An improved multi-objective optimization approach for performance-based design of structures using nonlinear time-history analyses
Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant r...
Ausführliche Beschreibung
Autor*in: |
Mokarram, Vahid [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2018transfer abstract |
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Umfang: |
19 |
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Übergeordnetes Werk: |
Enthalten in: Atomic collapse in graphene quantum dots in a magnetic field - Eren, I. ELSEVIER, 2022, the official journal of the World Federation on Soft Computing (WFSC), Amsterdam [u.a.] |
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Übergeordnetes Werk: |
volume:73 ; year:2018 ; pages:647-665 ; extent:19 |
Links: |
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DOI / URN: |
10.1016/j.asoc.2018.08.048 |
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Katalog-ID: |
ELV04488172X |
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520 | |a Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. | ||
520 | |a Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. | ||
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10.1016/j.asoc.2018.08.048 doi GBV00000000000447.pica (DE-627)ELV04488172X (ELSEVIER)S1568-4946(18)30526-X DE-627 ger DE-627 rakwb eng 540 530 VZ 33.00 bkl Mokarram, Vahid verfasserin aut An improved multi-objective optimization approach for performance-based design of structures using nonlinear time-history analyses 2018transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. DI Elsevier IDA Elsevier LS Elsevier MDOF Elsevier SDOF Elsevier PBD Elsevier RBF Elsevier DOF Elsevier MOEA Elsevier NDP Elsevier NTHA Elsevier CSM Elsevier EA Elsevier OP Elsevier IO Elsevier SMRF Elsevier NSP Elsevier CP Elsevier LCC Elsevier PSO Elsevier MOP Elsevier PA Elsevier RC Elsevier FEMA Elsevier SOP Elsevier PH Elsevier FC-MOPSO Elsevier MPA Elsevier Banan, Mohammad Reza oth Enthalten in Elsevier Science Eren, I. ELSEVIER Atomic collapse in graphene quantum dots in a magnetic field 2022 the official journal of the World Federation on Soft Computing (WFSC) Amsterdam [u.a.] (DE-627)ELV007866305 volume:73 year:2018 pages:647-665 extent:19 https://doi.org/10.1016/j.asoc.2018.08.048 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 73 2018 647-665 19 |
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10.1016/j.asoc.2018.08.048 doi GBV00000000000447.pica (DE-627)ELV04488172X (ELSEVIER)S1568-4946(18)30526-X DE-627 ger DE-627 rakwb eng 540 530 VZ 33.00 bkl Mokarram, Vahid verfasserin aut An improved multi-objective optimization approach for performance-based design of structures using nonlinear time-history analyses 2018transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. DI Elsevier IDA Elsevier LS Elsevier MDOF Elsevier SDOF Elsevier PBD Elsevier RBF Elsevier DOF Elsevier MOEA Elsevier NDP Elsevier NTHA Elsevier CSM Elsevier EA Elsevier OP Elsevier IO Elsevier SMRF Elsevier NSP Elsevier CP Elsevier LCC Elsevier PSO Elsevier MOP Elsevier PA Elsevier RC Elsevier FEMA Elsevier SOP Elsevier PH Elsevier FC-MOPSO Elsevier MPA Elsevier Banan, Mohammad Reza oth Enthalten in Elsevier Science Eren, I. ELSEVIER Atomic collapse in graphene quantum dots in a magnetic field 2022 the official journal of the World Federation on Soft Computing (WFSC) Amsterdam [u.a.] (DE-627)ELV007866305 volume:73 year:2018 pages:647-665 extent:19 https://doi.org/10.1016/j.asoc.2018.08.048 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 73 2018 647-665 19 |
allfields_unstemmed |
10.1016/j.asoc.2018.08.048 doi GBV00000000000447.pica (DE-627)ELV04488172X (ELSEVIER)S1568-4946(18)30526-X DE-627 ger DE-627 rakwb eng 540 530 VZ 33.00 bkl Mokarram, Vahid verfasserin aut An improved multi-objective optimization approach for performance-based design of structures using nonlinear time-history analyses 2018transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. DI Elsevier IDA Elsevier LS Elsevier MDOF Elsevier SDOF Elsevier PBD Elsevier RBF Elsevier DOF Elsevier MOEA Elsevier NDP Elsevier NTHA Elsevier CSM Elsevier EA Elsevier OP Elsevier IO Elsevier SMRF Elsevier NSP Elsevier CP Elsevier LCC Elsevier PSO Elsevier MOP Elsevier PA Elsevier RC Elsevier FEMA Elsevier SOP Elsevier PH Elsevier FC-MOPSO Elsevier MPA Elsevier Banan, Mohammad Reza oth Enthalten in Elsevier Science Eren, I. ELSEVIER Atomic collapse in graphene quantum dots in a magnetic field 2022 the official journal of the World Federation on Soft Computing (WFSC) Amsterdam [u.a.] (DE-627)ELV007866305 volume:73 year:2018 pages:647-665 extent:19 https://doi.org/10.1016/j.asoc.2018.08.048 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 73 2018 647-665 19 |
