论文标题
用于优化航空救护车舰队登台的算法
Algorithms for Optimizing Fleet Staging of Air Ambulances
论文作者
论文摘要
在灾难情况下，空中救护车快速反应通常是患者生存的决定因素。障碍加剧了这种情况，地理偏僻和车辆放置的局限性使其成为一项艰巨的任务。考虑到这些要素，响应者的安排是至关重要的关键决定。利用真实的任务数据，这项研究通过整数线性编程结构了一个最佳的覆盖范围问题。为了进行准确的比较，将Gurobi优化器与开发的模型进行了编程，并定时进行了性能。创建了实现基础排名的解决方案，然后创建了基于本地和禁忌搜索的算法。事实证明，本地搜索算法不足以最大程度地提高覆盖范围，而禁忌搜索取得了近乎最佳的结果。在后一种情况下，将总车辆的行程距离最小化，并且运行时大大优于Gurobi产生的车辆。此外，利用并行CUDA处理的变化进一步降低了算法运行时。事实证明，随着测试任务的数量增加，同时也保持了相同的最小距离。
In a disaster situation, air ambulance rapid response will often be the determining factor in patient survival. Obstacles intensify this circumstance, with geographical remoteness and limitations in vehicle placement making it an arduous task. Considering these elements, the arrangement of responders is a critical decision of the utmost importance. Utilizing real mission data, this research structured an optimal coverage problem with integer linear programming. For accurate comparison, the Gurobi optimizer was programmed with the developed model and timed for performance. A solution implementing base ranking followed by both local and Tabu search-based algorithms was created. The local search algorithm proved insufficient for maximizing coverage, while the Tabu search achieved near-optimal results. In the latter case, the total vehicle travel distance was minimized and the runtime significantly outperformed the one generated by Gurobi. Furthermore, variations utilizing parallel CUDA processing further decreased the algorithmic runtime. These proved superior as the number of test missions increased, while also maintaining the same minimized distance.
