{"title":"组合逻辑电路设计中的交叉笛卡尔遗传规划","authors":"J. E. H. D. Silva, H. Bernardino","doi":"10.1109/BRACIS.2018.00033","DOIUrl":null,"url":null,"abstract":"The development of an efficient crossover for Cartesian Genetic Programming (CGP) has been widely investigated, but there is not a large number of approaches using this type of operator when designing combinational logic circuits. In this paper, we introduce a new crossover for CGP when using a single genotype representation and the desired model has multiple outputs. The proposal modifies the standard evolutionary strategy commonly adopted in CGP by combining the subgraphs of the best outputs of the parent and its offspring in order to generate a new fittest individual. The proposed crossover is applied to combinational logic circuits with multiple outputs, a parameter analysis is performed, and the results obtained are compared to those found by a baseline CGP and other techniques from the literature.","PeriodicalId":405190,"journal":{"name":"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Cartesian Genetic Programming with Crossover for Designing Combinational Logic Circuits\",\"authors\":\"J. E. H. D. Silva, H. Bernardino\",\"doi\":\"10.1109/BRACIS.2018.00033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development of an efficient crossover for Cartesian Genetic Programming (CGP) has been widely investigated, but there is not a large number of approaches using this type of operator when designing combinational logic circuits. In this paper, we introduce a new crossover for CGP when using a single genotype representation and the desired model has multiple outputs. The proposal modifies the standard evolutionary strategy commonly adopted in CGP by combining the subgraphs of the best outputs of the parent and its offspring in order to generate a new fittest individual. The proposed crossover is applied to combinational logic circuits with multiple outputs, a parameter analysis is performed, and the results obtained are compared to those found by a baseline CGP and other techniques from the literature.\",\"PeriodicalId\":405190,\"journal\":{\"name\":\"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BRACIS.2018.00033\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BRACIS.2018.00033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cartesian Genetic Programming with Crossover for Designing Combinational Logic Circuits
The development of an efficient crossover for Cartesian Genetic Programming (CGP) has been widely investigated, but there is not a large number of approaches using this type of operator when designing combinational logic circuits. In this paper, we introduce a new crossover for CGP when using a single genotype representation and the desired model has multiple outputs. The proposal modifies the standard evolutionary strategy commonly adopted in CGP by combining the subgraphs of the best outputs of the parent and its offspring in order to generate a new fittest individual. The proposed crossover is applied to combinational logic circuits with multiple outputs, a parameter analysis is performed, and the results obtained are compared to those found by a baseline CGP and other techniques from the literature.