allfieldsGer |
10.1016/j.asoc.2018.08.048 doi GBV00000000000447.pica (DE-627)ELV04488172X (ELSEVIER)S1568-4946(18)30526-X DE-627 ger DE-627 rakwb eng 540 530 VZ 33.00 bkl Mokarram, Vahid verfasserin aut An improved multi-objective optimization approach for performance-based design of structures using nonlinear time-history analyses 2018transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. DI Elsevier IDA Elsevier LS Elsevier MDOF Elsevier SDOF Elsevier PBD Elsevier RBF Elsevier DOF Elsevier MOEA Elsevier NDP Elsevier NTHA Elsevier CSM Elsevier EA Elsevier OP Elsevier IO Elsevier SMRF Elsevier NSP Elsevier CP Elsevier LCC Elsevier PSO Elsevier MOP Elsevier PA Elsevier RC Elsevier FEMA Elsevier SOP Elsevier PH Elsevier FC-MOPSO Elsevier MPA Elsevier Banan, Mohammad Reza oth Enthalten in Elsevier Science Eren, I. ELSEVIER Atomic collapse in graphene quantum dots in a magnetic field 2022 the official journal of the World Federation on Soft Computing (WFSC) Amsterdam [u.a.] (DE-627)ELV007866305 volume:73 year:2018 pages:647-665 extent:19 https://doi.org/10.1016/j.asoc.2018.08.048 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 73 2018 647-665 19 |
allfieldsSound |
10.1016/j.asoc.2018.08.048 doi GBV00000000000447.pica (DE-627)ELV04488172X (ELSEVIER)S1568-4946(18)30526-X DE-627 ger DE-627 rakwb eng 540 530 VZ 33.00 bkl Mokarram, Vahid verfasserin aut An improved multi-objective optimization approach for performance-based design of structures using nonlinear time-history analyses 2018transfer abstract 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. DI Elsevier IDA Elsevier LS Elsevier MDOF Elsevier SDOF Elsevier PBD Elsevier RBF Elsevier DOF Elsevier MOEA Elsevier NDP Elsevier NTHA Elsevier CSM Elsevier EA Elsevier OP Elsevier IO Elsevier SMRF Elsevier NSP Elsevier CP Elsevier LCC Elsevier PSO Elsevier MOP Elsevier PA Elsevier RC Elsevier FEMA Elsevier SOP Elsevier PH Elsevier FC-MOPSO Elsevier MPA Elsevier Banan, Mohammad Reza oth Enthalten in Elsevier Science Eren, I. ELSEVIER Atomic collapse in graphene quantum dots in a magnetic field 2022 the official journal of the World Federation on Soft Computing (WFSC) Amsterdam [u.a.] (DE-627)ELV007866305 volume:73 year:2018 pages:647-665 extent:19 https://doi.org/10.1016/j.asoc.2018.08.048 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 73 2018 647-665 19 |
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An improved multi-objective optimization approach for performance-based design of structures using nonlinear time-history analyses |
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Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. |
abstractGer |
Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. |
abstract_unstemmed |
Performance-based design (PBD) of buildings can be properly addressed in a multi-objective optimization framework. However, computational costs of such an approach will be very expensive especially if nonlinear time-history analysis (NTHA) is used as the evaluation tool. In this paper, significant reductions in computational costs of solving structural multi-objective optimization problems is achieved by proposing a new metaheuristic surrogate model called Surrogate FC-MOPSO. In this method, which is an extension of FC-MOPSO algorithm, NTHA and pushover analysis (PA) are simultaneously employed for evaluating system responses. PAs are adopted as an approximation tool in the surrogate model while the responses corresponding to feasible solutions are always evaluated from NTHAs. The final Pareto optimal solutions, which yield tradeoffs between initial and life-cycle costs (LCCs), are already evaluated based on NTHAs. It is shown that application of the proposed method results in substantial reductions of runtime of the considered problems. It is also demonstrated that adopting PAs as the only evaluation tool in optimal performance-based design of structures can result in unreliable solutions. |
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