{"title":"蚁群算法在算术电路进化设计中的应用","authors":"M. Abd-El-Barr, S. M. Sait, Bambang A. B. Sarif","doi":"10.1109/ICM.2003.238612","DOIUrl":null,"url":null,"abstract":"Evolutionary computation is a new field of research in which hardware design is pursued by deriving inspiration from biological organisms. This new paradigm is expected to radically change the synthesis procedures in a way that allows discovering novel designs and/or more efficient circuits. In this paper, a multi objective optimization strategy for design of arithmetic circuits based on Ant Colony optimization algorithm is presented. Results are compared with those obtained using other techniques.","PeriodicalId":180690,"journal":{"name":"Proceedings of the 12th IEEE International Conference on Fuzzy Systems (Cat. No.03CH37442)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Ant colony algorithm for evolutionary design of arithmetic circuits\",\"authors\":\"M. Abd-El-Barr, S. M. Sait, Bambang A. B. Sarif\",\"doi\":\"10.1109/ICM.2003.238612\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Evolutionary computation is a new field of research in which hardware design is pursued by deriving inspiration from biological organisms. This new paradigm is expected to radically change the synthesis procedures in a way that allows discovering novel designs and/or more efficient circuits. In this paper, a multi objective optimization strategy for design of arithmetic circuits based on Ant Colony optimization algorithm is presented. Results are compared with those obtained using other techniques.\",\"PeriodicalId\":180690,\"journal\":{\"name\":\"Proceedings of the 12th IEEE International Conference on Fuzzy Systems (Cat. No.03CH37442)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 12th IEEE International Conference on Fuzzy Systems (Cat. No.03CH37442)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICM.2003.238612\",\"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 the 12th IEEE International Conference on Fuzzy Systems (Cat. No.03CH37442)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICM.2003.238612","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ant colony algorithm for evolutionary design of arithmetic circuits
Evolutionary computation is a new field of research in which hardware design is pursued by deriving inspiration from biological organisms. This new paradigm is expected to radically change the synthesis procedures in a way that allows discovering novel designs and/or more efficient circuits. In this paper, a multi objective optimization strategy for design of arithmetic circuits based on Ant Colony optimization algorithm is presented. Results are compared with those obtained using other techniques.
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