双向通航港口船舶调度优化模型与算法

为提高双向通航港口船舶调度的安全性和调度效率,研究双向通航港口船舶调度优化模型和算法。考虑船舶属性和船舶交通状况等因素,基于船舶调度安全性、连续性和高效性要求,建立以单向/双向通航模式转换、航道与泊位协调和安全性为约束的双向通航港口船舶调度多目标优化模型;设计双向通航港口船舶调度多目标遗传算法获取最佳调度方案。对试验所求的调度方案进行一般性安全检验、双向通航安全检验和双向通航与单向通航转换安全性检验,结果表明:提出的双向通航港口船舶调度优化模型与算法能在保证安全的前提下有效获取船舶调度方案,提高双向通航港口船舶调度效率。     

基于蚁群算法的港口船舶调度优化问题研究

港口船舶调度优化问题是当前一个公开的难题,传统方法无法获得理想的港口船舶调度优化方案,为了加快港口船舶调度速度,降低港口船舶调度成本,建立了基于蚁群算法的港口船舶调度优化模型。首先分析当前港口船舶调度优化研究现状,指出各种方法出现不足的原因,然后构建港口船舶调度优化问题的多约束优化目标函数,并引入蚁群算法对多约束优化目标函数进行寻优,求得港口船舶调度优化问题的最优解,最后进行港口船舶调度优化仿真模拟实验。相对于其他港口船舶调度优化模型,蚁群算法改善了港口船舶调度优化问题求解的效率,港口船舶调度优化问题的解质量更高,可以满足港口船舶调度管理的实际应用要求。     

基于人机交互-蚁群算法的船舶交通多航道调度优化

传统基于纯蚁群算法的船舶交通多航道调度优化无法根据实际情况调整船舶优先级,船舶占港时间较长,经济效益差,因此设计一种基于人机交互-蚁群算法的船舶交通多航道调度优化方法。建立多航道调度优化模型,明确各船舶调度策略,确定调度时间、等待时间最小的目标函数,建立避免调度过程中产生混乱和协调船舶交叉的约束条件;在调度优化中引入人机交互-蚁群算法,采用人工设置临时改变船舶工作的优先级,以此来提高港口工作效率,并设置算法的搜索顺序,完成船舶交通多航道调度优化的研究。在算例仿真中,为验证传统方法与设计方法的调度结果,设置港口参数并分析两方法的调度方案,结果表明设计的方法得到的方案能有效缩短船舶平均在港口的停留时间和恢复正常生产所需要的时间。     

群智能优化算法的船舶信息管理任务批量流水调度研究

针对传统的船舶信息管理任务调度模型的调度平均等待时间长的问题,研究群智能优化算法的船舶信息管理任务批量流水调度模型。根据群智能优化算法理论,将调度过程中的船舶看作粒子,根据实际调度需求设定调度模型的参数。为缩短船舶调度平均等待时间,规划船舶调度的目标函数以及约束条件。计算粒子适应度,将粒子与任务分配一一映射,根据船舶可信度计算得到局部粒子最优解,更新粒子位置直至出现最优调度解,完成船舶信息管理任务批量流水调度模型的构建。通过与传统调度模型的对比仿真实验,验证构建的基于群智能优化算法的船舶调度模型能够缩短传统调度模型2/3的平均调度等待时间,提高了调度效率。     

遗传算法在港口船舶调度领域中的应用

以港口企业的研究实践为出发点,从港口船舶调度的优化目标和影响港口船舶调度的因素两方面入手,借助多目标优化和遗传算法在各自算法上的优势,针对港口船舶调度的特殊性要求,将两种算法进行动态融合,并结合实际业务数据进行了模型的构建和求解。     

支线集装箱船舶航线规划与配载协同优化

针对支线集装箱船舶运输中喂给港数和靠泊条件不一的实际背景,考虑船舶容量、行驶稳性和交付时间等约束,采用两阶段分层方法研究支线集装箱船舶航线规划和配载协同优化问题。两阶段中分别以所有船舶总运营成本最小和混装堆栈数最小为目标,构建船舶航线规划和配载优化的混合整数规划(MIP)模型,结合问题特征设计粒子群算法(PSO)求解模型。结果表明：模型与算法均可实现问题求解,对于较大规模的算例,模型最长求解时间超过600 s, PSO最长求解时间为16.66 s,平均10.00 s内完成求解,表现出较好的求解性能,可为支线集装箱船舶航线规划与配载协同优化提供决策参考。     

