【作者】 周泰；

【导师】 叶怀珍；

【作者基本信息】 西南交通大学 ， 物流工程， 2009， 博士

【摘要】 随着全球经济一体化进程的加快,众多企业间、供应链间的竞争已转变为区域之间的竞争。为了保持区域竞争优势,实现经济高速发展,区域就需要更好地运用全部的物流资源,并且必须使这些物流资源所形成的物流能力成为经济高速增长的强劲推动力。因此,关于区域物流能力的研究就有着极其重要的现实意义和战略意义。本文选取区域物流能力作为研究对象,系统深入地研究了区域物流能力的理论构建、量化问题、预测问题以及它与区域经济协同发展过程中存在的两个辩证问题:即通过提高区域物流能力的关键要素量来实现区域经济的快步增长和通过采用经济手段最大程度地增强区域物流能力。本文的创新工作和主要成果体现在以下几个方面:1.论文首先梳理了已有的关于区域物流能力的研究文献,对其相关研究的状况及成果进行了系统分析和总结,指出了目前关于区域物流能力及其与区域经济协同发展相关研究中存在的主要问题,进而提出了本文的研究思路并确定了理论框架。2.对国内外学者关于区域物流能力的主要观点进行深入剖析和比较,对概念所涵盖的实质内容进行深刻理解与把握,在此基础上,对区域物流能力的内涵进行了重新界定,给出了区域物流能力的准确定义,并分析了其特征。然后,运用系统论的思想深入剖析了区域物流能力的构成要素,将区域物流能力分解为基础设施支撑能力、信息系统保障能力、经营管理运作能力、发展环境支持能力四个基本要素,并遵循设定的指标体系构建原则,将其进一步分解,生成相关的定性定量指标,构建了科学系统的、具有一定通用性的区域物流能力三层量化指标体系,建立了区域物流能力的理论体系。3.对区域物流能力的量化问题进行了研究。根据已构建的区域物流能力量化指标体系,并针对量化指标存在的不确定性和模糊性,以及指标之间的不相容性等特点,采用了物元分析理论,并结合模糊集合和欧氏贴近度的概念,建立了基于欧式贴近度的区域物流能力模糊物元分析模型。采用综合集成赋权法来确定量化指标的权重系数,使得到的综合权值同时体现了主观信息和客观信息,更加科学。实例分析验证了该量化模型的实用性和合理性。4.对区域物流能力的有效预测方法进行了研究。为获得合理、准确的短期预测结果,采用了组合预测的方法,将灰色系统理论中的GM预测模型与径向基函数神经网络有效地结合起来,综合了灰色系统的贫乏数据建模的优点和神经网络特有的高度非线性映射能力,构建了基于灰色径向基函数网络的非线性组合预测模型,并通过实例分析验证了该预测模型的有效性。5.对通过提高区域物流能力的关键要素量来实现区域经济快步增长的问题进行了研究。将区域经济与区域物流能力的作用关系,分解成区域产业经济与区域物流能力的作用关系,进而分解成区域产业经济与区域物流能力关键要素的作用关系,建立了一个与产业经济结构相对应的区域物流能力灰色控制模型。在建模方法上,采用了适用于多个因素关系的GM(1,N)模型来进行构建。在灰色控制系统模型中,选取区域物流能力量化指标体系中的三个关键指标作为系统的控制变量,表征区域产业经济规模的GDP产值作为状态变量,充分揭示了区域产业经济与物流能力关键要素的作用关系。6.对通过采用投资这种经济手段,来最大程度地提高区域物流能力的问题进行了研究。建立了区域物流能力的带有约束条件限制的产业投资结构优化非线性规划模型,然后,利用RBF神经网络来映射区域产业投资分配结构与区域物流能力的复杂的、高度非线性关系,构建了基于RBF网络的非线性规划优化模型,并采用改进的遗传算法,求解了非线性规划优化模型,获得了优化问题的近似最优解以及投资结构的优化方向。本文采用定性分析与定量分析相结合、数学建模与实证分析相结合的研究方法,体现了理论与实践相结合的原则。各种研究成果对我国区域物流与区域经济协同发展的理论探索具有一定的开拓意义,对现实问题的解决具有良好的理论指导和实践参考作用。更多还原

