沿海大型枢纽港陆路集疏运多通道空间尺度随机动态规划研究

项目名称： 沿海大型枢纽港陆路集疏运多通道空间尺度随机动态规划研究

项目编号： No.51309049

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 水利工程

项目作者： 王文渊

作者单位： 大连理工大学

项目金额： 25万元

中文摘要： 吞吐量的持续增长和船舶大型化的发展趋势，使沿海港口集疏运体系供需矛盾日益突出，集疏运通道拥堵现象日趋严重。规划与设计港口集疏运通道时若按照公路或铁路相关理论，则忽略了船舶到港及装卸特性对港口集疏运通道交通的影响,进而无法准确反映港口集疏运体系的供需关系。本研究以大型枢纽港陆路集疏运体系多通道空间尺度为研究对象，探究港口集疏运体系的复杂系统本质，挖掘船舶到港等随机因素驱动下的港口陆路集疏运交通特征；从船舶到港与港口生产随机性的视角，建立基于通道服务水平的港口集疏运通道通过能力计算理论；提出基于冗余优化的港口陆路集疏运通道空间尺度确定方法；引入复杂自适应系统理论辨析港口规模及功能的发展过程中集疏运交通特征演化机理，运用动态规划理论，研究适应港口发展各阶段陆路集疏运多通道空间尺度的需求，构建沿海大型枢纽港陆路集疏运体系多通道空间尺度随机动态规划模型，为沿海大型枢纽港口集疏运通道建设提供理论支撑。

中文关键词： 沿海枢纽港；陆路集疏运；通道尺度；演化机理；随机动态规划

英文摘要： A stable growth in coastal ports' throughputs and a tendency of upsizing ships sharp the imbalance between supply and demand of port collection and distribution system (PCDS), reflected in the increasingly serious traffic congestion in collecting and distributing corridors (CDCs). The relevant planning and design theories of highway and urban road cannot accurately reflect the supply-demand relationship of PCDS, because of ignoring the influence of ships' arrival and handling features on traffic flow in port. This research takes the spatial scale of landside CDCs in large coastal hub port as objective, explores the complex essence of PCDS, and mines the features of port traffic driven by random factors as ships' arrival. From the perspective of the randomness of ships' arrival and port operation, it studies some theoretical approaches on calculating the service level-based capacity of port CDCs, and proposes the method of determining spatial scale of landside CDCs based on redundancy optimization theory. Furthermore, on the basis of introducing Complex adaptive system(CAS) theory to analyze the evolution mechanism of PCDS in the development of port's scale and function, dynamic programming is used to study the demands of spatial scale of landside CDCs in various stages of port development. A theoretical system o

英文关键词： Coastal hub port；Landside collection and distribution system；Corridor scale；Evolution mechanism；Stochastic dynamic programming