面向多约束的船舶组立构件建造作业调度方法研究

为了提高船舶中小组立等中间产品建造作业调度能力,提升船舶建造效率,提出面向多约束的船舶组立建造作业调度方法。首先,分析船舶组立建造的工艺流程和作业调度方法,综合考虑机器小组、工艺和交货期等多种约束条件,以建造周期最短为调度目标,建立船舶组立建造作业调度数学模型;其次,综合运用算法分解策略及调度规则,设计改进的最短作业优先调度算法实现模型求解;最后,以某船厂建造车间一定生产周期（17天）的中小组立先行中日程计划为对象,验证该方法的有效性和实用性。研究结果表明,所提出的面向多约束的船舶组立建造作业调度方法相较于当前的调度方法,排产周期压缩22小时,即缩短了原有周期的16.18%,有效提高了生产计划排产和作业调度效率。     

船舶平面分段单流水线反应式模糊调度研究

本文针对船舶平面分段流水线调度过程中加工时间和交货期的不确定性,采用模糊化手段进行调度决策。为了应对船舶平面分段生产过程中的急件插入的情况,提出描述船舶平面分段单流水线反应式调度问题的数学模型,以最小化模糊最大完工时间makespan、最大化平均AICD、最大化平均AISS为调度目标,设计了求解模型的一种多目标文化基因算法。基于解的形式采用有效的变异、交叉操作,并嵌入局部搜索算子以增强算法搜索能力。本研究通过makespan和satisfaction两个指标反映算法的有效性,通过甘特图模拟仿真调度过程,为实际船舶平面分段的生产建造提供决策支持。     

基于云计算的船舶数据并行调度算法研究

传统船舶数据并行调度算法,存在数据调度速度较慢、并行识别准确率较低等弊端。为有效解决上述问题,设计基于云计算的船舶数据并行调度算法。通过云计算架构的搭建、SBS数据云体系的搭建,完成船舶云计算环境的搭建。通过船舶数据感知调度、多目标船舶数据的并行调度、算法性能分析,完成基于云计算船舶数据并行调度算法设计。模拟算法工作环境,设计对比实验结果表明,新型算法与传统算法相比,大幅提升数据调度速度、并行识别准确率等属性。     

船舶排闸的遗传算法设计与仿真

为优化船舶排闸,在对船舶排闸问题进行建模的基础上,提出船舶排闸的遗传算法,详细阐述将遗传算法应用于船舶排闸问题的具体实现方法。给出船舶过闸调度的仿真模型,包括交通流模型和调度模型。构建仿真实验系统,仔细比较3种船舶排闸算法,验证遗传优化算法的有效性。该研究对于内河船闸调度具有较强的理论和实用价值。     

Estimation of CO2 reduction for Japanese domestic container transportation based on mathematical models

This research discusses domestic feeder container transportation connected with international trades in Japan. Optimal round trip courses of container ship fleet from the perspective of CO₂ emission reduction are calculated and analyzed to obtain basic knowledge about CO₂ emission reduction in the container feeder transportation system. Specifically, based on the weekly origin–destination (OD) data at a hub port (Kobe) and other related transportation data, the ship routes are designed by employing a mathematical modeling approach. First, a mixed integer programming model is formulated and solved by using an optimization software that employs branch and bound algorithm. The objective function of the model is to minimize the CO₂ emission subject to necessary (and partially simplified) constraints. The model is then tested on various types of ships with different speed and capacity. Moreover, it is also tested on various waiting times at hub port to investigate the effect in CO₂ emission of the designated fleet. Both the assessment method of container feeder transportation and the transportation’s basic insights in view of CO₂ emission are shown through the analysis.     

Analysis of the continuous berth allocation problem in container ports using a genetic algorithm

The optimal usage of berths plays a key role in raising the efficiency of container terminals. The berth allocation problem in a container terminal is defined as the feasible allocation of berths to incoming ships such that the total time that elapses between the arrival of the ships to their exit from their berths is minimized. In the transportation literature, the latter problem is usually formulated as a mixed integer programming model. Optimization methods, like the branch and bound algorithm, are efficient ways to solve this model but become absolutely unusable when the size of the problem increases. An advanced search method such as GA may be suited to such a situation. In this paper, a genetic-based algorithm is proposed for the problem. Computational results for two test problems (a small and a large-sized problem) are also presented. The results from the small test are also compared with the results obtained from the branch and bound algorithm.     

