常规移动医疗服务的车辆路径和调度
Vehicle Routing and Scheduling for Regular Mobile Healthcare Services
摘要：
我们提出了我们的解决方案，一个特定的实际问题，在域中的车辆路径和调度。一般的任务是找到最小数量的\emph{mobile resources}的最佳分配，可以在远程位置提供定期服务。这些\emph{mobile resources}位于一个中心位置。规范最初是为一个实际应用程序定义的，它是一个正在进行的项目的起点。特别是，目标是减轻罗马尼亚城市周围农村地区的健康问题。配备医疗设备的面包车按计划每天从县首府出发，在县内的乡镇提供一定数量的检查，并在同一天返回首府。从医疗保健的角度来看，每辆面包车都配备了超声波扫描仪，他们计划在每三个月对孕妇进行调查，以诊断潜在的问题。该项目的动机是，目前有报告将罗马尼亚列为欧洲联盟婴儿死亡率最高的国家。我们分两个阶段开发解决方案：对与我们的目标最相关的参数和数据进行建模，然后设计和实现一种算法，以提供优化的解决方案。输出调度的最重要指标是每个乡镇提供给定检查时间所需的货车数量，其次是总旅行时间或燃料消耗，不同路线的数量等。我们的解决方案实现了两种概率算法，我们从中选择了表现最好的一种。
英文摘要：
We propose our solution to a particular practical problem in the domain of vehicle routing and scheduling. The generic task is finding the best allocation of the minimum number of \emph{mobile resources} that can provide periodical services in remote locations. These \emph{mobile resources} are based at a single central location. Specifications have been defined initially for a real-life application that is the starting point of an ongoing project. Particularly, the goal is to mitigate health problems in rural areas around a city in Romania. Medically equipped vans are programmed to start daily routes from county capital, provide a given number of examinations in townships within the county and return to the capital city in the same day. From the health care perspective, each van is equipped with an ultrasound scanner, and they are scheduled to investigate pregnant woman each trimester aiming to diagnose potential problems. The project is motivated by reports currently ranking Romania as the country with the highest infant mortality rate in the European Union. We developed our solution in two phases: modeling of the most relevant parameters and data available for our goal and then design and implement an algorithm that provides an optimized solution. The most important metric of an output scheduling is the number of vans that are necessary to provide a given amount of examination time per township, followed by total travel time or fuel consumption, number of different routes, and others. Our solution implements two probabilistic algorithms out of which we chose the one that performs the best.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
