{"title":"基于粒子群优化技术的网表双分区","authors":"S. S. Gill, R. Chandel, A. Chandel","doi":"10.1504/IJAISC.2012.048178","DOIUrl":null,"url":null,"abstract":"In this paper circuit netlist bipartitioning using particle swarm optimisation technique is presented. Particle swarm optimisation is a powerful evolutionary computation technique for global search and optimisation. The circuit netlist is partitioned into two partitions such that the number of interconnections between the partitions (cutsize) is minimised. Results obtained show the versatility of the proposed soft computing method in solving non polynomial hard problems like circuit netlist partitioning.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Netlist bipartitioning using particle swarm optimisation technique\",\"authors\":\"S. S. Gill, R. Chandel, A. Chandel\",\"doi\":\"10.1504/IJAISC.2012.048178\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper circuit netlist bipartitioning using particle swarm optimisation technique is presented. Particle swarm optimisation is a powerful evolutionary computation technique for global search and optimisation. The circuit netlist is partitioned into two partitions such that the number of interconnections between the partitions (cutsize) is minimised. Results obtained show the versatility of the proposed soft computing method in solving non polynomial hard problems like circuit netlist partitioning.\",\"PeriodicalId\":364571,\"journal\":{\"name\":\"Int. J. Artif. Intell. Soft Comput.\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Artif. Intell. Soft Comput.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJAISC.2012.048178\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Artif. Intell. Soft Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJAISC.2012.048178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Netlist bipartitioning using particle swarm optimisation technique
In this paper circuit netlist bipartitioning using particle swarm optimisation technique is presented. Particle swarm optimisation is a powerful evolutionary computation technique for global search and optimisation. The circuit netlist is partitioned into two partitions such that the number of interconnections between the partitions (cutsize) is minimised. Results obtained show the versatility of the proposed soft computing method in solving non polynomial hard problems like circuit netlist partitioning.