基于数据仓库和信息挖掘的柴油机维修决策支持系统

针对舰船柴油机维修决策中待处理数据量的急剧增加，研究以数据仓库和信息挖掘技术为核心的智能维修决策支持系统。对数据仓库的设计与实现进行了介绍，把信息挖掘作为一种特殊的模型应用于决策支持系统中的知识发现，说明了柴油机维修决策支持系统的实施原则和步骤。     

信息技术在柴油机维修决策支持系统中的应用

针对舰船柴油机维修决策中待处理数据量的急剧增加,研究以数据仓库和信息挖掘技术为核心的智能维修决策支持系统。对数据仓库的设计与实现进行了介绍,把信息挖掘作为一种特殊的模型应用于决策支持系统中的知识发现,说明了柴油机维修决策支持系统的实施原则和步骤。     

ETL技术在船舶制造海量异构数据处理中的应用

以船舶制造海量异构数据为对象，研究ETL技术及其执行工具，建立船舶制造海量异构数据处理架构，构建统一的数据仓库系统，符合船舶数据结构特性，能够可靠、有效、快速地实现船舶制造各种数据间的抽取、清洗、转换及装载，解决船舶数据源无法相互关联及汇总的问题，实现数据整合、展示、分析的快速响应，提高智能管控执行效率。     

船舶运输决策系统中数据仓库的应用与研究

船舶运输决策系统是为航运企业和港口等提供决策支持的重要信息系统。该系统通常采用索引机制,提升数据库的数据读取速率,从而提高整个决策系统的决策效率。本文提出一种基于遗传算法的数据库属性访问概率决策支持系统,使用遗传算法完成有效的最优数据库索引创建。本文提出的系统将Microsoft SQL Server 2000作为后端数据库,并采用C#进行实现。实验结果表明,本方法具有显著的性能改进,能够基于用户的访问需求,生成的最佳数据库索引集。     

基于知识融合的船舶能耗决策支持系统

在建立船舶能耗评价模型基础上,针对能耗影响因素众多,提出了基于知识融合的船舶能耗决策支持系统的研究。以船舶能耗为对象,应用系统辨识理论,建立重点设备能耗模型库;以方法、经验和案例为基础,建立船舶能耗知识库;融合模型库、知识库、关系数据库等多源知识,建立船舶能耗评价与决策支持系统。以实现船舶航运管理、船舶操纵控制、航线设计以及船舶设计等各个过程的决策支持。     

基于大数据分析的船舶运输可持续性研究

本研究旨在探讨基于大数据分析的船舶运输可持续性。通过对船舶运输相关的大数据进行收集和分析,以经济、社会和环境三个方面为切入点,综合考虑船舶运输的可持续性问题,包括航线规划、船舶设计、燃油消耗、航运市场需求和货物运输量等多个方面。分析了船舶运输的可持续性问题,并提出了相应的解决方案,以实现船舶运输的可持续发展。     

船舶运输现代化管理的研究

根据船舶运输管理的特点，论述了用决策支持系统和专家系统相融合的方法研究船舶运输现代化管理问题的必要性和可行性，并针对优化航线配船问题，提出了具体解决问题的设想，不但保留发线性规划解决航线配船的优点，而且更加符合航运计划和调度的实际情况，为进一步解决现代化管理指明了方向。     

船舶运输环境观测与数据传输系统的构建

要实现海运航线的智能决策,需要对船舶运输环境要素进行监测,采集数据并实时传输。船舶运输环境观测与数据传输系统的构建,包括系统研发,观测系统实船安装、调试、试运行,观测数据落地(接收)、存储(数据库管理)、分发(反馈)。     

基于机器学习的船舶能耗智能预测方法验证分析

船舶能耗智能预测是实现船舶能效智能评估与优化决策的基础和前提。大数据、人工智能、机器学习等新兴技术促进了船舶能耗预测方法的不断发展，为分析不同基于机器学习的船舶能耗预测算法的预测精度与效果，进行了不同预测算法的实例验证分析。结合船舶油耗及其影响因素实船采集数据，通过采用不同机器学习算法对船舶能耗进行预测分析，验证了各算法的特点和优势，从而为选择合适的船舶能耗预测算法提供参考。     

基于数据仓库的航运企业港口使费成本管控决策系统应用

为进一步降低航运企业的成本费用,提出一种基于数据仓库的加强港口使费成本管控的方法,以港口使费中的引航费为例,通过Kettle工具搭建数据仓库,设计以船长驾驶船舶抵离港口的引航情况为主题的数据集市,开发计算机辅助分析模块。实践结果表明,该方法能提供翔实、可靠的数据支撑,帮助业务管理人员快速、准确地决策,从而进一步压缩航运企业经营成本。     

A continuous berth template design model with multiple wharfs

ABSTRACT

Berth planning plays an important role in improving the efficiency of a container terminal. This study focuses on the berth template problem (BTP), which determines the berthing windows of the calling ships within a planning horizon (e.g. a week) in a cyclical way. As a mid-term tactical decision problem, BTP provides the decision support for a terminal operator to negotiate the contracts with the shipping lines. This study develops an integer programming (IP) model aiming to minimize the total deviation, given the ship-dependent target times preferred by the shipping lines. To validate the model and illustrate the benefits of its use, we perform a numerical experiment based on operational data of a specific container terminal in Southeast Asia. Two IP-based heuristic methods are developed to take into account the decision framework of terminal operators in reaction to demand increases. The experiment results indicate that the model and the solution approaches can enhance the resource utilization and operational efficiency of container terminals.     

