基于GIS的救灾应急物资车辆调度研究

In China, occurred frequently a lot of natural disasters. In the rescue and relief work, it is an important social significance and practical value that establish a relief commodity transportation and vehicle scheduling who could render the disaster-relief emergency materials be delivered quickly, effectively and reliably to the area where need them.The geographic information systems (GIS) is an information system with strong spatial analysis function. This study will explore research base on GIS in the vehicle routing problem of disaster-relief emergency materials, improve the responsiveness of the emergency rescue..Due to the uncertainty of natural disasters, the demand of the disaster-relief emergency materials is becoming uncertain. The demand information can not be accumulated over a long term, or difficult to be provided a clear description. The case-based fuzzy inference will be applied in this study, analyzing and forecasting the demand of the disaster-relief emergency materials.In the vehicle routing problem of disaster-relief emergency materials, the most important is that to ensure the transportation volume in least time, considering the economic value. In other words, it is a multi-objective decision taking into account the factors of the time, the transportation volume and the economic value. Considering the stochastic of the demand information and the traffic time, the chance-constrained programming with fuzzy parameters will be used for the modeling of the vehicle routing problem. Solving by the evolutionary algorithm, the optimal routing will be chosen to distribute the disaster-relief emergency materials.

在我国，自然灾害时有发生。在抢险救灾工作中，派遣救援车辆以最短的时间、运用相对经济的方式，准确的把救灾应急物资调运到灾区，具有重大的社会意义和应用价值。地理信息系统（GIS）是一种具有空间数据处理功能的信息系统。本研究将结合GIS技术，探讨基于GIS的救灾应急物资运输车辆路径问题，提高应急救援工作的响应能力。.由于自然灾害的不确定性，救灾应急物资的需求随之变得具有不确定性。需求信息无法长期积累,或难以提供清晰的描述。本课题拟应用基于案例的模糊推理，分析预测救灾应急物资需求。救灾应急物资运输车辆路径选择的核心就是在最短的时间内保证运量最大，兼顾经济性,即考虑时间、运量、经济等因素的多目标决策。针对需求点的需求信息和需求点之间的旅行时间的不确定，运用含有模糊参数的机会约束规划对应急物资运输车辆路径问题进行建模。采用演化算法求解该问题,选择优化的路径，将救灾应急物资进行配送。

在我国，洪涝灾害时有发生，在抢险救灾工作中，派遣救援车辆以最短的时间、运用相对经济的方式，准确的把救灾应急物资调运到灾区，具有重大的社会意义和应用价值。.由于自然灾害的不确定性，救灾应急物资的需求随之变得具有不确定性。需求信息无法长期积累,或难以提供清晰的描述。课题搜集了近年来我国洪涝灾害的相关案例，选取了其中比较有代表性的特征数据，运用基于案例的模糊推理，分析预测救灾应急物资需求，用模糊数来描述需求数量。救灾应急物资运输车辆路径选择的核心就是在最短的时间内保证运量最大，兼顾经济性,即考虑时间、运量、经济等因素的多目标决策。针对需求点的需求信息的模糊量，运用可能性理论构建了应急物资运输车辆路径问题的模糊机会约束规划模型。然后设计了遗传算法求解该问题，得到优化的车辆运输路径，既满足受灾点时限要求、又能使配送时间和成本最低。.