{"title":"考虑单处理器在线模型的大型作业","authors":"E. Tarasova, N. Grigoreva","doi":"10.1109/ICOA55659.2022.9934593","DOIUrl":null,"url":null,"abstract":"The paper proposes for consideration an online scheduling model for single processor with a deadlines and minimization of the total delay. A new LJSF algorithm has been proposed that takes into account the size of the jobs entering the process and is adapted to cases of large jobs. In comparison with existing algorithms, LJSF improved the results on average by 3% - 20% in more than 40% of examples for different testing groups, while in other cases the values of the objective functions were close with a deviation of no more than 2%.","PeriodicalId":345017,"journal":{"name":"2022 8th International Conference on Optimization and Applications (ICOA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Accounting for large jobs for a single-processor online model\",\"authors\":\"E. Tarasova, N. Grigoreva\",\"doi\":\"10.1109/ICOA55659.2022.9934593\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper proposes for consideration an online scheduling model for single processor with a deadlines and minimization of the total delay. A new LJSF algorithm has been proposed that takes into account the size of the jobs entering the process and is adapted to cases of large jobs. In comparison with existing algorithms, LJSF improved the results on average by 3% - 20% in more than 40% of examples for different testing groups, while in other cases the values of the objective functions were close with a deviation of no more than 2%.\",\"PeriodicalId\":345017,\"journal\":{\"name\":\"2022 8th International Conference on Optimization and Applications (ICOA)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 8th International Conference on Optimization and Applications (ICOA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOA55659.2022.9934593\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 8th International Conference on Optimization and Applications (ICOA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOA55659.2022.9934593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Accounting for large jobs for a single-processor online model
The paper proposes for consideration an online scheduling model for single processor with a deadlines and minimization of the total delay. A new LJSF algorithm has been proposed that takes into account the size of the jobs entering the process and is adapted to cases of large jobs. In comparison with existing algorithms, LJSF improved the results on average by 3% - 20% in more than 40% of examples for different testing groups, while in other cases the values of the objective functions were close with a deviation of no more than 2%.
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