解。实例计算表明,使用该方法,迭代次数明显少于基本遗传算法,船舶自由浮态计算时间大幅下降,计算结果准确可靠。研究结果对于迅速掌握船舶状态,可靠保障船舶生命力具有重要意义。     

一种基于APDL语言的船舶波浪压力自动加载方法

针对全船结构强度直接计算中,波浪加载较为麻烦的问题,提出了一种ANSYS环境下的波浪压力自动加载的方法。该方法将三维水动力程序计算的船体表面的波浪压力经过插值算法转换到有限元结构单元上,压力数据文件读入ANSYS实现了自动加载。最后,利用该自动加载方法对一艘穿浪双体船进行加载。结果表明,该方法将波浪载荷计算和结构强度分...     

基于多种群萤火虫算法的集装箱船结构优化

针对集装箱船结构优化问题，依据CCS规范建立以集装箱船舯剖面面积最小为优化目标，板厚、型材横截面积为离散设计变量的优化数学模型。提出一种多种群萤火虫算法，各种群设置不同的参数，提高搜索区域，多子群并行寻优、子群主群协作寻优提高算法寻优性能，对所建模型进行优化计算。优化算例表明，所提出的多种群萤火虫算法比标准萤火虫算法可以更快的收敛得到最优解，在满足所有约束条件情况下，集装箱船舯剖面面积最小约13.2%，验证了多种群萤火虫算法应用于集装箱船结构优化的有效性。     

变尺寸装箱问题的迭代/贪婪动态规划算法

针对船舶建造中管材切割规划这一类特殊的变尺寸装箱问题,提出了一种迭代贪婪/动态规划算法(IGDP)并对其进行求解。首先,提出了求解子集和问题的贪婪操作与动态规划的组合解法。然后,基于贪婪操作与动态规划的组合解法实现对整个问题的构造启发式求解,并且通过迭代的拆箱/再分配操作提高了算法的局部搜索能力。最后,通过8个算例的仿真实验,对所提算法与现有算法进行了性能比较。结果表明:IGDP的性能优于现有算法,且具有可以接受的计算耗费。     

Evaluating the trade-off between the level of customer service and transportation costs in a ship scheduling problem

In many ship scheduling problems, time windows are imposed at the loading and/ or discharging of the cargoes to be lifted. Up until now, all proposed solution methods to ship scheduling problems have treated the time window constraints as hard constraints. By transforming the time window constraints into soft constraints, some of the loading/discharging operations may be performed outside the time windows, penalized by an inconvenience cost for not meeting the time window. The motivation behind introducing soft time windows is that, by allowing controlled time window violations for some customers, it may be possible to obtain better routes and significant reductions in the transportation costs. The purpose of this paper is to evaluate the trade-off between transportation costs and the time window violations. Computational results based on data from a real ship scheduling problem are presented and used as a basis for the evaluation.     

Evaluating the trade-off between the level of customer service and transportation costs in a ship scheduling problem

In many ship scheduling problems, time windows are imposed at the loading and/ or discharging of the cargoes to be lifted. Up until now, all proposed solution methods to ship scheduling problems have treated the time window constraints as hard constraints. By transforming the time window constraints into soft constraints, some of the loading/discharging operations may be performed outside the time windows, penalized by an inconvenience cost for not meeting the time window. The motivation behind introducing soft time windows is that, by allowing controlled time window violations for some customers, it may be possible to obtain better routes and significant reductions in the transportation costs. The purpose of this paper is to evaluate the trade-off between transportation costs and the time window violations. Computational results based on data from a real ship scheduling problem are presented and used as a basis for the evaluation.     

船舶航行性能综合优化研究

船舶航行性能优化是一个非常复杂的问题,它具有多个设计变量,多个约束和多个极点.传统的优化方法通常无法解决该问题.文中采用了一种传统的优化方法一复合形法(CA)和遗传算法(GA),模拟退火算法(SA)来计算船舶航行性能优化问题,比较了三种优化方法的输出结果并选取最好的那个解作为最终的优化结果.通过这种方法.可以以更高的概率获得真实的最优解.应该指出的是,这三种算法都作了某种程度上的改进.作者采用C++语言基于面向对象思想开发了计算软件-ShipPO.文中列出的所有船舶航行性能优化计算结果都是在ShipPO平台上计算出来的,结果表明采用三种优化方法计算一次船舶航行性能优化问题耗时并不太多.最终的结果表明ShipPO具有很强的寻找全局最优解的能力,它能够很好地满足工程需要.     

Multi-period liner ship fleet planning with dependent uncertain container shipment demand

This paper deals with a realistic multi-period liner ship fleet planning problem by incorporating stochastic dependency of the random and period-dependent container shipment demand. This problem is formulated as a multi-period stochastic programming model with a sequence of interrelated two-stage stochastic programming (2SSP) problems characterized ship fleet planning in each single period. A solution method integrating dual decomposition and Lagrangian relaxation method is designed for solving the developed model. Numerical experiments are carried out to assess applicability and performance of the proposed model and solution algorithm. The results further demonstrate importance of stochastic dependence of the uncertain container shipment demand.     

Multi-objective topology and size optimization of high-speed vehicle-passenger catamaran structure by genetic algorithm

Ship structural design has become recently an ever more important and difficult task, because it should always take into account several estimation criteria which are a crucial element of shipyard management, as the hull structural strength is one of the most important factors of overall ship safety, and the total cost of structural materials used for the construction of a ship is a significant part of her total construction cost. Simultaneously, a complete definition of the optimal structural design requires a formulation of size-topology-shape-material optimization task unifying the optimization problems from these four areas and giving an effective solution of this problem. So far, a significant progress towards a solution of this problem has not been achieved. An objective of the underlying paper was to develop an evolutionary algorithm for multi-objective optimization of both topology and scantlings of structural elements of large spatial sections of ships. In the paper an evolutionary algorithm where selection takes place based on the scalar objective function is proposed and applied to solve the problem of structural elements weight and cleaned and painted surface area on a high-speed vehicle-passenger catamaran structure with several design variables, such as plate thickness, scantlings of longitudinal stiffeners and transverse frames, and spacing between longitudinal and transversal members. The results of numerical experiments with the use of the developed algorithm are presented. They show that the proposed genetic algorithm can be an efficient multi-objective optimization tool for simultaneous design of the topology and sizing of ship structures.