Effective hybrid discrete artificial bee colony algorithms for the total flowtime minimization in the blocking flowshop problem
Abstract In this paper, three effective hybrid discrete artificial bee colony (hDABC1, hDABC2, hDABC3) algorithms are presented to solve the blocking flowshop scheduling problem with the objective of minimizing the total flowtime. The three hybrid DABC algorithms utilize discrete job permutations to...
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| Autor*in: |
Han, Yu-Yan [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2012 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag London Limited 2012 |
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| Übergeordnetes Werk: |
Enthalten in: The international journal of advanced manufacturing technology - Springer-Verlag, 1985, 67(2012), 1-4 vom: 18. Sept., Seite 397-414 |
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| Übergeordnetes Werk: |
volume:67 ; year:2012 ; number:1-4 ; day:18 ; month:09 ; pages:397-414 |
| Links: |
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| DOI / URN: |
10.1007/s00170-012-4493-5 |
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| Katalog-ID: |
OLC2026049653 |
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| 520 | |a Abstract In this paper, three effective hybrid discrete artificial bee colony (hDABC1, hDABC2, hDABC3) algorithms are presented to solve the blocking flowshop scheduling problem with the objective of minimizing the total flowtime. The three hybrid DABC algorithms utilize discrete job permutations to represent food sources and apply discrete operators to generate new food sources for the employed bees, onlookers, and scouts, respectively. First, two heuristic rules called the MME-A and MME-B (variant of combination of minmax and NEH) are presented to construct an initial population with a certain level of quality and diversity. Second, a self-adaptive strategy is applied to employed bees. Third, the estimation of distribution algorithm implements explicit learning from selected individuals and then generates good solutions for onlooker bees. Last but not least, to improve the algorithms' local exploitation ability, a very efficient local search-based insertion neighborhood is carried out in three stages respectively, that is, hDABC1 algorithm is generated by applying a local search to the solution obtained in the employed bee stage. hDABC2 is designed by carrying out a local search in the onlooker bee stage, and hDABC3 is developed by applying a local search in the scout bee stage. Computational experiments on standard benchmark problems are conducted. The results and comparisons show that the proposed algorithms are very effective and efficient for the blocking flowshop scheduling problems with total flowtime criterion than the other algorithms. | ||
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| 650 | 4 | |a Total flowtime | |
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| 700 | 1 | |a Liang, J. J. |4 aut | |
| 700 | 1 | |a Pan, Quan-Ke |4 aut | |
| 700 | 1 | |a Li, Jun-Qing |4 aut | |
| 700 | 1 | |a Sang, Hong-Yan |4 aut | |
| 700 | 1 | |a Cao, N. N. |4 aut | |
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10.1007/s00170-012-4493-5 doi (DE-627)OLC2026049653 (DE-He213)s00170-012-4493-5-p DE-627 ger DE-627 rakwb eng 670 VZ Han, Yu-Yan verfasserin aut Effective hybrid discrete artificial bee colony algorithms for the total flowtime minimization in the blocking flowshop problem 2012 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Limited 2012 Abstract In this paper, three effective hybrid discrete artificial bee colony (hDABC1, hDABC2, hDABC3) algorithms are presented to solve the blocking flowshop scheduling problem with the objective of minimizing the total flowtime. The three hybrid DABC algorithms utilize discrete job permutations to represent food sources and apply discrete operators to generate new food sources for the employed bees, onlookers, and scouts, respectively. First, two heuristic rules called the MME-A and MME-B (variant of combination of minmax and NEH) are presented to construct an initial population with a certain level of quality and diversity. Second, a self-adaptive strategy is applied to employed bees. Third, the estimation of distribution algorithm implements explicit learning from selected individuals and then generates good solutions for onlooker bees. Last but not least, to improve the algorithms' local exploitation ability, a very efficient local search-based insertion neighborhood is carried out in three stages respectively, that is, hDABC1 algorithm is generated by applying a local search to the solution obtained in the employed bee stage. hDABC2 is designed by carrying out a local search in the onlooker bee stage, and hDABC3 is developed by applying a local search in the scout bee stage. Computational experiments on standard benchmark problems are conducted. The results and comparisons show that the proposed algorithms are very effective and efficient for the blocking flowshop scheduling problems with total flowtime criterion than the other algorithms. Blocking flowshop Total flowtime Artificial bee colony algorithm Estimation of distribution algorithm Liang, J. J. aut Pan, Quan-Ke aut Li, Jun-Qing aut Sang, Hong-Yan aut Cao, N. N. aut Enthalten in The international journal of advanced manufacturing technology Springer-Verlag, 1985 67(2012), 1-4 vom: 18. Sept., Seite 397-414 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:67 year:2012 number:1-4 day:18 month:09 pages:397-414 https://doi.org/10.1007/s00170-012-4493-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_20 GBV_ILN_70 GBV_ILN_150 GBV_ILN_2018 GBV_ILN_2333 GBV_ILN_4046 AR 67 2012 1-4 18 09 397-414 |
