Multiobjective optimization for modular unit production lines focusing on crew allocation and production performance
A flexible production duration is necessary because of the increase in the demand for modular construction; further, the benefits of modular construction, such as reduced duration and labor requirement, are also considered important. Such construction requires various production line design alternat...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Hyun, Hosang [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2021transfer abstract |
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| Übergeordnetes Werk: |
Enthalten in: Biosensors: A novel approach to and recent discovery in detection of cytokines - Mobed, Ahmad ELSEVIER, 2020, an international research journal, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:125 ; year:2021 ; pages:0 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.autcon.2021.103581 |
|---|
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ELV053839927 |
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| 520 | |a A flexible production duration is necessary because of the increase in the demand for modular construction; further, the benefits of modular construction, such as reduced duration and labor requirement, are also considered important. Such construction requires various production line design alternatives that consider the benefits with equal priority. To address this issue, a multiobjective optimization model for modular unit production line (MOMUPL) was developed based on a genetic algorithm. To this end, differences between unit production line design and scheduling methods in the manufacturing industry were identified. Then, to rank solutions in optimization processes, the nondominated sorting genetic algorithm II (NSGA-II) was applied to the model. The MOMUPL suggests various optimization results, thereby allowing the project manager to select a solution based on specific project characteristics. Therefore, using MOMUPL, the duration for scheduling is expected to be reduced along with a reduction in project labor cost and duration. | ||
| 520 | |a A flexible production duration is necessary because of the increase in the demand for modular construction; further, the benefits of modular construction, such as reduced duration and labor requirement, are also considered important. Such construction requires various production line design alternatives that consider the benefits with equal priority. To address this issue, a multiobjective optimization model for modular unit production line (MOMUPL) was developed based on a genetic algorithm. To this end, differences between unit production line design and scheduling methods in the manufacturing industry were identified. Then, to rank solutions in optimization processes, the nondominated sorting genetic algorithm II (NSGA-II) was applied to the model. The MOMUPL suggests various optimization results, thereby allowing the project manager to select a solution based on specific project characteristics. Therefore, using MOMUPL, the duration for scheduling is expected to be reduced along with a reduction in project labor cost and duration. | ||
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10.1016/j.autcon.2021.103581 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001490.pica (DE-627)ELV053839927 (ELSEVIER)S0926-5805(21)00032-7 DE-627 ger DE-627 rakwb eng 570 VZ BIODIV DE-30 fid 44.00 bkl Hyun, Hosang verfasserin aut Multiobjective optimization for modular unit production lines focusing on crew allocation and production performance 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A flexible production duration is necessary because of the increase in the demand for modular construction; further, the benefits of modular construction, such as reduced duration and labor requirement, are also considered important. Such construction requires various production line design alternatives that consider the benefits with equal priority. To address this issue, a multiobjective optimization model for modular unit production line (MOMUPL) was developed based on a genetic algorithm. To this end, differences between unit production line design and scheduling methods in the manufacturing industry were identified. Then, to rank solutions in optimization processes, the nondominated sorting genetic algorithm II (NSGA-II) was applied to the model. The MOMUPL suggests various optimization results, thereby allowing the project manager to select a solution based on specific project characteristics. Therefore, using MOMUPL, the duration for scheduling is expected to be reduced along with a reduction in project labor cost and duration. A flexible production duration is necessary because of the increase in the demand for modular construction; further, the benefits of modular construction, such as reduced duration and labor requirement, are also considered important. Such construction requires various production line design alternatives that consider the benefits with equal priority. To address this issue, a multiobjective optimization model for modular unit production line (MOMUPL) was developed based on a genetic algorithm. To this end, differences between unit production line design and scheduling methods in the manufacturing industry were identified. Then, to rank solutions in optimization processes, the nondominated sorting genetic algorithm II (NSGA-II) was applied to the model. The MOMUPL suggests various optimization results, thereby allowing the project manager to select a solution based on specific project characteristics. Therefore, using MOMUPL, the duration for scheduling is expected to be reduced along with a reduction in project labor cost and duration. Yoon, Inseok oth Lee, Hyun-Soo oth Park, Moonseo oth Lee, Jeonghoon oth Enthalten in Elsevier Science Publ Mobed, Ahmad ELSEVIER Biosensors: A novel approach to and recent discovery in detection of cytokines 2020 an international research journal Amsterdam [u.a.] (DE-627)ELV004774973 volume:125 year:2021 pages:0 https://doi.org/10.1016/j.autcon.2021.103581 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 125 2021 0 |