Optimal container ship size: a global cost minimization approach

ABSTRACT

Currently, the best container ship size in a service is determined mainly by the liner operator, considering only the economies of scale of ships. Its external diseconomies to the ports and shippers are usually not considered in the decision-making process, which may reduce the overall efficiency and lead to global nonoptimality. This study incorporates the cost to the shipping companies at the main lines, ports, and feeder services, as well as the external costs to shippers and ports in a hub-and-spoke network, and determines the best ship size and the number of weekly services to minimize the overall costs. The external cost to the shippers in the feeder ports is assumed to be proportional to the feeder cost, and a sensitivity analysis is provided. The maximum container ship size is estimated according to different levels of freight demand. A numerical analysis shows that the optimal size should be smaller than the current biggest container ships in service.     

西江干线集装箱船船型论证

按照改善船舶技术经济性、提高航道和船闸通航效率原则,对西江干线新一代集装箱船型进行论证。采用划分典型航段、典型吨级的方法对西江干线集装箱船型进行优化,得到各航段的最佳船型。结果表明,最佳船型的技术和经济性能与现有优秀船型相比有明显的提高。     

Impact of scale increase of container ships on the generalised chain cost

In recent years, an increase in the size of the container ships could be observed. The question is how these larger ships will influence the total generalised costs from a port of loading to a destination in the European hinterland. The second question is whether a scale increase of the container ships on other loops, such as a loop from the United States to Europe, has the same impact on the generalised chain costs as on the loop from Asia to Europe. A derived question is which element of the total chain has the highest importance, and whether this balance varies as the ship size changes. In this article, a model is developed that allows answering the above research questions. The model is designed to simulate the cost of a complete loop of a container ship and of a chain that uses that same loop. For the chain cost simulation, the maritime part is determined by the loop. From the ports of loading and unloading, the port container handling and the hinterland transportation costs are also integrated. The model also allows calculating the total chain cost from a point of origin (either a hinterland region or a port) to a destination point (also a port or a hinterland region). An actual container loop of a container shipping company can be introduced in the model. An application is made to two existing container loops, namely from Asia respectively the United States to Europe. It turns out that changing ship does indeed lead to economies of scale, but also that the impact is larger on the Asia–Europe connection than on the US–Europe connection. Furthermore, the maritime component has the biggest share in the total chain cost, but as ship size increases, the shares start getting closer to each other. This research contributes to the existing literature in two ways. First of all, it quantifies the impact of the scale increase of container ships throughout the total chain. Second, this is done from a bottom-up engineering modelling approach.     

浙江省内河集装箱运输适用船型研究

分析当前浙江省内河集装箱船型情况,结合浙江省内河航道、跨航桥梁、控制性船闸等基础设施现状及发展规划,提出适合浙江省的内河集装箱发展船型,并分析其节能、高效、经济、适应性等特点。本研究对行业主管部门研究制定相关标准具有参考价值,对全国内河集装箱运输发展具有借鉴意义。     

世界海上集装箱运输业的近况及发展

介绍世界海上集装箱运输业的近况及发展。首先略述近期世界经济的全面恢复，指出这必然拉动世界海上集装箱运输业的发展，接着介绍近几年世界集装箱大港的吞吐量变化和集装箱运输船队的构成，重点是今后几年超大型集装箱船的建造情况。最后选择性介绍几个大港扩建深水码头的规划。     

LNG罐式集装箱水运安全性探讨

LNG公路运输成本高,交通事故频发,为此有关专家提出LNG罐式集装箱水路运输的模式。该模式将会使运输成本显著降低,但如何保障运输安全就成为关键问题。该文就LNG罐式集装箱水路运输涉及的各个环节——LNG罐式集装箱、码头装卸和水路运输的安全性要求进行探讨,分析LNG罐式集装箱的积载和隔离方式,并提出一些建议,为中国开展LNG罐式集装箱水路运输业务提供参考。     

基于多目标混沌云粒子群算法的泊位-岸桥分配研究

为了提高集装箱港口泊位-岸桥分配效果和优化效率,以集卡运距和船舶在港时间最小为优化目标,建立了多目标离散泊位-岸桥分配模型,利用混沌云粒子群算法对泊位-岸桥分配模型进行求解,开发了粒子可行-整数化处理模块,内嵌于混沌云粒子群算法进化中,制定了粒子编码规则,设计了多目标函数的粒子历史极值和全局极值的计算方法,提出了基于混沌云粒子群优化算法求解多目标离散泊位-岸桥分配模型的新方法,数值算例结果证明了该模型和算法的可行性和实用性。     

单体小水线面水翼复合型高速船应用前景探讨

该文简要介绍了单体小水线面水翼复合型高速船（HYSWAS）国内外研究概况,HYSWAS与其它高性能船比较具有航速高、耐波性好、可大型化的优点。通过海峡客运船队的论证和东亚超高速货运航线经济性分析,提出了HYSWAS用作高速客渡船和小型、高速集装箱船,具有良好的应用前景。