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10.1007/s00170-012-4493-5 doi (DE-627)OLC2026049653 (DE-He213)s00170-012-4493-5-p DE-627 ger DE-627 rakwb eng 670 VZ Han, Yu-Yan verfasserin aut Effective hybrid discrete artificial bee colony algorithms for the total flowtime minimization in the blocking flowshop problem 2012 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Limited 2012 Abstract In this paper, three effective hybrid discrete artificial bee colony (hDABC1, hDABC2, hDABC3) algorithms are presented to solve the blocking flowshop scheduling problem with the objective of minimizing the total flowtime. The three hybrid DABC algorithms utilize discrete job permutations to represent food sources and apply discrete operators to generate new food sources for the employed bees, onlookers, and scouts, respectively. First, two heuristic rules called the MME-A and MME-B (variant of combination of minmax and NEH) are presented to construct an initial population with a certain level of quality and diversity. Second, a self-adaptive strategy is applied to employed bees. Third, the estimation of distribution algorithm implements explicit learning from selected individuals and then generates good solutions for onlooker bees. Last but not least, to improve the algorithms' local exploitation ability, a very efficient local search-based insertion neighborhood is carried out in three stages respectively, that is, hDABC1 algorithm is generated by applying a local search to the solution obtained in the employed bee stage. hDABC2 is designed by carrying out a local search in the onlooker bee stage, and hDABC3 is developed by applying a local search in the scout bee stage. Computational experiments on standard benchmark problems are conducted. The results and comparisons show that the proposed algorithms are very effective and efficient for the blocking flowshop scheduling problems with total flowtime criterion than the other algorithms. Blocking flowshop Total flowtime Artificial bee colony algorithm Estimation of distribution algorithm Liang, J. J. aut Pan, Quan-Ke aut Li, Jun-Qing aut Sang, Hong-Yan aut Cao, N. N. aut Enthalten in The international journal of advanced manufacturing technology Springer-Verlag, 1985 67(2012), 1-4 vom: 18. Sept., Seite 397-414 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:67 year:2012 number:1-4 day:18 month:09 pages:397-414 https://doi.org/10.1007/s00170-012-4493-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_20 GBV_ILN_70 GBV_ILN_150 GBV_ILN_2018 GBV_ILN_2333 GBV_ILN_4046 AR 67 2012 1-4 18 09 397-414 |
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10.1007/s00170-012-4493-5 doi (DE-627)OLC2026049653 (DE-He213)s00170-012-4493-5-p DE-627 ger DE-627 rakwb eng 670 VZ Han, Yu-Yan verfasserin aut Effective hybrid discrete artificial bee colony algorithms for the total flowtime minimization in the blocking flowshop problem 2012 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Limited 2012 Abstract In this paper, three effective hybrid discrete artificial bee colony (hDABC1, hDABC2, hDABC3) algorithms are presented to solve the blocking flowshop scheduling problem with the objective of minimizing the total flowtime. The three hybrid DABC algorithms utilize discrete job permutations to represent food sources and apply discrete operators to generate new food sources for the employed bees, onlookers, and scouts, respectively. First, two heuristic rules called the MME-A and MME-B (variant of combination of minmax and NEH) are presented to construct an initial population with a certain level of quality and diversity. Second, a self-adaptive strategy is applied to employed bees. Third, the estimation of distribution algorithm implements explicit learning from selected individuals and then generates good solutions for onlooker bees. Last but not least, to improve the algorithms' local exploitation ability, a very efficient local search-based insertion neighborhood is carried out in three stages respectively, that is, hDABC1 algorithm is generated by applying a local search to the solution obtained in the employed bee stage. hDABC2 is designed by carrying out a local search in the onlooker bee stage, and hDABC3 is developed by applying a local search in the scout bee stage. Computational experiments on standard benchmark problems are conducted. The results and comparisons show that the proposed algorithms are very effective and efficient for the blocking flowshop scheduling problems with total flowtime criterion than the other algorithms. Blocking flowshop Total flowtime Artificial bee colony algorithm Estimation of distribution algorithm Liang, J. J. aut Pan, Quan-Ke aut Li, Jun-Qing aut Sang, Hong-Yan aut Cao, N. N. aut Enthalten in The international journal of advanced manufacturing technology Springer-Verlag, 1985 67(2012), 1-4 vom: 18. Sept., Seite 397-414 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:67 year:2012 number:1-4 day:18 month:09 pages:397-414 https://doi.org/10.1007/s00170-012-4493-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_20 GBV_ILN_70 GBV_ILN_150 GBV_ILN_2018 GBV_ILN_2333 GBV_ILN_4046 AR 67 2012 1-4 18 09 397-414 |
