School-based optimization for performance-based optimum seismic design of steel frames
Abstract The performance-based optimum seismic design of steel frames is one of the most complicated and computationally demanding structural optimization problems. Metaheuristic optimization methods have been successfully used for solving engineering design problems over the last three decades. A v...
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Gespeichert in:
| Autor*in: |
Degertekin, S. O. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag London Ltd., part of Springer Nature 2020 |
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| Übergeordnetes Werk: |
Enthalten in: Engineering with computers - Springer London, 1985, 37(2020), 4 vom: 05. März, Seite 3283-3297 |
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| Übergeordnetes Werk: |
volume:37 ; year:2020 ; number:4 ; day:05 ; month:03 ; pages:3283-3297 |
| Links: |
|---|
| DOI / URN: |
10.1007/s00366-020-00993-1 |
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OLC2127713737 |
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| 520 | |a Abstract The performance-based optimum seismic design of steel frames is one of the most complicated and computationally demanding structural optimization problems. Metaheuristic optimization methods have been successfully used for solving engineering design problems over the last three decades. A very recently developed metaheuristic method called school-based optimization (SBO) will be utilized in the performance-based optimum seismic design of steel frames for the first time in this study. The SBO actually is an improved/enhanced version of teaching–learning-based optimization (TLBO), which mimics the teaching and learning process in a class where learners interact with the teacher and between themselves. Ad hoc strategies are adopted in order to minimize the computational cost of SBO results. The objective of the optimization problem is to minimize the weight of steel frames under interstory drift and strength constraints. Three steel frames previously designed by different metaheuristic methods including particle swarm optimization, improved quantum particle swarm optimization, firefly and modified firefly algorithms, teaching–learning-based optimization, and JAYA algorithm are used as benchmark optimization examples to verify the efficiency and robustness of the present SBO algorithm. Optimization results are compared with those of other state-of-the-art metaheuristic algorithms in terms of minimum structural weight, convergence speed, and several statistical parameters. Remarkably, in all test problems, SBO finds lighter designs with less computational effort than the TLBO and other methods available in metaheuristic optimization literature. | ||
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10.1007/s00366-020-00993-1 doi (DE-627)OLC2127713737 (DE-He213)s00366-020-00993-1-p DE-627 ger DE-627 rakwb eng 004 600 VZ Degertekin, S. O. verfasserin (orcid)0000-0001-8885-6468 aut School-based optimization for performance-based optimum seismic design of steel frames 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2020 Abstract The performance-based optimum seismic design of steel frames is one of the most complicated and computationally demanding structural optimization problems. Metaheuristic optimization methods have been successfully used for solving engineering design problems over the last three decades. A very recently developed metaheuristic method called school-based optimization (SBO) will be utilized in the performance-based optimum seismic design of steel frames for the first time in this study. The SBO actually is an improved/enhanced version of teaching–learning-based optimization (TLBO), which mimics the teaching and learning process in a class where learners interact with the teacher and between themselves. Ad hoc strategies are adopted in order to minimize the computational cost of SBO results. The objective of the optimization problem is to minimize the weight of steel frames under interstory drift and strength constraints. Three steel frames previously designed by different metaheuristic methods including particle swarm optimization, improved quantum particle swarm optimization, firefly and modified firefly algorithms, teaching–learning-based optimization, and JAYA algorithm are used as benchmark optimization examples to verify the efficiency and robustness of the present SBO algorithm. Optimization results are compared with those of other state-of-the-art metaheuristic algorithms in terms of minimum structural weight, convergence speed, and several statistical parameters. Remarkably, in all test problems, SBO finds lighter designs with less computational effort than the TLBO and other methods available in metaheuristic optimization literature. Performance-based design Pushover analysis Structural optimization Steel frames School-based optimization Tutar, H. (orcid)0000-0002-1440-7659 aut Lamberti, L. (orcid)0000-0002-9845-8786 aut Enthalten in Engineering with computers Springer London, 1985 37(2020), 4 vom: 05. März, Seite 3283-3297 (DE-627)129175404 (DE-600)51529-2 (DE-576)014455536 0177-0667 nnns volume:37 year:2020 number:4 day:05 month:03 pages:3283-3297 https://doi.org/10.1007/s00366-020-00993-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_2018 GBV_ILN_4277 AR 37 2020 4 05 03 3283-3297 |
