{"title":"定期移动医疗保健服务的车辆路线和调度","authors":"Cosmin Pascaru, Paul Diac","doi":"10.1109/ICTAI.2018.00080","DOIUrl":null,"url":null,"abstract":"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 minimum number of mobile resources that can provide periodical services in remote locations. These 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 healthcare 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 European Union. Our solution was developed in two phases: first modeling of the most relevant parameters and data available for our goal and second, design and implement an algorithm that provides an optimized solution. The most important metric of a 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, etc. Our solution implements two probabilistic algorithms out of which the best was chosen.","PeriodicalId":254686,"journal":{"name":"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Vehicle Routing and Scheduling for Regular Mobile Healthcare Services\",\"authors\":\"Cosmin Pascaru, Paul Diac\",\"doi\":\"10.1109/ICTAI.2018.00080\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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 minimum number of mobile resources that can provide periodical services in remote locations. These 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 healthcare 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 European Union. Our solution was developed in two phases: first modeling of the most relevant parameters and data available for our goal and second, design and implement an algorithm that provides an optimized solution. The most important metric of a 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, etc. Our solution implements two probabilistic algorithms out of which the best was chosen.\",\"PeriodicalId\":254686,\"journal\":{\"name\":\"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTAI.2018.00080\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTAI.2018.00080","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vehicle Routing and Scheduling for Regular Mobile Healthcare Services
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 minimum number of mobile resources that can provide periodical services in remote locations. These 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 healthcare 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 European Union. Our solution was developed in two phases: first modeling of the most relevant parameters and data available for our goal and second, design and implement an algorithm that provides an optimized solution. The most important metric of a 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, etc. Our solution implements two probabilistic algorithms out of which the best was chosen.