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10.1007/s00170-012-4493-5 doi (DE-627)OLC2026049653 (DE-He213)s00170-012-4493-5-p DE-627 ger DE-627 rakwb eng 670 VZ Han, Yu-Yan verfasserin aut Effective hybrid discrete artificial bee colony algorithms for the total flowtime minimization in the blocking flowshop problem 2012 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Limited 2012 Abstract In this paper, three effective hybrid discrete artificial bee colony (hDABC1, hDABC2, hDABC3) algorithms are presented to solve the blocking flowshop scheduling problem with the objective of minimizing the total flowtime. The three hybrid DABC algorithms utilize discrete job permutations to represent food sources and apply discrete operators to generate new food sources for the employed bees, onlookers, and scouts, respectively. First, two heuristic rules called the MME-A and MME-B (variant of combination of minmax and NEH) are presented to construct an initial population with a certain level of quality and diversity. Second, a self-adaptive strategy is applied to employed bees. Third, the estimation of distribution algorithm implements explicit learning from selected individuals and then generates good solutions for onlooker bees. Last but not least, to improve the algorithms' local exploitation ability, a very efficient local search-based insertion neighborhood is carried out in three stages respectively, that is, hDABC1 algorithm is generated by applying a local search to the solution obtained in the employed bee stage. hDABC2 is designed by carrying out a local search in the onlooker bee stage, and hDABC3 is developed by applying a local search in the scout bee stage. Computational experiments on standard benchmark problems are conducted. The results and comparisons show that the proposed algorithms are very effective and efficient for the blocking flowshop scheduling problems with total flowtime criterion than the other algorithms. Blocking flowshop Total flowtime Artificial bee colony algorithm Estimation of distribution algorithm Liang, J. J. aut Pan, Quan-Ke aut Li, Jun-Qing aut Sang, Hong-Yan aut Cao, N. N. aut Enthalten in The international journal of advanced manufacturing technology Springer-Verlag, 1985 67(2012), 1-4 vom: 18. Sept., Seite 397-414 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:67 year:2012 number:1-4 day:18 month:09 pages:397-414 https://doi.org/10.1007/s00170-012-4493-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_20 GBV_ILN_70 GBV_ILN_150 GBV_ILN_2018 GBV_ILN_2333 GBV_ILN_4046 AR 67 2012 1-4 18 09 397-414 |
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10.1007/s00170-012-4493-5 doi (DE-627)OLC2026049653 (DE-He213)s00170-012-4493-5-p DE-627 ger DE-627 rakwb eng 670 VZ Han, Yu-Yan verfasserin aut Effective hybrid discrete artificial bee colony algorithms for the total flowtime minimization in the blocking flowshop problem 2012 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Limited 2012 Abstract In this paper, three effective hybrid discrete artificial bee colony (hDABC1, hDABC2, hDABC3) algorithms are presented to solve the blocking flowshop scheduling problem with the objective of minimizing the total flowtime. The three hybrid DABC algorithms utilize discrete job permutations to represent food sources and apply discrete operators to generate new food sources for the employed bees, onlookers, and scouts, respectively. First, two heuristic rules called the MME-A and MME-B (variant of combination of minmax and NEH) are presented to construct an initial population with a certain level of quality and diversity. Second, a self-adaptive strategy is applied to employed bees. Third, the estimation of distribution algorithm implements explicit learning from selected individuals and then generates good solutions for onlooker bees. Last but not least, to improve the algorithms' local exploitation ability, a very efficient local search-based insertion neighborhood is carried out in three stages respectively, that is, hDABC1 algorithm is generated by applying a local search to the solution obtained in the employed bee stage. hDABC2 is designed by carrying out a local search in the onlooker bee stage, and hDABC3 is developed by applying a local search in the scout bee stage. Computational experiments on standard benchmark problems are conducted. The results and comparisons show that the proposed algorithms are very effective and efficient for the blocking flowshop scheduling problems with total flowtime criterion than the other algorithms. Blocking flowshop Total flowtime Artificial bee colony algorithm Estimation of distribution algorithm Liang, J. J. aut Pan, Quan-Ke aut Li, Jun-Qing aut Sang, Hong-Yan aut Cao, N. N. aut Enthalten in The international journal of advanced manufacturing technology Springer-Verlag, 1985 67(2012), 1-4 vom: 18. Sept., Seite 397-414 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:67 year:2012 number:1-4 day:18 month:09 pages:397-414 https://doi.org/10.1007/s00170-012-4493-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_20 GBV_ILN_70 GBV_ILN_150 GBV_ILN_2018 GBV_ILN_2333 GBV_ILN_4046 AR 67 2012 1-4 18 09 397-414 |
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Effective hybrid discrete artificial bee colony algorithms for the total flowtime minimization in the blocking flowshop problem |
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Effective hybrid discrete artificial bee colony algorithms for the total flowtime minimization in the blocking flowshop problem |
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Han, Yu-Yan |
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The international journal of advanced manufacturing technology |
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2012 |
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Han, Yu-Yan Liang, J. J. Pan, Quan-Ke Li, Jun-Qing Sang, Hong-Yan Cao, N. N. |
