{"title":"带后进先出缓冲区的作业重调度算法,以最小化延迟作业的加权数","authors":"Ulrich Pferschy, Julia Resch, G. Righini","doi":"10.1007/s10951-022-00751-9","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":50061,"journal":{"name":"Journal of Scheduling","volume":"26 1","pages":"267 - 287"},"PeriodicalIF":1.4000,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Algorithms for rescheduling jobs with a LIFO buffer to minimize the weighted number of late jobs\",\"authors\":\"Ulrich Pferschy, Julia Resch, G. Righini\",\"doi\":\"10.1007/s10951-022-00751-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":50061,\"journal\":{\"name\":\"Journal of Scheduling\",\"volume\":\"26 1\",\"pages\":\"267 - 287\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2022-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Scheduling\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s10951-022-00751-9\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Scheduling","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s10951-022-00751-9","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
期刊介绍:
The Journal of Scheduling provides a recognized global forum for the publication of all forms of scheduling research. First published in June 1998, Journal of Scheduling covers advances in scheduling research, such as the latest techniques, applications, theoretical issues and novel approaches to problems. The journal is of direct relevance to the areas of Computer Science, Discrete Mathematics, Operational Research, Engineering, Management, Artificial Intelligence, Construction, Distribution, Manufacturing, Transport, Aerospace and Retail and Service Industries. These disciplines face complex scheduling needs and all stand to gain from advances in scheduling technology and understanding.