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以大规模突发性事件的应急物资调度为背景,解决应急物资车辆配送中时间最短和配送车辆数最少问题。针对多出救点、多受灾点、单物资类型的应急调度问题,构建了应急时间最短、车辆数最少的多目标应急物资车辆调度模型。由于应急物资车辆调度过程中存在道路受阻等许多不确定因素,而采用变精度粗糙集理论引入了参数β,允许一定程度的错误分类率存在,提高不同精度下的不确定信息处理能力。设计的蚁群优化算法对该应急物资调度模型进行求解并与Dijkstra算法计算的结果进行了对比。实验结果验证所提出模型与设计的算法的有效性。
In the context of large-scale emergency deployment of emergency materials, emergency vehicles to solve the shortest delivery time and delivery vehicles the least number of issues. In order to solve the emergency dispatch problem of multiple salvage points, multiple disaster points and single material type, a multi-objective emergency vehicle scheduling model with the shortest emergency time and the minimum number of vehicles is constructed. Because there are many uncertainties such as road obstruction during the process of emergency vehicle dispatching, variable-precision rough set theory is adopted to introduce parameter β, which allows a certain degree of error classification rate to exist and enhances the uncertainty information processing ability under different precision. The ant colony optimization algorithm is designed to solve the emergency material dispatch model and compare with the result of Dijkstra algorithm. The experimental results verify the effectiveness of the proposed model and the designed algorithm.