突发事件应急物资调配方案研究

发布时间：2018-09-07 07:55

【摘要】：为了及时有效地抢救灾区人民的生命和财产,降低灾害造成的巨大损失,保障人民生活的正常进行,建立与研究适于我国国情的应急物流体系已刻不容缓了。而作为应急物流环节中最关键的一个环节的应急物资调配,关系到应急物资能否准确、高效地被运输到受灾点,同时也往往关系到救援工作的成败与否。因此研究重灾区的应急物资调配问题意义重大。论文通过汇总国内外对应急物流领域研究的相关文献资料,明确了研究应急物流具有重大实践意义,论述了应急物流与普通物流的区别;强调应急物流系统具有不确定性、弱成本性等特点,运用物流工程学和管理运筹学的相关理论,在“强时效性、弱经济性”的指导下,基于应急物流系统,将应急物资调配问题作为核心进行研究。论文主要做的研究工作如下:1.介绍了应急物资需求预测基础理论,在考虑灾区信息不确定的条件下,引入基于CBR技术的应急物资需求预测模型;通过应用该模型准确、高效地预测受灾点的应急物资需求量。最后取得的预测结果令人满意,为进行应急物资调配提供研究基础;2.考虑到应急救援初期灾区环境存在诸如信息严重缺失和道路塌陷等不确定性因素,以应急时间的不确定性来表示这些影响因素,然后通过引入区间数数学理论来表示应急时间的不确定性。在多资源连续消耗的多出救点系统下,建立以应急开始时间最早的多资源应急物资调配模型;3.在时间确定的条件下,考虑道路网中各个路段对应急物资调配的影响,分别建立了多出救点、单受灾点的应急时间最小、应急物资流量最大的多目标调配模型和多出救点、多受灾点的应急时间最小、应急成本最小的应急物资车辆路径—调配模型,在模型的求解中,使用了Dijkstra和Floyd算法以及变式的最小费用最大流算法对模型进行求解;4.使用Matlab工具对算法进行编程,并将研究理论运用于算例分析之中,验证了论文中所建模型的有效性和算法效率具有的高效性,使应急物资调配更加高效而准确的进行。
[Abstract]:In order to save the lives and property of the people in the disaster area in time and effectively, to reduce the huge losses caused by the disasters and to ensure the normal life of the people, it is urgent to establish and study the emergency logistics system suitable for the national conditions of our country. As the most critical link in emergency logistics, emergency material allocation is related to whether the emergency materials can be accurately and efficiently transported to the disaster site, but also often related to the success or failure of the rescue work. Therefore, it is of great significance to study the allocation of emergency materials in the worst-hit areas. By summarizing the relevant literature of emergency logistics research at home and abroad, the paper clarifies the significance of studying emergency logistics, discusses the difference between emergency logistics and ordinary logistics, emphasizes the uncertainty of emergency logistics system. Under the guidance of "strong timeliness and weak economy" under the guidance of "strong timeliness and weak economy", based on the emergency logistics system, the problem of emergency material allocation is taken as the core of the research by using the relevant theories of logistics engineering and management operations research. The main research work of this paper is as follows: 1. This paper introduces the basic theory of emergency material demand prediction, introduces the emergency material demand forecasting model based on CBR technology under the condition of considering the uncertain information of disaster area, and predicts the emergency material demand in the disaster-stricken area accurately and efficiently by using this model. The prediction results obtained are satisfactory and provide a research basis for emergency material allocation. Considering that there are uncertainties in the environment of the disaster areas in the initial stages of emergency response, such as serious lack of information and road collapse, and that these factors are expressed in terms of the uncertainty of the emergency response time, Then the uncertainty of emergency time is expressed by introducing interval number theory. In this paper, a multi-resource emergency material allocation model with the earliest emergency start time is established under the system of multi-resource continuous consumption. Under the condition of time determination, considering the influence of each section of road network on emergency material allocation, the multi-objective deployment model and the extra rescue point are established, which have the minimum emergency time and the largest flow of emergency materials. In order to solve the model, Dijkstra and Floyd algorithms and variable minimum cost maximum flow algorithm are used to solve the model of vehicle routing and allocation of emergency materials with minimum emergency time and minimum emergency cost. The algorithm is programmed with Matlab tool and the research theory is applied to the analysis of an example. The validity of the model and the efficiency of the algorithm are verified, which makes the allocation of emergency materials more efficient and accurate.
【学位授予单位】：兰州交通大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：D63

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