D. Prayogo, H. Santoso, Franky Budiman, Marcellino Jason
{"title":"采用元启发式算法的钢框架布局、拓扑和尺寸优化:比较研究","authors":"D. Prayogo, H. Santoso, Franky Budiman, Marcellino Jason","doi":"10.9744/ced.24.1.31-37","DOIUrl":null,"url":null,"abstract":"Determining the topology, layout, and size of structural elements is one of the most important aspects in designing steel seismic-resistant structures. Optimization of these parameters is beneficial to find the lightest weight of the structure, thus reducing construction cost. This study compares the performance of three metaheuristic algorithms, namely, Particle Swarm Optimization (PSO), Symbiotic Organisms Search (SOS), and Differential Evolution (DE). Three study cases are used in order to find the lightest structural weight without violating constraints based on SNI 1726:2019, SNI 1729:2020, and SNI 7860:2020. The results of this study show that SOS has better performance than other algorithms.","PeriodicalId":30107,"journal":{"name":"Civil Engineering Dimension","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Layout, Topology, and Size Optimization of Steel Frame Design Using Metaheuristic Algorithms: A Comparative Study\",\"authors\":\"D. Prayogo, H. Santoso, Franky Budiman, Marcellino Jason\",\"doi\":\"10.9744/ced.24.1.31-37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Determining the topology, layout, and size of structural elements is one of the most important aspects in designing steel seismic-resistant structures. Optimization of these parameters is beneficial to find the lightest weight of the structure, thus reducing construction cost. This study compares the performance of three metaheuristic algorithms, namely, Particle Swarm Optimization (PSO), Symbiotic Organisms Search (SOS), and Differential Evolution (DE). Three study cases are used in order to find the lightest structural weight without violating constraints based on SNI 1726:2019, SNI 1729:2020, and SNI 7860:2020. The results of this study show that SOS has better performance than other algorithms.\",\"PeriodicalId\":30107,\"journal\":{\"name\":\"Civil Engineering Dimension\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Civil Engineering Dimension\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9744/ced.24.1.31-37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Civil Engineering Dimension","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9744/ced.24.1.31-37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Layout, Topology, and Size Optimization of Steel Frame Design Using Metaheuristic Algorithms: A Comparative Study
Determining the topology, layout, and size of structural elements is one of the most important aspects in designing steel seismic-resistant structures. Optimization of these parameters is beneficial to find the lightest weight of the structure, thus reducing construction cost. This study compares the performance of three metaheuristic algorithms, namely, Particle Swarm Optimization (PSO), Symbiotic Organisms Search (SOS), and Differential Evolution (DE). Three study cases are used in order to find the lightest structural weight without violating constraints based on SNI 1726:2019, SNI 1729:2020, and SNI 7860:2020. The results of this study show that SOS has better performance than other algorithms.