{"title":"随机进化:一类通用布局问题的快速有效的启发式算法","authors":"Y. Saab, V. Rao","doi":"10.1109/DAC.1990.114823","DOIUrl":null,"url":null,"abstract":"There are two canonical optimization problems, network bisectioning (NB) and traveling salesman (TS), that emerge from the physical design and layout of integrated circuits. An analogy is used between iterative techniques for combinatorial optimization and the evolution of biological species to obtain the stochastic evolution (SE) heuristic for solving a wide range of combinatorial optimization problems. It is shown that SE can be specifically tailored to solve both NB and TS. Experimental results for the NB and TS problems show that the SE algorithm produces better quality solutions and is faster than the simulated annealing algorithm in all instances considered.<<ETX>>","PeriodicalId":118552,"journal":{"name":"27th ACM/IEEE Design Automation Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"61","resultStr":"{\"title\":\"Stochastic evolution: a fast effective heuristic for some generic layout problems\",\"authors\":\"Y. Saab, V. Rao\",\"doi\":\"10.1109/DAC.1990.114823\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are two canonical optimization problems, network bisectioning (NB) and traveling salesman (TS), that emerge from the physical design and layout of integrated circuits. An analogy is used between iterative techniques for combinatorial optimization and the evolution of biological species to obtain the stochastic evolution (SE) heuristic for solving a wide range of combinatorial optimization problems. It is shown that SE can be specifically tailored to solve both NB and TS. Experimental results for the NB and TS problems show that the SE algorithm produces better quality solutions and is faster than the simulated annealing algorithm in all instances considered.<<ETX>>\",\"PeriodicalId\":118552,\"journal\":{\"name\":\"27th ACM/IEEE Design Automation Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"61\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"27th ACM/IEEE Design Automation Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DAC.1990.114823\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"27th ACM/IEEE Design Automation Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DAC.1990.114823","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stochastic evolution: a fast effective heuristic for some generic layout problems
There are two canonical optimization problems, network bisectioning (NB) and traveling salesman (TS), that emerge from the physical design and layout of integrated circuits. An analogy is used between iterative techniques for combinatorial optimization and the evolution of biological species to obtain the stochastic evolution (SE) heuristic for solving a wide range of combinatorial optimization problems. It is shown that SE can be specifically tailored to solve both NB and TS. Experimental results for the NB and TS problems show that the SE algorithm produces better quality solutions and is faster than the simulated annealing algorithm in all instances considered.<>
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