Implementing the street-turn strategy by an optimization model

The street-turn option represents a major strategy for the profitability of shipping companies supplying container-based transportation. This option consists in the distribution of trucks delivering loaded containers to import customers, the subsequent allocation of empty containers to export customers and the final dispatch of loaded containers to departure ports. However, the determination of truck routes is a time-consuming activity for shipping companies, because available information can suddenly change while they are making their decisions. In this paper we aim to propose a decision support tool to quickly determine truck routes and implement the street-turn strategy. This tool is based on an optimization model determining the allocation of empty containers between customers and defining truck routes in a post-optimization phase. We compare routes resulting from the proposed model to the decisions of a real shipping company. Early results indicate that this approach represents a promising support for shipping companies in dealing with street-turns. It can significantly reduce distances travelled by trucks and times requested to determine routes.     

A reactive container rerouting model for container flow recovery in a hub-and-spoke liner shipping network

This paper focuses on the container rerouting due to a disruption, aims at making the optimal container flow recovery plan for the affected liner shipping company. First, we make the initial effort to bring up with a basic framework of disruption management for liner shipping. Second, we present a compact integer linear programming model for addressing the container rerouting problem under the proposed framework in a hub-and-spoke liner shipping network, based on a given recovery vessel schedule that determines to omit a port of call. Other shipping companies’ services and other modes (roadway, railway, and airline) as candidate alternative means to transport the miss-connected containers are also incorporated in the proposed model. The container flow recovery plan would select the optimal alternative paths for the miss-connected containers balancing the trade-off between container transport costs and delivery delay penalty costs. Finally, a case study from a global liner shipping company is investigated and the computational results indicate the model can be solved effectively and efficiently for the real-scale problem. Thus, the proposed approach in this paper can supply real-time decision support tool for the liner shipping operators on handling the process of container flow recovery.     

Fleet deployment in liner shipping: a case study

The fleet deployment problem is an important planning problem in liner shipping. It deals with optimally assigning voyages to available vessels in the fleet and determining vessel routes and schedules in a way that minimizes costs or maximizes profit. This paper presents a new model for a fleet deployment problem in liner shipping, and we also propose a multi-start local search heuristic to solve the problem. The heuristic has been embedded in a prototype decision support system (DSS) that has been implemented and tested at Höegh Autoliners, a major global provider of ro-ro (roll-on roll-off) vehicle transportation services. The heuristic was able to produce high-quality solutions within a few minutes to a real planning problem with more than 55 vessels and 150 voyages over a planning horizon of 4–6 months. Tests indicated that the solutions suggested by the DSS gave between 2 and 10% improvements compared with solutions from manual planning. What is almost equally important is that using the DSS can ease the planning process.     

远洋船舶在线监控系统的研究

由于船舶与公司岸基在地域上的分离,目前公司岸基尚不能对远洋船舶的安全营运进行实时、有效的监控。应用先进的计算机信息技术、通信技术和网络技术等,将船-岸安全监控管理有机地结合在一起,船-岸随时交互数据,协作管理业务,确保远洋船舶运输的安全高效。形成一个开放的集船舶监控、管理、决策于一体的远洋船舶在线监控系统,从而实现和提高远洋船舶的安全管理水平。以中远集团所辖船舶为实施对象开发成功了远洋船舶在线监控系统。     

内河船舶避碰决策智能优化研究

针对内河船舶航行及内河航道的诸多特点,分析影响内河船舶碰撞危险的各种因素,建立内河船舶碰撞危险度的评判模型;重点对内河船舶避碰决策及优化展开研究,系统化描述保证船舶安全、经济航行的多种条件,提出相应的避碰决策模型,并在此基础上拟应用优化理论展开探讨。     

基于OLAP的数据仓库模型的探讨

随着跨领域产业的出现和各领域知识的互相渗透,企业决策所需要的数据量越来越庞大。一个企业的数据仓库包含了该企业运作的所有历史数据,有效地构建和使用数据仓库为企业人做出决策提供更优越的平台。本文提出基于OLAP的数据仓库的设计方案,并对雪花模式和星型模式的优缺点进行详细论述。     

采用自动识别系统对水下输气管线、离岸平台和船舶检验评分的实时监测（英文）

The aim of this research is to develop an algorithm and application that can perform real-time monitoring of the safety operation of offshore platforms and subsea gas pipelines as well as determine the need for ship inspection using data obtained from automatic identification system(AIS). The research also focuses on the integration of shipping database,AIS data, and others to develop a prototype for designing a real-time monitoring system of offshore platforms and pipelines. A simple concept is used in the development of this prototype, which is achieved by using an overlaying map that outlines the coordinates of the offshore platform and subsea gas pipeline with the ship's coordinates(longitude/latitude) as detected by AIS. Using such information, we can then build an early warning system(EWS) relayed through short message service(SMS), email, or other means when the ship enters the restricted and exclusion zone of platforms and pipelines. The ship inspection system is developed by combining several attributes. Then, decision analysis software is employed to prioritize the vessel's four attributes, including ship age, ship type, classification, and flag state.Results show that the EWS can increase the safety level of offshore platforms and pipelines, as well as the efficient use of patrol boats in monitoring the safety of the facilities. Meanwhile, ship inspection enables the port to prioritize the ship to be inspected in accordance with the priority ranking inspection score.     

大型航运集团辅助决策支持系统的设计与实现

围绕某大型航运集团战略决策,参考国际先进企业的实践经验,按照信息共享的原则,全面整合经营、生产、财务、人力资源、安全以及发展环境等方面关键数据.建立统计分析和计量经济模型,进行深度挖掘和分析预测,设计重大和分层决策的辅助决策分析主题.建立一个全面、及时、上下一致、透明的管理视图,为集团及各成员单位决策提供辅助决策支持,也为各部门经营操作提供一个统计分析工具.