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10.1007/s00366-020-00993-1 doi (DE-627)OLC2127713737 (DE-He213)s00366-020-00993-1-p DE-627 ger DE-627 rakwb eng 004 600 VZ Degertekin, S. O. verfasserin (orcid)0000-0001-8885-6468 aut School-based optimization for performance-based optimum seismic design of steel frames 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2020 Abstract The performance-based optimum seismic design of steel frames is one of the most complicated and computationally demanding structural optimization problems. Metaheuristic optimization methods have been successfully used for solving engineering design problems over the last three decades. A very recently developed metaheuristic method called school-based optimization (SBO) will be utilized in the performance-based optimum seismic design of steel frames for the first time in this study. The SBO actually is an improved/enhanced version of teaching–learning-based optimization (TLBO), which mimics the teaching and learning process in a class where learners interact with the teacher and between themselves. Ad hoc strategies are adopted in order to minimize the computational cost of SBO results. The objective of the optimization problem is to minimize the weight of steel frames under interstory drift and strength constraints. Three steel frames previously designed by different metaheuristic methods including particle swarm optimization, improved quantum particle swarm optimization, firefly and modified firefly algorithms, teaching–learning-based optimization, and JAYA algorithm are used as benchmark optimization examples to verify the efficiency and robustness of the present SBO algorithm. Optimization results are compared with those of other state-of-the-art metaheuristic algorithms in terms of minimum structural weight, convergence speed, and several statistical parameters. Remarkably, in all test problems, SBO finds lighter designs with less computational effort than the TLBO and other methods available in metaheuristic optimization literature. Performance-based design Pushover analysis Structural optimization Steel frames School-based optimization Tutar, H. (orcid)0000-0002-1440-7659 aut Lamberti, L. (orcid)0000-0002-9845-8786 aut Enthalten in Engineering with computers Springer London, 1985 37(2020), 4 vom: 05. März, Seite 3283-3297 (DE-627)129175404 (DE-600)51529-2 (DE-576)014455536 0177-0667 nnns volume:37 year:2020 number:4 day:05 month:03 pages:3283-3297 https://doi.org/10.1007/s00366-020-00993-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_2018 GBV_ILN_4277 AR 37 2020 4 05 03 3283-3297 |
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10.1007/s00366-020-00993-1 doi (DE-627)OLC2127713737 (DE-He213)s00366-020-00993-1-p DE-627 ger DE-627 rakwb eng 004 600 VZ Degertekin, S. O. verfasserin (orcid)0000-0001-8885-6468 aut School-based optimization for performance-based optimum seismic design of steel frames 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2020 Abstract The performance-based optimum seismic design of steel frames is one of the most complicated and computationally demanding structural optimization problems. Metaheuristic optimization methods have been successfully used for solving engineering design problems over the last three decades. A very recently developed metaheuristic method called school-based optimization (SBO) will be utilized in the performance-based optimum seismic design of steel frames for the first time in this study. The SBO actually is an improved/enhanced version of teaching–learning-based optimization (TLBO), which mimics the teaching and learning process in a class where learners interact with the teacher and between themselves. Ad hoc strategies are adopted in order to minimize the computational cost of SBO results. The objective of the optimization problem is to minimize the weight of steel frames under interstory drift and strength constraints. Three steel frames previously designed by different metaheuristic methods including particle swarm optimization, improved quantum particle swarm optimization, firefly and modified firefly algorithms, teaching–learning-based optimization, and JAYA algorithm are used as benchmark optimization examples to verify the efficiency and robustness of the present SBO algorithm. Optimization results are compared with those of other state-of-the-art metaheuristic algorithms in terms of minimum structural weight, convergence speed, and several statistical parameters. Remarkably, in all test problems, SBO finds lighter designs with less computational effort than the TLBO and other methods available in metaheuristic optimization literature. Performance-based design Pushover analysis Structural optimization Steel frames School-based optimization Tutar, H. (orcid)0000-0002-1440-7659 aut Lamberti, L. (orcid)0000-0002-9845-8786 aut Enthalten in Engineering with computers Springer London, 1985 37(2020), 4 vom: 05. März, Seite 3283-3297 (DE-627)129175404 (DE-600)51529-2 (DE-576)014455536 0177-0667 nnns volume:37 year:2020 number:4 day:05 month:03 pages:3283-3297 https://doi.org/10.1007/s00366-020-00993-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_2018 GBV_ILN_4277 AR 37 2020 4 05 03 3283-3297 |
