{"title":"应用遗传算法进行生产与维修一体化规划","authors":"Ghita Ettaye, A. E. Barkany, A. E. Khalfi","doi":"10.1109/LOGISTIQUA.2017.7962892","DOIUrl":null,"url":null,"abstract":"The planning of maintenance activities can hinder manufacturing operations in term of cost, quality and time, but it is necessary to ensure the availability of the production equipment to meet customer demands. We propose to model the function of maintenance tasks and production operations by the sum of the two costs under a set of constraints. As a method of resolution, we use genetic algorithms to optimize the integrated plan and to compare our results with the existing work in the literature.","PeriodicalId":310750,"journal":{"name":"2017 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Applying genetic algorithm for integrated planning of production and maintenance\",\"authors\":\"Ghita Ettaye, A. E. Barkany, A. E. Khalfi\",\"doi\":\"10.1109/LOGISTIQUA.2017.7962892\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The planning of maintenance activities can hinder manufacturing operations in term of cost, quality and time, but it is necessary to ensure the availability of the production equipment to meet customer demands. We propose to model the function of maintenance tasks and production operations by the sum of the two costs under a set of constraints. As a method of resolution, we use genetic algorithms to optimize the integrated plan and to compare our results with the existing work in the literature.\",\"PeriodicalId\":310750,\"journal\":{\"name\":\"2017 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LOGISTIQUA.2017.7962892\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LOGISTIQUA.2017.7962892","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Applying genetic algorithm for integrated planning of production and maintenance
The planning of maintenance activities can hinder manufacturing operations in term of cost, quality and time, but it is necessary to ensure the availability of the production equipment to meet customer demands. We propose to model the function of maintenance tasks and production operations by the sum of the two costs under a set of constraints. As a method of resolution, we use genetic algorithms to optimize the integrated plan and to compare our results with the existing work in the literature.
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