The rapid outbreak of COVID-19 pandemic invoked scientists and researchers to prepare the world for future disasters. During the pandemic, global authorities on healthcare urged the importance of disinfection of objects and surfaces. To implement efficient and safe disinfection services during the pandemic, robots have been utilized for indoor assets. In this paper, we envision the use of drones for disinfection of outdoor assets in hospitals and other facilities. Such heterogeneous assets may have different service demands (e.g., service time, quantity of the disinfectant material etc.), whereas drones have typically limited capacity (i.e., travel time, disinfectant carrying capacity). To serve all the facility assets in an efficient manner, the drone to assets allocation and drone travel routes must be optimized. In this paper, we formulate the capacitated vehicle routing problem (CVRP) to find optimal route for each drone such that the total service time is minimized, while simultaneously the drones meet the demands of each asset allocated to it. The problem is solved using mixed integer programming (MIP). As CVRP is an NP-hard problem, we propose a lightweight heuristic to achieve sub-optimal performance while reducing the time complexity in solving the problem involving a large number of assets.
翻译:COVID-19大流行病的迅速爆发使科学家和研究人员为未来灾害做好准备。在这一大流行病期间,全球保健当局敦促对物体和表面进行消毒的重要性。为了在大流行病期间实施高效和安全的消毒服务,机器人被用于室内资产。在本文件中,我们设想使用无人驾驶飞机对医院和其他设施室外资产进行消毒,这种分散的资产可能有不同的服务需求(如服务时间、消毒材料的数量等),而无人驾驶飞机通常能力有限(即旅行时间、消毒载荷能力)。为了以高效的方式为所有设施资产提供服务,必须优化无人驾驶飞机对资产分配和无人驾驶飞机旅行路线的优化。在本文件中,我们提出了机动车辆路由问题,以便为每架无人驾驶飞机找到最佳路线,以便尽可能缩短总服务时间,同时,无人驾驶飞机满足分配给它的每一资产的需求。问题通过混合整数编程解决(MIP)。由于CVRP是一个棘手的问题,我们提议在减少涉及复杂程度的大型资产时,轻量的超额资产。