【Abstract】 With the acceleration of the global economic integration, the competitions among enterprises and supply chains have already transformed into regional competition. In order to maintain competition advantage and achieve the high-speed development of the regional economy, regions need to make better use of logistics resources and make regional logistics capability (RLC), which is formed by logistics resources, become the powerful impetus to the high-speed development of regional economy. Therefore, the study on RLC has an important realistic significance and strategic meaning.In this dissertation, the author chooses the RLC as the research object, study thoroughly and systematically on its problems of theory structure, quantization, forecast and two dialectical problems of its development in coordination with regional economy, the problems of how to achieve regional economic growth in the quickstep by improving the value of key elements of RLC and strengthen RLC to the greatest extent by using economic means. The original works and main contributions of this dissertation can be summarized as follows:1. The author reviews the existing literatures of RLC at first, analyzes and summaries the relative research situations and results systematically, points out the main problems of existing study on RLC and its development in coordination with regional economy at present, and puts forward the research thoughts and theoretical framework of this dissertation.2. The author thoroughly analyzes and compares the major views of scholars both at home and abroad on RLC, so as to understand and grasp the essence which is covered by the concept in-depth. On this basis, the author explains the connotation of RLC, gives a precise definition of RLC, and analyzes its characteristics. Then according to the thoughts of system theory, the author breaks RLC down into the four basic key elements of supporting capability of infrastructure, supportability of information system, management operational capability, and supportive capability of development environment, and further decomposes each basic key element into different qualitative and quantitative indexes conforming to the constructing principle of index system, scientifically sets up a three-layer quantitative index system with strong commonality, and establishes the theoretical system of RLC.3. The author studies the problem of quantization of RLC. On the basis of the quantitative index system of RLC, and aiming at the uncertainty and fuzziness of some quantitative indexes and incompatibility of index each other, the dissertation sets up a quantitative model of RLC based on Euclid approach degree of fuzzy matter-element by adopting matter-element theory and combining it with fuzzy set and the concept of Euclid approach degree; calculates the weight coefficient of indexes by using the method of comprehensive integration granting weight, which reflects the subjective and objective information comprehensively; verifies the practicability and rationality of the quantitative model by means of case-study.4. The author studies the effective forecasting method of RLC. In order to get reasonable and accurate results in the short-term forecast, the dissertation adopts a method of combination forecasting, which combines GM of grey system theory with radial basis function(RBF) neural network together effectively and gives full scope to their double-edged advantages that the grey system can construct forecasting model with poor information and neural network is capable of high non-linear mapping uniquely, constructs a new kind of non-linear combined forecasting model of RLC based on grey RBF neural network, and verifies the validity of the forecasting model by means of case-study.5. The author studies the problem of how to achieve regional economic rapid growth by improving the value of key elements of RLC. The dissertation breaks the relationship of regional economic and RLC down into the relationship of regional industrial economy and RLC, and further into the relationship of regional industrial economy and key elements of RLC, builds a grey control system of RLC and industrial economy. In the control model, the dissertation adopts the model GM(1,N) which is applicable to multi-factor analysis, chooses three key elements of RLC as control variables, and regional industrial gross domestic product(GDP) which represent industrial economic scale as state variables, fully reveales the relation between regional industrial economy and key elements of RLC.6. The author studies the problem of how to improve RLC to the greatest extent by using economic means of investment. In the first place, the dissertation sets up a nonlinear programming (NLP) optimization model of RLC with constraint conditions on industrial investment; Then constructs the investment structural optimization model of RLC based on RBF neural network by using RBF neural network which maps complex nonlinear relation between RLC and industrial investment; Finally, solves the model by improved genetic algorithm(IGA),and obtains the approximate optimal solution of the optimization problem ,as well as the optimal direction of investment structural.This dissertation adopts the study methods of qualitative analysis combined with quantitative analysis and mathematical modeling combined with empirical analysis, which embodies the principles of integrating theory with practice. The results of study have certain pioneering meanings for theoretical exploration of synergistic development of the regional logistics and regional economy of our country; they also have good theoretical direction and practical reference guide for the solution of realistic problems.更多还原