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10.1007/s00366-020-00993-1 doi (DE-627)OLC2127713737 (DE-He213)s00366-020-00993-1-p DE-627 ger DE-627 rakwb eng 004 600 VZ Degertekin, S. O. verfasserin (orcid)0000-0001-8885-6468 aut School-based optimization for performance-based optimum seismic design of steel frames 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2020 Abstract The performance-based optimum seismic design of steel frames is one of the most complicated and computationally demanding structural optimization problems. Metaheuristic optimization methods have been successfully used for solving engineering design problems over the last three decades. A very recently developed metaheuristic method called school-based optimization (SBO) will be utilized in the performance-based optimum seismic design of steel frames for the first time in this study. The SBO actually is an improved/enhanced version of teaching–learning-based optimization (TLBO), which mimics the teaching and learning process in a class where learners interact with the teacher and between themselves. Ad hoc strategies are adopted in order to minimize the computational cost of SBO results. The objective of the optimization problem is to minimize the weight of steel frames under interstory drift and strength constraints. Three steel frames previously designed by different metaheuristic methods including particle swarm optimization, improved quantum particle swarm optimization, firefly and modified firefly algorithms, teaching–learning-based optimization, and JAYA algorithm are used as benchmark optimization examples to verify the efficiency and robustness of the present SBO algorithm. Optimization results are compared with those of other state-of-the-art metaheuristic algorithms in terms of minimum structural weight, convergence speed, and several statistical parameters. Remarkably, in all test problems, SBO finds lighter designs with less computational effort than the TLBO and other methods available in metaheuristic optimization literature. Performance-based design Pushover analysis Structural optimization Steel frames School-based optimization Tutar, H. (orcid)0000-0002-1440-7659 aut Lamberti, L. (orcid)0000-0002-9845-8786 aut Enthalten in Engineering with computers Springer London, 1985 37(2020), 4 vom: 05. März, Seite 3283-3297 (DE-627)129175404 (DE-600)51529-2 (DE-576)014455536 0177-0667 nnns volume:37 year:2020 number:4 day:05 month:03 pages:3283-3297 https://doi.org/10.1007/s00366-020-00993-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_2018 GBV_ILN_4277 AR 37 2020 4 05 03 3283-3297 |
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10.1007/s00366-020-00993-1 doi (DE-627)OLC2127713737 (DE-He213)s00366-020-00993-1-p DE-627 ger DE-627 rakwb eng 004 600 VZ Degertekin, S. O. verfasserin (orcid)0000-0001-8885-6468 aut School-based optimization for performance-based optimum seismic design of steel frames 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2020 Abstract The performance-based optimum seismic design of steel frames is one of the most complicated and computationally demanding structural optimization problems. Metaheuristic optimization methods have been successfully used for solving engineering design problems over the last three decades. A very recently developed metaheuristic method called school-based optimization (SBO) will be utilized in the performance-based optimum seismic design of steel frames for the first time in this study. The SBO actually is an improved/enhanced version of teaching–learning-based optimization (TLBO), which mimics the teaching and learning process in a class where learners interact with the teacher and between themselves. Ad hoc strategies are adopted in order to minimize the computational cost of SBO results. The objective of the optimization problem is to minimize the weight of steel frames under interstory drift and strength constraints. Three steel frames previously designed by different metaheuristic methods including particle swarm optimization, improved quantum particle swarm optimization, firefly and modified firefly algorithms, teaching–learning-based optimization, and JAYA algorithm are used as benchmark optimization examples to verify the efficiency and robustness of the present SBO algorithm. Optimization results are compared with those of other state-of-the-art metaheuristic algorithms in terms of minimum structural weight, convergence speed, and several statistical parameters. Remarkably, in all test problems, SBO finds lighter designs with less computational effort than the TLBO and other methods available in metaheuristic optimization literature. Performance-based design Pushover analysis Structural optimization Steel frames School-based optimization Tutar, H. (orcid)0000-0002-1440-7659 aut Lamberti, L. (orcid)0000-0002-9845-8786 aut Enthalten in Engineering with computers Springer London, 1985 37(2020), 4 vom: 05. März, Seite 3283-3297 (DE-627)129175404 (DE-600)51529-2 (DE-576)014455536 0177-0667 nnns volume:37 year:2020 number:4 day:05 month:03 pages:3283-3297 https://doi.org/10.1007/s00366-020-00993-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_2018 GBV_ILN_4277 AR 37 2020 4 05 03 3283-3297 |
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Degertekin, S. O. Tutar, H. Lamberti, L. |
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10.1007/s00366-020-00993-1 |
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school-based optimization for performance-based optimum seismic design of steel frames |
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School-based optimization for performance-based optimum seismic design of steel frames |
