{"title":"一种混合遗传算法在大量受害者涌入的情况下对医院资源进行评估","authors":"Abderrahmane Ben Kacem, Oualid Kamach, S. Chafik","doi":"10.1109/LOGISTIQUA.2019.8907324","DOIUrl":null,"url":null,"abstract":"This paper describes a hybrid approach to size the hospital resources in the cases of a massive influx of victims generated by a disaster situation (natural or made man disaster). This suggested approach based on the genetic algorithm is a blending between the simulation (ARENA) and machine learning (Neural Networks). The first one produces a matrix of theoretical solutions and the second one contributes a solution based on the feedback on experiences. This method provided a reliable and efficient solution based on available resources and on a solutions applied in real cases. The result shows that the genetic algorithm provided a new solution that improves the solutions got by the simulation. Also we made an application as a decision support tool for hospital decision-makers to provide with the needs of resources in the same cases. This work is being carried out in collaboration with the Mohammed 5 hospital center in Casablanca (Morocco).","PeriodicalId":435919,"journal":{"name":"2019 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A hybrid genetic algorithm to size the hospital resources in the case of a massive influx of victims\",\"authors\":\"Abderrahmane Ben Kacem, Oualid Kamach, S. Chafik\",\"doi\":\"10.1109/LOGISTIQUA.2019.8907324\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a hybrid approach to size the hospital resources in the cases of a massive influx of victims generated by a disaster situation (natural or made man disaster). This suggested approach based on the genetic algorithm is a blending between the simulation (ARENA) and machine learning (Neural Networks). The first one produces a matrix of theoretical solutions and the second one contributes a solution based on the feedback on experiences. This method provided a reliable and efficient solution based on available resources and on a solutions applied in real cases. The result shows that the genetic algorithm provided a new solution that improves the solutions got by the simulation. Also we made an application as a decision support tool for hospital decision-makers to provide with the needs of resources in the same cases. This work is being carried out in collaboration with the Mohammed 5 hospital center in Casablanca (Morocco).\",\"PeriodicalId\":435919,\"journal\":{\"name\":\"2019 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LOGISTIQUA.2019.8907324\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LOGISTIQUA.2019.8907324","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A hybrid genetic algorithm to size the hospital resources in the case of a massive influx of victims
This paper describes a hybrid approach to size the hospital resources in the cases of a massive influx of victims generated by a disaster situation (natural or made man disaster). This suggested approach based on the genetic algorithm is a blending between the simulation (ARENA) and machine learning (Neural Networks). The first one produces a matrix of theoretical solutions and the second one contributes a solution based on the feedback on experiences. This method provided a reliable and efficient solution based on available resources and on a solutions applied in real cases. The result shows that the genetic algorithm provided a new solution that improves the solutions got by the simulation. Also we made an application as a decision support tool for hospital decision-makers to provide with the needs of resources in the same cases. This work is being carried out in collaboration with the Mohammed 5 hospital center in Casablanca (Morocco).