A hybrid genetic algorithm approach to mixed-model assembly line balancing
Abstract Assembly line balancing has been a focus of interest to academics in operation management for the last four decades. Mass production has saved huge costs for manufacturers in various industries for some time. With the growing trend of greater product variability and shorter life cycles, tra...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Noorul Haq, A. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2005 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag 2005 |
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| Übergeordnetes Werk: |
Enthalten in: The international journal of advanced manufacturing technology - Springer-Verlag, 1985, 28(2005), 3-4 vom: 20. Apr., Seite 337-341 |
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volume:28 ; year:2005 ; number:3-4 ; day:20 ; month:04 ; pages:337-341 |
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10.1007/s00170-004-2373-3 |
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10.1007/s00170-004-2373-3 doi (DE-627)OLC2026005753 (DE-He213)s00170-004-2373-3-p DE-627 ger DE-627 rakwb eng 670 VZ Noorul Haq, A. verfasserin aut A hybrid genetic algorithm approach to mixed-model assembly line balancing 2005 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2005 Abstract Assembly line balancing has been a focus of interest to academics in operation management for the last four decades. Mass production has saved huge costs for manufacturers in various industries for some time. With the growing trend of greater product variability and shorter life cycles, traditional mass production is being replaced in assembly lines. The current market is intensely competitive and consumer-centric. Mixed-model assembly lines are increasing in many industrial environments. This study deals with mixed-model assembly line balancing for n models, and uses a classical genetic algorithm approach to minimize the number of workstations. We also incorporated a hybrid genetic algorithm approach that used the solution from the modified ranked positional method for the initial solution to reduce the search space within the global space, thereby reducing search time. Several examples illustrate the approach. The software used for programming is C++ language . Genetic algorithm Hybrid algorithm Mixed-model assembly line balancing Rengarajan, K. aut Jayaprakash, J. aut Enthalten in The international journal of advanced manufacturing technology Springer-Verlag, 1985 28(2005), 3-4 vom: 20. Apr., Seite 337-341 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:28 year:2005 number:3-4 day:20 month:04 pages:337-341 https://doi.org/10.1007/s00170-004-2373-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_20 GBV_ILN_21 GBV_ILN_70 GBV_ILN_150 GBV_ILN_2006 GBV_ILN_2014 GBV_ILN_2018 GBV_ILN_2241 GBV_ILN_2333 GBV_ILN_4046 GBV_ILN_4277 GBV_ILN_4307 AR 28 2005 3-4 20 04 337-341 |
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10.1007/s00170-004-2373-3 doi (DE-627)OLC2026005753 (DE-He213)s00170-004-2373-3-p DE-627 ger DE-627 rakwb eng 670 VZ Noorul Haq, A. verfasserin aut A hybrid genetic algorithm approach to mixed-model assembly line balancing 2005 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2005 Abstract Assembly line balancing has been a focus of interest to academics in operation management for the last four decades. Mass production has saved huge costs for manufacturers in various industries for some time. With the growing trend of greater product variability and shorter life cycles, traditional mass production is being replaced in assembly lines. The current market is intensely competitive and consumer-centric. Mixed-model assembly lines are increasing in many industrial environments. This study deals with mixed-model assembly line balancing for n models, and uses a classical genetic algorithm approach to minimize the number of workstations. We also incorporated a hybrid genetic algorithm approach that used the solution from the modified ranked positional method for the initial solution to reduce the search space within the global space, thereby reducing search time. Several examples illustrate the approach. The software used for programming is C++ language . Genetic algorithm Hybrid algorithm Mixed-model assembly line balancing Rengarajan, K. aut Jayaprakash, J. aut Enthalten in The international journal of advanced manufacturing technology Springer-Verlag, 1985 28(2005), 3-4 vom: 20. Apr., Seite 337-341 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:28 year:2005 number:3-4 day:20 month:04 pages:337-341 https://doi.org/10.1007/s00170-004-2373-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_20 GBV_ILN_21 GBV_ILN_70 GBV_ILN_150 GBV_ILN_2006 GBV_ILN_2014 GBV_ILN_2018 GBV_ILN_2241 GBV_ILN_2333 GBV_ILN_4046 GBV_ILN_4277 GBV_ILN_4307 AR 28 2005 3-4 20 04 337-341 |
