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基于性能的导航（Performance Based Navigation,PBN）飞行程序设计方案的优选对提高终端区空域的容量,空中交通管理工作的质量、效率,甚至飞机的飞行安全至关重要.但在实际操作中,PBN飞行程序设计方案的评估通常由有关专家根据机场的特点,依据专业知识及经验来确定优选方案,存在主观性和随意性的缺陷.为了提高PBN飞行程序设计方案优选的合理性和有效性,本文构建了PBN飞行程序设计方案的评价指标体系,建立了基于相对优势度法的区间数多属性评价模型.在该模型中,属性权重及评价指标值均采用区间数形式赋值,这些区间数用于计算备选方案的相对优势度,通过选择最大相对优势度来确定最佳方案.实例证明,所提出的评价模型能充分利用决策信息,有效地解决PBN飞行程序设计方案的优选问题.     

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为寻求一定运输需求和运营条件下,航线上最优的集装箱班轮运输发船间隔及相关决策量,使资金极为密集的航运业运行更优,以一定营运期内航线上班轮运营利润为目标,以船舶载重能力、各类箱型箱位数和港口装卸效率为约束建立班轮运营经济模型.根据班轮航线各港间各类箱型箱量的关系,详细研究运营系统中船舶资本成本、营运成本,以及包括燃料费、装卸费、靠泊费、港口使用费、船员津贴的航次变动成本的解析式,提出调和平均方法的港口综合装卸效率,以及各航段保留一定燃油量、交货时实现利润的条件下盈利航速的解,兼顾实现班轮各航段船天利润和运营总利润两方面最优.结合隐函数求导和函数极值方法求出模型决策变量的最优解,并以实例说明模型的有效性.     

基于SAP BW的北车运营指标决策支持系统

从BW功能结构出发,结合中国北车运营指标数据集成以及模型创建的实践,提出企业决策支持数据模型的优化创建方法,给出合理的创建数据模型的原则.该建模方法与原则已经成功应用于北车集团运营指标分析业务,经过实践证明这些方法与原则具有实施便捷、结构清晰、查询快速的优势.     

不确定箱重下内河集装箱班轮航线配载决策

与集装箱海运相比内河集装箱班轮运输具有其独特性,同时对于内贸箱而言,货主订舱时箱重信息的不确定性导致其航线配载决策变得更加复杂.本文考虑不确定箱重影响,以最小化航线班轮堆栈占用数量为目标,构建内河集装箱班轮航线配载决策的随机规划模型.为实现求解,基于随机规划理论,采用机会约束描述随机约束,将随机规划模型转化为随机机会约束规划模型,并设计混合邻域搜索算法求解.算法由蒙特卡罗随机模拟、神经元网络训练及邻域搜索启发式3个部分组成.算例研究表明,混合邻域搜索算法的鲁棒性较好,可实现配载计划对不确定因素的有效吸收.     

铁路超限货物运输条件辅助决策可视化仿真系统研究

本文分析了目前我国铁路超限货物运输管理现状,并在此基础上提出了应用计算机实现铁路超限货物运输仿真,开发铁路超限货物运输条件辅助决策系统.目的是通过仿真能够更直观的对超限货物运输条件进行决策,最终达到提高超限货物运输效率与安全性的目的.     

基于“作业面”的铁路集装箱中心站集卡路径优化研究

结合现场作业情况分析了影响集卡最优走行路径选择的5个主要因素:集卡作业道路通行情况、装卸线上集卡等待轨道吊排队情况、堆场内集卡等待龙门吊排队情况、堆场内龙门吊作业效率,以及空闲集卡距目的地的距离,提出了影响因素隶属度的计算方法,给出了基于模糊决策理论的集卡最优路径选择求解算法,并以铁路集装箱中心站的实例进行验证分析.该优化方法提高了集装箱中心站集卡的作业效率,为基于“作业面”的集装箱中心站的集卡调度系统提供了理论和技术支持.     

紧迫危险不可避免碰撞操船决策自动生成方法

针对紧迫危险操船决策具有特殊性及一般性的特点,介绍了特征完全匹配的案例推理(CBR)原理及方法设计,重点论述了紧迫危险操船决策案例库的建立、案例库的算法表示形式及基于特征CBR的操船决策自动检索与生成机制.借助船舶智能操控仿真测试平台开展仿真实验,验证了方法的可行性.它是船舶智能避碰决策支持系统的组成部分,对船舶航行安全及航海模拟器培训教学具有理论研究与实际应用价值.     

基于多属性决策的目标群威胁判断方法

在现代作战指挥决策系统当中,如何迅速反映战场态势变化,做出威胁判断,对实现指挥系统的自动化具有重要意义。根据多属性决策与威胁判断的特点,论文提出了基于多属性决策的目标群威胁判断方法,将目标群的属性及相互关系进行量化并对进行威胁判断与等级排序,其属性值由隶属函数进行刻哂。最后通过实例验证目标群威胁判断方法的有效性。     

A multi-criteria decision method for the analysis of the Motorways of the Sea: the application to the case of France and Spain on the Atlantic Coast

Despite European Union (EU) political support to identify the most feasible Motorways of the Sea, the final decision can only be made by Private Shipping Companies, which are operators of a unique stretch of the intermodal chain. This paper provides a multi-criteria decision method to identify the most suitable Motorways of the Sea taking into account the competitiveness of whole intermodal routes versus the alternative of road transport from the loader’s perspective. The analysis is carried out assuming a ‘many-to-many’ transport model. Firstly indexes of time and cost were defined and evaluated for every available route in the model in accordance with a multi-criteria decision matrix. Secondly, through a Monte Carlo simulation a sensitivity analysis was carried out in order to evaluate the influence on the results of the forecast assumed to construct the matrix. The results obtained are not only quantitative, but also qualitative. The development of intermodal routes via Motorways of the Sea is especially relevant for the peripheral EU countries. Due to the relevance of the freight flow between France and Spain and the congestion of their connections through the Pyrenees, the method proposed was applied to the analysis of this particular case     

Choosing Public Transport—Incorporating Richer Behavioural Elements in Modal Choice Models

The development of behaviourally richer representations of the role of well-established and increasingly important influences on modal choice, such as trip time reliability and accounting for risk attitude and process rules, has moved forward at a fast pace in the context of automobile travel. In the public transport setting, such contributions have, with rare exception, not been considered. In this paper, we discuss and empirically illustrate the merits of advanced modelling developments aimed at improving our understanding of public transport choice, namely the inclusion of reliability in extended expected utility theoretic forms, to recognize risk attitude and perceptual conditioning, the consideration of passenger crowding and its inclusion in linear additive models, and the role of multiple heuristics in representing attribute processing as a way of conditioning modal choice. We illustrate the mechanics of introducing these behaviourally appealing extensions using a modal choice data set collected in Sydney.