Effective Hot Rolling Batch Scheduling Algorithms in Compact Strip Production.
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| Title: | Effective Hot Rolling Batch Scheduling Algorithms in Compact Strip Production. |
|---|---|
| Authors: | Chen, Qingda1 (AUTHOR) cqd0309@126.com, Pan, Quanke2 (AUTHOR) panquanke@mail.neu.edu.cn, Zhang, Biao3 (AUTHOR) zhangbiao1218@gmail.com, Ding, Jingliang1 (AUTHOR) jlding@mail.neu.edu.cn, Li, Junqing1 (AUTHOR) lijunqing.cn@gmail.com |
| Source: | IEEE Transactions on Automation Science & Engineering. Oct2019, Vol. 16 Issue 4, p1933-1951. 19p. |
| Subjects: | Bees algorithm, Hot rolling, Batch processing, Metaheuristic algorithms, Evolutionary algorithms, Bee colonies, Computer scheduling |
| Abstract: | This paper studies a hot rolling batch scheduling problem in compact strip production (CSP), which is decomposed into a two-stage problem. The first stage is the strip combination problem aimed at determining the strip combination of each rolling turn and the number of rolling turns with the objective of minimizing the number of virtual strips, and the second is the strip allocation and sequencing problem aimed at optimizing the allocation and rolling sequence of the strips in each rolling turn. We first model this two-stage problem considering a set of production constraints and then design an optimal approach to solve the strip combination problem. Subsequently, we design an evolutionary algorithm (i.e., artificial bee colony algorithm) with a novel search strategy for employed bees, a dynamic strategy for onlooker bees, a variable neighborhood search strategy for a scout bee, and an enhanced strategy to solve the problem in the second stage. Computational experiments demonstrate the effectiveness of the proposed algorithms. Note to Practitioners—The hot rolling batch scheduling process is crucial in linking the casting and rolling processes of iron and steel productions. In the rolling batch scheduling problem of CSP, there is no buffer between the casting and rolling processes, and virtual strips must be added to satisfy production constraints. Most rolling batch scheduling methods do not consider the addition of virtual strips. In this paper, we mathematically characterize the hot rolling batch scheduling problem in CSP with flexible production constraints. We then show how the optimal approach and artificial bee colony algorithm are designed. Finally, the effectiveness of the proposed algorithms is demonstrated by comparisons with other well-known metaheuristic algorithms. This paper can be extended to other hot rolling batch scheduling problems with buffers and hybrid flowshop scheduling problems. [ABSTRACT FROM AUTHOR] |
| Copyright of IEEE Transactions on Automation Science & Engineering is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 139076449 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Effective Hot Rolling Batch Scheduling Algorithms in Compact Strip Production. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Chen%2C+Qingda%22">Chen, Qingda</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> cqd0309@126.com</i><br /><searchLink fieldCode="AR" term="%22Pan%2C+Quanke%22">Pan, Quanke</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> panquanke@mail.neu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Biao%22">Zhang, Biao</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> zhangbiao1218@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Ding%2C+Jingliang%22">Ding, Jingliang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jlding@mail.neu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Junqing%22">Li, Junqing</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> lijunqing.cn@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Automation+Science+%26+Engineering%22">IEEE Transactions on Automation Science & Engineering</searchLink>. Oct2019, Vol. 16 Issue 4, p1933-1951. 19p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Bees+algorithm%22">Bees algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22Hot+rolling%22">Hot rolling</searchLink><br /><searchLink fieldCode="DE" term="%22Batch+processing%22">Batch processing</searchLink><br /><searchLink fieldCode="DE" term="%22Metaheuristic+algorithms%22">Metaheuristic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Evolutionary+algorithms%22">Evolutionary algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Bee+colonies%22">Bee colonies</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+scheduling%22">Computer scheduling</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper studies a hot rolling batch scheduling problem in compact strip production (CSP), which is decomposed into a two-stage problem. The first stage is the strip combination problem aimed at determining the strip combination of each rolling turn and the number of rolling turns with the objective of minimizing the number of virtual strips, and the second is the strip allocation and sequencing problem aimed at optimizing the allocation and rolling sequence of the strips in each rolling turn. We first model this two-stage problem considering a set of production constraints and then design an optimal approach to solve the strip combination problem. Subsequently, we design an evolutionary algorithm (i.e., artificial bee colony algorithm) with a novel search strategy for employed bees, a dynamic strategy for onlooker bees, a variable neighborhood search strategy for a scout bee, and an enhanced strategy to solve the problem in the second stage. Computational experiments demonstrate the effectiveness of the proposed algorithms. Note to Practitioners—The hot rolling batch scheduling process is crucial in linking the casting and rolling processes of iron and steel productions. In the rolling batch scheduling problem of CSP, there is no buffer between the casting and rolling processes, and virtual strips must be added to satisfy production constraints. Most rolling batch scheduling methods do not consider the addition of virtual strips. In this paper, we mathematically characterize the hot rolling batch scheduling problem in CSP with flexible production constraints. We then show how the optimal approach and artificial bee colony algorithm are designed. Finally, the effectiveness of the proposed algorithms is demonstrated by comparisons with other well-known metaheuristic algorithms. This paper can be extended to other hot rolling batch scheduling problems with buffers and hybrid flowshop scheduling problems. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IEEE Transactions on Automation Science & Engineering is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1109/TASE.2019.2914925 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 1933 Subjects: – SubjectFull: Bees algorithm Type: general – SubjectFull: Hot rolling Type: general – SubjectFull: Batch processing Type: general – SubjectFull: Metaheuristic algorithms Type: general – SubjectFull: Evolutionary algorithms Type: general – SubjectFull: Bee colonies Type: general – SubjectFull: Computer scheduling Type: general Titles: – TitleFull: Effective Hot Rolling Batch Scheduling Algorithms in Compact Strip Production. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chen, Qingda – PersonEntity: Name: NameFull: Pan, Quanke – PersonEntity: Name: NameFull: Zhang, Biao – PersonEntity: Name: NameFull: Ding, Jingliang – PersonEntity: Name: NameFull: Li, Junqing IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2019 Type: published Y: 2019 Identifiers: – Type: issn-print Value: 15455955 Numbering: – Type: volume Value: 16 – Type: issue Value: 4 Titles: – TitleFull: IEEE Transactions on Automation Science & Engineering Type: main |
| ResultId | 1 |
