{"title":"自调整优化,以兼容交付和低能耗","authors":"Chending Mao, Jia Lin, S. Arima","doi":"10.1109/ISSM55802.2022.10027098","DOIUrl":null,"url":null,"abstract":"This paper introduced n-step hybrid flow-shop scheduling (nHFS) with batch process to consider a trade-offs between power consumption and productivity. Wider optimization scope with power conscious have been advanced to increase efficiency of algorithm and tune the parameter automatically based on our past research. Concretely, Energy consumption and due date are considered in Self-tuning Optimization. Actual companies' data are used to evaluate the performance of proposed and past methods.","PeriodicalId":130513,"journal":{"name":"2022 International Symposium on Semiconductor Manufacturing (ISSM)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Self-tuning Optimization to Compatible the Delivery and Low Energy Consumption\",\"authors\":\"Chending Mao, Jia Lin, S. Arima\",\"doi\":\"10.1109/ISSM55802.2022.10027098\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduced n-step hybrid flow-shop scheduling (nHFS) with batch process to consider a trade-offs between power consumption and productivity. Wider optimization scope with power conscious have been advanced to increase efficiency of algorithm and tune the parameter automatically based on our past research. Concretely, Energy consumption and due date are considered in Self-tuning Optimization. Actual companies' data are used to evaluate the performance of proposed and past methods.\",\"PeriodicalId\":130513,\"journal\":{\"name\":\"2022 International Symposium on Semiconductor Manufacturing (ISSM)\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Symposium on Semiconductor Manufacturing (ISSM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSM55802.2022.10027098\",\"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 International Symposium on Semiconductor Manufacturing (ISSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSM55802.2022.10027098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Self-tuning Optimization to Compatible the Delivery and Low Energy Consumption
This paper introduced n-step hybrid flow-shop scheduling (nHFS) with batch process to consider a trade-offs between power consumption and productivity. Wider optimization scope with power conscious have been advanced to increase efficiency of algorithm and tune the parameter automatically based on our past research. Concretely, Energy consumption and due date are considered in Self-tuning Optimization. Actual companies' data are used to evaluate the performance of proposed and past methods.