João Fabrício Filho, Luis Gustavo Araujo Rodriguez, A. F. Silva
{"title":"寻找优化序列的进化算法:建议与实验","authors":"João Fabrício Filho, Luis Gustavo Araujo Rodriguez, A. F. Silva","doi":"10.1504/ijcse.2020.10027432","DOIUrl":null,"url":null,"abstract":"Evolutionary algorithms are metaheuristics for solving combinatorial and optimisation problems. A combinatorial problem, important in the context of software development, consists of selecting code transformations that must be utilised by the compiler while generating the target code. The objective of this paper is to propose and evaluate an evolutionary algorithm that is capable of finding an efficient sequence of optimising transformations, which will be used while generating the target code. The results indicate that it is efficient to find good transformation sequences, and a good option to generate databases for machine learning systems.","PeriodicalId":340410,"journal":{"name":"Int. J. Comput. Sci. Eng.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An evolutionary algorithm for finding optimisation sequences: proposal and experiments\",\"authors\":\"João Fabrício Filho, Luis Gustavo Araujo Rodriguez, A. F. Silva\",\"doi\":\"10.1504/ijcse.2020.10027432\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Evolutionary algorithms are metaheuristics for solving combinatorial and optimisation problems. A combinatorial problem, important in the context of software development, consists of selecting code transformations that must be utilised by the compiler while generating the target code. The objective of this paper is to propose and evaluate an evolutionary algorithm that is capable of finding an efficient sequence of optimising transformations, which will be used while generating the target code. The results indicate that it is efficient to find good transformation sequences, and a good option to generate databases for machine learning systems.\",\"PeriodicalId\":340410,\"journal\":{\"name\":\"Int. J. Comput. Sci. Eng.\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Comput. Sci. Eng.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijcse.2020.10027432\",\"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. Comput. Sci. Eng.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijcse.2020.10027432","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An evolutionary algorithm for finding optimisation sequences: proposal and experiments
Evolutionary algorithms are metaheuristics for solving combinatorial and optimisation problems. A combinatorial problem, important in the context of software development, consists of selecting code transformations that must be utilised by the compiler while generating the target code. The objective of this paper is to propose and evaluate an evolutionary algorithm that is capable of finding an efficient sequence of optimising transformations, which will be used while generating the target code. The results indicate that it is efficient to find good transformation sequences, and a good option to generate databases for machine learning systems.