{"title":"利用遗传算法优化楼面面积","authors":"M. Rebaudengo, M. Reorda","doi":"10.1109/GLSV.1994.290002","DOIUrl":null,"url":null,"abstract":"The paper deals with the problem of Floorplan Area Optimization; an approach based on Genetic Algorithms is proposed. The method produces optimal results with CPU time requirements comparable with the ones of other approaches but presents some advantages: it is simple to implement, it allows the user to easily trade off CPU time with result accuracy, it requires a limited amount of memory to store partial results, it is not sensible to special structures like nested wheels. Experimental results on the biggest problems proposed in the literature are reported.<<ETX>>","PeriodicalId":330584,"journal":{"name":"Proceedings of 4th Great Lakes Symposium on VLSI","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Floorplan area optimization using genetic algorithms\",\"authors\":\"M. Rebaudengo, M. Reorda\",\"doi\":\"10.1109/GLSV.1994.290002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper deals with the problem of Floorplan Area Optimization; an approach based on Genetic Algorithms is proposed. The method produces optimal results with CPU time requirements comparable with the ones of other approaches but presents some advantages: it is simple to implement, it allows the user to easily trade off CPU time with result accuracy, it requires a limited amount of memory to store partial results, it is not sensible to special structures like nested wheels. Experimental results on the biggest problems proposed in the literature are reported.<<ETX>>\",\"PeriodicalId\":330584,\"journal\":{\"name\":\"Proceedings of 4th Great Lakes Symposium on VLSI\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 4th Great Lakes Symposium on VLSI\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GLSV.1994.290002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 4th Great Lakes Symposium on VLSI","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLSV.1994.290002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Floorplan area optimization using genetic algorithms
The paper deals with the problem of Floorplan Area Optimization; an approach based on Genetic Algorithms is proposed. The method produces optimal results with CPU time requirements comparable with the ones of other approaches but presents some advantages: it is simple to implement, it allows the user to easily trade off CPU time with result accuracy, it requires a limited amount of memory to store partial results, it is not sensible to special structures like nested wheels. Experimental results on the biggest problems proposed in the literature are reported.<>