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effective hybrid discrete artificial bee colony algorithms for the total flowtime minimization in the blocking flowshop problem |
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Effective hybrid discrete artificial bee colony algorithms for the total flowtime minimization in the blocking flowshop problem |
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Abstract In this paper, three effective hybrid discrete artificial bee colony (hDABC1, hDABC2, hDABC3) algorithms are presented to solve the blocking flowshop scheduling problem with the objective of minimizing the total flowtime. The three hybrid DABC algorithms utilize discrete job permutations to represent food sources and apply discrete operators to generate new food sources for the employed bees, onlookers, and scouts, respectively. First, two heuristic rules called the MME-A and MME-B (variant of combination of minmax and NEH) are presented to construct an initial population with a certain level of quality and diversity. Second, a self-adaptive strategy is applied to employed bees. Third, the estimation of distribution algorithm implements explicit learning from selected individuals and then generates good solutions for onlooker bees. Last but not least, to improve the algorithms' local exploitation ability, a very efficient local search-based insertion neighborhood is carried out in three stages respectively, that is, hDABC1 algorithm is generated by applying a local search to the solution obtained in the employed bee stage. hDABC2 is designed by carrying out a local search in the onlooker bee stage, and hDABC3 is developed by applying a local search in the scout bee stage. Computational experiments on standard benchmark problems are conducted. The results and comparisons show that the proposed algorithms are very effective and efficient for the blocking flowshop scheduling problems with total flowtime criterion than the other algorithms. © Springer-Verlag London Limited 2012 |
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Abstract In this paper, three effective hybrid discrete artificial bee colony (hDABC1, hDABC2, hDABC3) algorithms are presented to solve the blocking flowshop scheduling problem with the objective of minimizing the total flowtime. The three hybrid DABC algorithms utilize discrete job permutations to represent food sources and apply discrete operators to generate new food sources for the employed bees, onlookers, and scouts, respectively. First, two heuristic rules called the MME-A and MME-B (variant of combination of minmax and NEH) are presented to construct an initial population with a certain level of quality and diversity. Second, a self-adaptive strategy is applied to employed bees. Third, the estimation of distribution algorithm implements explicit learning from selected individuals and then generates good solutions for onlooker bees. Last but not least, to improve the algorithms' local exploitation ability, a very efficient local search-based insertion neighborhood is carried out in three stages respectively, that is, hDABC1 algorithm is generated by applying a local search to the solution obtained in the employed bee stage. hDABC2 is designed by carrying out a local search in the onlooker bee stage, and hDABC3 is developed by applying a local search in the scout bee stage. Computational experiments on standard benchmark problems are conducted. The results and comparisons show that the proposed algorithms are very effective and efficient for the blocking flowshop scheduling problems with total flowtime criterion than the other algorithms. © Springer-Verlag London Limited 2012 |
| abstract_unstemmed |
Abstract In this paper, three effective hybrid discrete artificial bee colony (hDABC1, hDABC2, hDABC3) algorithms are presented to solve the blocking flowshop scheduling problem with the objective of minimizing the total flowtime. The three hybrid DABC algorithms utilize discrete job permutations to represent food sources and apply discrete operators to generate new food sources for the employed bees, onlookers, and scouts, respectively. First, two heuristic rules called the MME-A and MME-B (variant of combination of minmax and NEH) are presented to construct an initial population with a certain level of quality and diversity. Second, a self-adaptive strategy is applied to employed bees. Third, the estimation of distribution algorithm implements explicit learning from selected individuals and then generates good solutions for onlooker bees. Last but not least, to improve the algorithms' local exploitation ability, a very efficient local search-based insertion neighborhood is carried out in three stages respectively, that is, hDABC1 algorithm is generated by applying a local search to the solution obtained in the employed bee stage. hDABC2 is designed by carrying out a local search in the onlooker bee stage, and hDABC3 is developed by applying a local search in the scout bee stage. Computational experiments on standard benchmark problems are conducted. The results and comparisons show that the proposed algorithms are very effective and efficient for the blocking flowshop scheduling problems with total flowtime criterion than the other algorithms. © Springer-Verlag London Limited 2012 |
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Effective hybrid discrete artificial bee colony algorithms for the total flowtime minimization in the blocking flowshop problem |
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