【作者】 高鹏；

【导师】 金淳； 韩庆平；

【作者基本信息】 大连理工大学 ， 管理科学与工程， 2011， 博士

【摘要】 在当今世界经济全球化的背景下,现代集装箱港口已经成为以港口为中心,整合周边各种物流要素的港口物流网络系统,成为功能更全面的多式联运系统的衔接点。在此背景下,如何评估整个港口物流网络系统的服务性能以及如何通过提高自身的服务能力来增加竞争力是当前急需解决的问题。本研究以集装箱港口物流网络系统为研究对象,研究了系统运作过程的建模问题,以及系统中关键要素堆场的作业调度进行优化问题。本文的具体研究工作如下：(1)基于排队网络的港口物流网络系统运作过程的建模研究。将整个港口物流网络系统的物流设施抽象为一个有向资源网络,其中卡口、码头、场站以及交叉路口为网络的节点,道路为网络的边,连接各节点资源。以排队网络理论为基础,首先针对资源网络中节点和边建立排队模型,然后阐述整个系统为调转混合排队网络。由于该排队网络模型不同于经典排队网络模型的基本假设,为求解系统模型,建立了基于离散事件仿真原理的系统仿真模型,并提出了基于操作分析法的系统运作性能指标的计算方法。(2)基于高层体系结构(High Level Architecture, HLA)的港口物流网络系统分布式仿真建模研究。为解决庞大的港口物流网络仿真模型在建模时所面临的可扩展性、互操作和重用性等问题,本文采用基于HLA的分布式仿真方法对港口物流网络系统进行建模。由于在HLA规范中缺乏与联邦成员分解原理相关的理论分析,因此本文采用基于解释结构模型的分析方法对港口物流网络系统中的物流作业活动进行分解,进而划分系统的仿真联邦成员。在系统实现上,分析了仿真联邦成员的基本功能,并重点分析了联邦成员集成的关键问题：联邦对象模型(Federation Object Model, FOM)的设计和交互时序的设计。(3)港口物流网络系统作业节点的堆场的提箱作业优化研究。针对堆场提箱作业中倒箱过程优化提出了两层嵌套的组合优化模型,并设计了基于启发式A*算法与GA算法组合的4种方案对模型进行求解。首先分析了倒箱设备——正面吊的作业规则,以及堆场的堆放规则,然后在分析倒箱序列以及设备作业移动路径的基础上,提出了外层为倒箱序列优化,内层为倒箱作业移动路径优化的两层优化模型。针对该模型提出两层嵌套优化算法的求解流程,并基于A*和遗传算法分别设计了外层和内层算法,提出了4种求解方案。更多还原

【Abstract】 In the background of economic globalization, the container ports have become important connection centers of the multimodal transportation system which is a port logistic network system integrating various different logistics elements and developing into more comprehensive logistics functions. In this background, it has become the quite important issue to be solved now that how to evaluate the service performance of the whole port logistics network system and to enhance competitiveness by advancing service capability.In this dissertation, the port logistics network system is taken as the research object, the problems of modeling operating process of the logistics network system and optimizing the operation scheduling of the container yards as key elements in port logistics network system are studied. Our contributions are shown as follows:(1) Research on modeling operating process of port logistics network system based on queuing network. The whole port logistics network system is attributed to a directed resource network, where the checkpoints, container terminals, container freight stations and intersections are the nodes of the network, and the road connecting with the nodes are the edges of the network. Based on the queuing network theory, firstly, the queuing network model is established for the nodes and edges of the resource network, then conclude that the entire system is a mixed queuing network with transfer blocking. Since the model is different from the basic hypothesis of classical queuing network model, to solve the system model, this dissertation builds the system simulation model based on the discrete event simulation theory, and establishes the method for evaluating system operation performance index based on operation analysis method.(2) Research on distributed simulation modeling of port logistics network system based on High Level Architecture(HLA). In order to solve the extensibility, interoperability, reusability of the bulky simulation model for port logistics network system, the dissertation adopts distributed simulation method based on HLA to build the model of port logistics network system. For the lack of theoretical analysis about decomposing the whole system into federates in HLA specification, we adopt the analysis method based on Interpretation Structural Modeling(ISM) to decompose the logistics activities of the whole port logistics network system, and then divide the simulation federates. For the implementation of system modeling, the key issues are discussed:design of the federation object model (FOM) and interactive time sequence.(3) Research on the optimization of container pick-up operation on yard as operation nodes on port logistics network system. A two-layer nested combinatorial optimization model is proposed for the rehandling process in container yard. Then the model is solved by four schemes based on the algorithm combination of heuristic A* arithmetic and genetic algorithm. Firstly, the dissertation analyzes the operation rules of reach stackers and yard storage. Then the two-layer nested optimization model is established based on the analyzing the rehandling sequence and moving paths of a container. The outer layer of the model is used for rehandling sequence optimization, and the inner layer for moving path optimization of rehandling operation. This dissertation proposes a solving process of two-layer nested optimization algorithm, designs a two-layers algorithms respectively based on heuristic A*arithmetic and genetic algorithm, and proposes four kinds of solving schemes.更多还原