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10.1016/j.autcon.2021.103581 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001490.pica (DE-627)ELV053839927 (ELSEVIER)S0926-5805(21)00032-7 DE-627 ger DE-627 rakwb eng 570 VZ BIODIV DE-30 fid 44.00 bkl Hyun, Hosang verfasserin aut Multiobjective optimization for modular unit production lines focusing on crew allocation and production performance 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A flexible production duration is necessary because of the increase in the demand for modular construction; further, the benefits of modular construction, such as reduced duration and labor requirement, are also considered important. Such construction requires various production line design alternatives that consider the benefits with equal priority. To address this issue, a multiobjective optimization model for modular unit production line (MOMUPL) was developed based on a genetic algorithm. To this end, differences between unit production line design and scheduling methods in the manufacturing industry were identified. Then, to rank solutions in optimization processes, the nondominated sorting genetic algorithm II (NSGA-II) was applied to the model. The MOMUPL suggests various optimization results, thereby allowing the project manager to select a solution based on specific project characteristics. Therefore, using MOMUPL, the duration for scheduling is expected to be reduced along with a reduction in project labor cost and duration. A flexible production duration is necessary because of the increase in the demand for modular construction; further, the benefits of modular construction, such as reduced duration and labor requirement, are also considered important. Such construction requires various production line design alternatives that consider the benefits with equal priority. To address this issue, a multiobjective optimization model for modular unit production line (MOMUPL) was developed based on a genetic algorithm. To this end, differences between unit production line design and scheduling methods in the manufacturing industry were identified. Then, to rank solutions in optimization processes, the nondominated sorting genetic algorithm II (NSGA-II) was applied to the model. The MOMUPL suggests various optimization results, thereby allowing the project manager to select a solution based on specific project characteristics. Therefore, using MOMUPL, the duration for scheduling is expected to be reduced along with a reduction in project labor cost and duration. Yoon, Inseok oth Lee, Hyun-Soo oth Park, Moonseo oth Lee, Jeonghoon oth Enthalten in Elsevier Science Publ Mobed, Ahmad ELSEVIER Biosensors: A novel approach to and recent discovery in detection of cytokines 2020 an international research journal Amsterdam [u.a.] (DE-627)ELV004774973 volume:125 year:2021 pages:0 https://doi.org/10.1016/j.autcon.2021.103581 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 125 2021 0 |
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10.1016/j.autcon.2021.103581 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001490.pica (DE-627)ELV053839927 (ELSEVIER)S0926-5805(21)00032-7 DE-627 ger DE-627 rakwb eng 570 VZ BIODIV DE-30 fid 44.00 bkl Hyun, Hosang verfasserin aut Multiobjective optimization for modular unit production lines focusing on crew allocation and production performance 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A flexible production duration is necessary because of the increase in the demand for modular construction; further, the benefits of modular construction, such as reduced duration and labor requirement, are also considered important. Such construction requires various production line design alternatives that consider the benefits with equal priority. To address this issue, a multiobjective optimization model for modular unit production line (MOMUPL) was developed based on a genetic algorithm. To this end, differences between unit production line design and scheduling methods in the manufacturing industry were identified. Then, to rank solutions in optimization processes, the nondominated sorting genetic algorithm II (NSGA-II) was applied to the model. The MOMUPL suggests various optimization results, thereby allowing the project manager to select a solution based on specific project characteristics. Therefore, using MOMUPL, the duration for scheduling is expected to be reduced along with a reduction in project labor cost and duration. A flexible production duration is necessary because of the increase in the demand for modular construction; further, the benefits of modular construction, such as reduced duration and labor requirement, are also considered important. Such construction requires various production line design alternatives that consider the benefits with equal priority. To address this issue, a multiobjective optimization model for modular unit production line (MOMUPL) was developed based on a genetic algorithm. To this end, differences between unit production line design and scheduling methods in