{"title":"大规模并行花授粉算法","authors":"Szilárd Nagy, K. Jármai","doi":"10.26649/musci.2019.048","DOIUrl":null,"url":null,"abstract":"An evolutionary optimization is an efficient tool, but time-consuming for optimizing non-linear and multi-dimensional problems. We propose a SIMD transformation for flower pollination algorithm and function to be optimized. The method was tested with standard test function, and the proportion of runtime in the sequential case and parallel case was examined.","PeriodicalId":340250,"journal":{"name":"MultiScience - XXXIII. microCAD International Multidisciplinary Scientific Conference","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Massively Parallel Flower Pollination Algorithm\",\"authors\":\"Szilárd Nagy, K. Jármai\",\"doi\":\"10.26649/musci.2019.048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An evolutionary optimization is an efficient tool, but time-consuming for optimizing non-linear and multi-dimensional problems. We propose a SIMD transformation for flower pollination algorithm and function to be optimized. The method was tested with standard test function, and the proportion of runtime in the sequential case and parallel case was examined.\",\"PeriodicalId\":340250,\"journal\":{\"name\":\"MultiScience - XXXIII. microCAD International Multidisciplinary Scientific Conference\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MultiScience - XXXIII. microCAD International Multidisciplinary Scientific Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26649/musci.2019.048\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MultiScience - XXXIII. microCAD International Multidisciplinary Scientific Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26649/musci.2019.048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An evolutionary optimization is an efficient tool, but time-consuming for optimizing non-linear and multi-dimensional problems. We propose a SIMD transformation for flower pollination algorithm and function to be optimized. The method was tested with standard test function, and the proportion of runtime in the sequential case and parallel case was examined.