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Abstract The performance-based optimum seismic design of steel frames is one of the most complicated and computationally demanding structural optimization problems. Metaheuristic optimization methods have been successfully used for solving engineering design problems over the last three decades. A very recently developed metaheuristic method called school-based optimization (SBO) will be utilized in the performance-based optimum seismic design of steel frames for the first time in this study. The SBO actually is an improved/enhanced version of teaching–learning-based optimization (TLBO), which mimics the teaching and learning process in a class where learners interact with the teacher and between themselves. Ad hoc strategies are adopted in order to minimize the computational cost of SBO results. The objective of the optimization problem is to minimize the weight of steel frames under interstory drift and strength constraints. Three steel frames previously designed by different metaheuristic methods including particle swarm optimization, improved quantum particle swarm optimization, firefly and modified firefly algorithms, teaching–learning-based optimization, and JAYA algorithm are used as benchmark optimization examples to verify the efficiency and robustness of the present SBO algorithm. Optimization results are compared with those of other state-of-the-art metaheuristic algorithms in terms of minimum structural weight, convergence speed, and several statistical parameters. Remarkably, in all test problems, SBO finds lighter designs with less computational effort than the TLBO and other methods available in metaheuristic optimization literature. © Springer-Verlag London Ltd., part of Springer Nature 2020 |
| abstractGer |
Abstract The performance-based optimum seismic design of steel frames is one of the most complicated and computationally demanding structural optimization problems. Metaheuristic optimization methods have been successfully used for solving engineering design problems over the last three decades. A very recently developed metaheuristic method called school-based optimization (SBO) will be utilized in the performance-based optimum seismic design of steel frames for the first time in this study. The SBO actually is an improved/enhanced version of teaching–learning-based optimization (TLBO), which mimics the teaching and learning process in a class where learners interact with the teacher and between themselves. Ad hoc strategies are adopted in order to minimize the computational cost of SBO results. The objective of the optimization problem is to minimize the weight of steel frames under interstory drift and strength constraints. Three steel frames previously designed by different metaheuristic methods including particle swarm optimization, improved quantum particle swarm optimization, firefly and modified firefly algorithms, teaching–learning-based optimization, and JAYA algorithm are used as benchmark optimization examples to verify the efficiency and robustness of the present SBO algorithm. Optimization results are compared with those of other state-of-the-art metaheuristic algorithms in terms of minimum structural weight, convergence speed, and several statistical parameters. Remarkably, in all test problems, SBO finds lighter designs with less computational effort than the TLBO and other methods available in metaheuristic optimization literature. © Springer-Verlag London Ltd., part of Springer Nature 2020 |
| abstract_unstemmed |
Abstract The performance-based optimum seismic design of steel frames is one of the most complicated and computationally demanding structural optimization problems. Metaheuristic optimization methods have been successfully used for solving engineering design problems over the last three decades. A very recently developed metaheuristic method called school-based optimization (SBO) will be utilized in the performance-based optimum seismic design of steel frames for the first time in this study. The SBO actually is an improved/enhanced version of teaching–learning-based optimization (TLBO), which mimics the teaching and learning process in a class where learners interact with the teacher and between themselves. Ad hoc strategies are adopted in order to minimize the computational cost of SBO results. The objective of the optimization problem is to minimize the weight of steel frames under interstory drift and strength constraints. Three steel frames previously designed by different metaheuristic methods including particle swarm optimization, improved quantum particle swarm optimization, firefly and modified firefly algorithms, teaching–learning-based optimization, and JAYA algorithm are used as benchmark optimization examples to verify the efficiency and robustness of the present SBO algorithm. Optimization results are compared with those of other state-of-the-art metaheuristic algorithms in terms of minimum structural weight, convergence speed, and several statistical parameters. Remarkably, in all test problems, SBO finds lighter designs with less computational effort than the TLBO and other methods available in metaheuristic optimization literature. © Springer-Verlag London Ltd., part of Springer Nature 2020 |
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School-based optimization for performance-based optimum seismic design of steel frames |
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