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10.1007/s00170-004-2373-3 doi (DE-627)OLC2026005753 (DE-He213)s00170-004-2373-3-p DE-627 ger DE-627 rakwb eng 670 VZ Noorul Haq, A. verfasserin aut A hybrid genetic algorithm approach to mixed-model assembly line balancing 2005 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2005 Abstract Assembly line balancing has been a focus of interest to academics in operation management for the last four decades. Mass production has saved huge costs for manufacturers in various industries for some time. With the growing trend of greater product variability and shorter life cycles, traditional mass production is being replaced in assembly lines. The current market is intensely competitive and consumer-centric. Mixed-model assembly lines are increasing in many industrial environments. This study deals with mixed-model assembly line balancing for n models, and uses a classical genetic algorithm approach to minimize the number of workstations. We also incorporated a hybrid genetic algorithm approach that used the solution from the modified ranked positional method for the initial solution to reduce the search space within the global space, thereby reducing search time. Several examples illustrate the approach. The software used for programming is C++ language . Genetic algorithm Hybrid algorithm Mixed-model assembly line balancing Rengarajan, K. aut Jayaprakash, J. aut Enthalten in The international journal of advanced manufacturing technology Springer-Verlag, 1985 28(2005), 3-4 vom: 20. Apr., Seite 337-341 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:28 year:2005 number:3-4 day:20 month:04 pages:337-341 https://doi.org/10.1007/s00170-004-2373-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_20 GBV_ILN_21 GBV_ILN_70 GBV_ILN_150 GBV_ILN_2006 GBV_ILN_2014 GBV_ILN_2018 GBV_ILN_2241 GBV_ILN_2333 GBV_ILN_4046 GBV_ILN_4277 GBV_ILN_4307 AR 28 2005 3-4 20 04 337-341 |
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Abstract Assembly line balancing has been a focus of interest to academics in operation management for the last four decades. Mass production has saved huge costs for manufacturers in various industries for some time. With the growing trend of greater product variability and shorter life cycles, traditional mass production is being replaced in assembly lines. The current market is intensely competitive and consumer-centric. Mixed-model assembly lines are increasing in many industrial environments. This study deals with mixed-model assembly line balancing for n models, and uses a classical genetic algorithm approach to minimize the number of workstations. We also incorporated a hybrid genetic algorithm approach that used the solution from the modified ranked positional method for the initial solution to reduce the search space within the global space, thereby reducing search time. Several examples illustrate the approach. The software used for programming is C++ language . © Springer-Verlag 2005 |
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Abstract Assembly line balancing has been a focus of interest to academics in operation management for the last four decades. Mass production has saved huge costs for manufacturers in various industries for some time. With the growing trend of greater product variability and shorter life cycles, traditional mass production is being replaced in assembly lines. The current market is intensely competitive and consumer-centric. Mixed-model assembly lines are increasing in many industrial environments. This study deals with mixed-model assembly line balancing for n models, and uses a classical genetic algorithm approach to minimize the number of workstations. We also incorporated a hybrid genetic algorithm approach that used the solution from the modified ranked positional method for the initial solution to reduce the search space within the global space, thereby reducing search time. Several examples illustrate the approach. The software used for programming is C++ language . © Springer-Verlag 2005 |
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Abstract Assembly line balancing has been a focus of interest to academics in operation management for the last four decades. Mass production has saved huge costs for manufacturers in various industries for some time. With the growing trend of greater product variability and shorter life cycles, traditional mass production is being replaced in assembly lines. The current market is intensely competitive and consumer-centric. Mixed-model assembly lines are increasing in many industrial environments. This study deals with mixed-model assembly line balancing for n models, and uses a classical genetic algorithm approach to minimize the number of workstations. We also incorporated a hybrid genetic algorithm approach that used the solution from the modified ranked positional method for the initial solution to reduce the search space within the global space, thereby reducing search time. Several examples illustrate the approach. The software used for programming is C++ language . © Springer-Verlag 2005 |
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A hybrid genetic algorithm approach to mixed-model assembly line balancing |
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Rengarajan, K. Jayaprakash, J. |
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