the manufacturing industry were identified. Then, to rank solutions in optimization processes, the nondominated sorting genetic algorithm II (NSGA-II) was applied to the model. The MOMUPL suggests various optimization results, thereby allowing the project manager to select a solution based on specific project characteristics. Therefore, using MOMUPL, the duration for scheduling is expected to be reduced along with a reduction in project labor cost and duration. Yoon, Inseok oth Lee, Hyun-Soo oth Park, Moonseo oth Lee, Jeonghoon oth Enthalten in Elsevier Science Publ Mobed, Ahmad ELSEVIER Biosensors: A novel approach to and recent discovery in detection of cytokines 2020 an international research journal Amsterdam [u.a.] (DE-627)ELV004774973 volume:125 year:2021 pages:0 https://doi.org/10.1016/j.autcon.2021.103581 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 125 2021 0 |
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Multiobjective optimization for modular unit production lines focusing on crew allocation and production performance |
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Multiobjective optimization for modular unit production lines focusing on crew allocation and production performance |
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Hyun, Hosang |
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Biosensors: A novel approach to and recent discovery in detection of cytokines |
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Biosensors: A novel approach to and recent discovery in detection of cytokines |
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10.1016/j.autcon.2021.103581 |
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multiobjective optimization for modular unit production lines focusing on crew allocation and production performance |
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Multiobjective optimization for modular unit production lines focusing on crew allocation and production performance |
| abstract |
A flexible production duration is necessary because of the increase in the demand for modular construction; further, the benefits of modular construction, such as reduced duration and labor requirement, are also considered important. Such construction requires various production line design alternatives that consider the benefits with equal priority. To address this issue, a multiobjective optimization model for modular unit production line (MOMUPL) was developed based on a genetic algorithm. To this end, differences between unit production line design and scheduling methods in the manufacturing industry were identified. Then, to rank solutions in optimization processes, the nondominated sorting genetic algorithm II (NSGA-II) was applied to the model. The MOMUPL suggests various optimization results, thereby allowing the project manager to select a solution based on specific project characteristics. Therefore, using MOMUPL, the duration for scheduling is expected to be reduced along with a reduction in project labor cost and duration. |
| abstractGer |
A flexible production duration is necessary because of the increase in the demand for modular construction; further, the benefits of modular construction, such as reduced duration and labor requirement, are also considered important. Such construction requires various production line design alternatives that consider the benefits with equal priority. To address this issue, a multiobjective optimization model for modular unit production line (MOMUPL) was developed based on a genetic algorithm. To this end, differences between unit production line design and scheduling methods in the manufacturing industry were identified. Then, to rank solutions in optimization processes, the nondominated sorting genetic algorithm II (NSGA-II) was applied to the model. The MOMUPL suggests various optimization results, thereby allowing the project manager to select a solution based on specific project characteristics. Therefore, using MOMUPL, the duration for scheduling is expected to be reduced along with a reduction in project labor cost and duration. |
| abstract_unstemmed |
A flexible production duration is necessary because of the increase in the demand for modular construction; further, the benefits of modular construction, such as reduced duration and labor requirement, are also considered important. Such construction requires various production line design alternatives that consider the benefits with equal priority. To address this issue, a multiobjective optimization model for modular unit production line (MOMUPL) was developed based on a genetic algorithm. To this end, differences between unit production line design and scheduling methods in the manufacturing industry were identified. Then, to rank solutions in optimization processes, the nondominated sorting genetic algorithm II (NSGA-II) was applied to the model. The MOMUPL suggests various optimization results, thereby allowing the project manager to select a solution based on specific project characteristics. Therefore, using MOMUPL, the duration for scheduling is expected to be reduced along with a reduction in project labor cost and duration. |
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Multiobjective optimization for modular unit production lines focusing on crew allocation and production performance |
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https://doi.org/10.1016/j.autcon.2021.103581 |
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Yoon, Inseok Lee, Hyun-Soo Park, Moonseo Lee, Jeonghoon |
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