{"title":"Implementation of Maximum Independent Set Problem by Algorithmic Tile Self-Assembly","authors":"Zhen Cheng, Jian-hua Xiao","doi":"10.1109/BIC-TA.2011.36","DOIUrl":null,"url":null,"abstract":"The maximum independent set problem is a classic combinational optimization problem. Recently, algorithmic tile self-assembly is considered as a promising technique in nanotechnology. In this work, we show how the tile self-assembly process is used to implement the maximum independent set problem including three small systems: nondeterministic guess system, AND operation system and comparing system. Our method can be successfully performed this problem in ¦¨(mn) steps parallely and at very low cost, here n and m is the number of vertices and edges of the given graph.","PeriodicalId":211822,"journal":{"name":"2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIC-TA.2011.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The maximum independent set problem is a classic combinational optimization problem. Recently, algorithmic tile self-assembly is considered as a promising technique in nanotechnology. In this work, we show how the tile self-assembly process is used to implement the maximum independent set problem including three small systems: nondeterministic guess system, AND operation system and comparing system. Our method can be successfully performed this problem in ¦¨(mn) steps parallely and at very low cost, here n and m is the number of vertices and edges of the given graph.