长江干线多事故点应急资源调度研究

Research on emergency resource scheduling of multiple accident points on the Yangtze River

为了更好地协调长江干线应急能力,针对多起事故同时发生对多种应急资源有需求的情况,考虑到应急救援范围、应急资源种类、应急资源数量等影响因素,以缩短应急时间、满足事故点需求、缩小运输成本为目标,建立多目标调度模型,使用传统和改进粒子群算法求解,对传统粒子群算法从惯性权重参数和环形拓扑结构两个方面进行了改进,增加模型的迭代次数,从而使其能够更好地适应所提出的模型,并获得更高计算精度。以长江干线某多事故点的应急行动为例进行典型案例研究,将构建的应急资源调度模型及相应的求解算法应用于该案例,结果表明,改进后的粒子群算法具有较好的求解质量,得到的结果符合实际情况。可见,提出的应急资源调度模型可以为解决长江干线应急资源调度问题提供支撑。

This paper is to solve the emergency resource scheduling problem when multiple accidents simultaneously occur in the Yangtze River Trunk Line. Emergency resources mainly include rescue and salvage in consideration of the characteristics of the Yangtze River traffic accident. According to different emergency tasks, the types of emergency resources can be further divided into six sub-categories: lifesaving, oil pollution cleaning, fire fighting, sunken ship sludge removal, raising of a wreck, and underwater rescue. Based on the existing research results of emergency resource scheduling, a multi-objective scheduling model is established to optimize the emergency resource scheduling scheme. The goal of the model is to shorten the emergency time, meet the needs of accident points, and reduce transportation costs, considering the influence factors such as the scope of emergency rescue, the types of emergency resources, the number of emergency resources, and the limitations of paths. The traditional particle swarm calculations are optimized in the inertia weight parameters and topological structure. A linear decreasing strategy is used to make the inertia weight value change with the iteration number, and a ring structure is used to increase the iteration number of the model so that it can better adapt to the proposed model. Taking the emergency action at a multi-accident point in the Yangtze River Trunk Line as a typical case study, the model and solution algorithm proposed in this paper are applied to this research case. Comparing the process of the two algorithms, it can be seen that the improved particle swarm algorithm has a slower convergence speed and more iterations, which can avoid prematurely falling into the local optimum, and has better solution quality. The results indicated that the improved algorithm proposed in this paper shortens the emergency action time and reduces the emergency action cost. The obtained results are in line with the actual situation. It can be seen that the emergency resource scheduling model proposed in this paper can provide scientific support when solving the emergency resource scheduling problem of the Yangtze River Trunk Line.