突发事件应急医疗物资调度的随机算法

Randomized Algorithm for Vehicle Routing Model for Medical Supplies in Large-Scale Emergencies

传统的车辆路径问题(VRP)是为车辆设计将物资从仓库运送到各个需求客户的路线,使得总的运输费用(或时间)最小。在本文中,我们更关心的是使得未满足的需求量和总的物资延误时间最小。这个模型的一个非常重要的应用就是当大规模突发事件发生以后如何有效的将应急医疗物资运送到各个医疗单位,例如自然灾难,恐怖袭击之后,各个医院的医疗物资有限,需要从应急中心调集所需物资,在这种情况下,从应急中心分发应急物资过程中的运输费用就不再是最主要的考查因素,而更重要的是考虑物资到达医院的时间以及到达量,因为这两个因素直接与病人生命息息相关。本文的主要工作是改进了已有的局部搜索算法,通过引入随机算法的思想设计了求解模型的改进随机算法,可以得到模型更优的解,并通过计算机模拟案例说明了算法是行之有效的。

A typical Vehicle Routing Problem （VRP） is goods from inventory to demanding customer locations. minimize unmet demand and time delays. An important to design the least cost routes for a vehicle fleet to supply In this paper, we are interested in routing vehicles to application of the presented model is to distribute medical supplies to response to large-scale emergencies, such as natural disasters, decease outbreaks, or acts of terrorism in which the supplies must be sent to cover all demands in the recommended response time. In this situation, transportation cost is the least important because it is unmet demand and/or time delay in an emergency situation that results in loss of life. In this paper, we design an Improved Randomized Algorithm （IRA） for the vehicle routing problem for large-scale emergency scenario. This algorithm can be very useful for emergency responder to best use the available vehicles in case of emergencies.