Solving the job shop scheduling problem with tabu search.
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| Title: | Solving the job shop scheduling problem with tabu search. |
|---|---|
| Authors: | Barnes, J. Wesley1, Chambers, John B.1 |
| Source: | IIE Transactions. Apr95, Vol. 27 Issue 2, p257-263. 7p. 1 Diagram, 5 Charts. |
| Subjects: | Production scheduling, Operations research, Heuristic, Machinery |
| Abstract: | In the job shop scheduling problem we desire to minimize the makespan where a set of machines perform technologically ordered operations unique to each member of a set of jobs. Each operation has a fixed time duration, no machine can perform more than one operation at a time, and preemption is not allowed. In this paper, an effective tabu search approach to the job shop scheduling problem is presented. The procedure starts from the best solution rendered by a set of 14 heuristic dispatching solutions. It then makes use of the classical disjunctive network representation of the problem and iteratively moves to another feasible solution by reversing the order of two adjacent critical path operations performed by the same machine. The concepts of historical generators and search restart are used in conjunction with a contiguous spectrum of short term memory values to enhance the overall exploration strategy. Computational results are presented and areas for future investigation are suggested. [ABSTRACT FROM AUTHOR] |
| Copyright of IIE Transactions is the property of Taylor & Francis Ltd 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: 15033808 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Solving the job shop scheduling problem with tabu search. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Barnes%2C+J%2E+Wesley%22">Barnes, J. Wesley</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chambers%2C+John+B%2E%22">Chambers, John B.</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IIE+Transactions%22">IIE Transactions</searchLink>. Apr95, Vol. 27 Issue 2, p257-263. 7p. 1 Diagram, 5 Charts. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Production+scheduling%22">Production scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Operations+research%22">Operations research</searchLink><br /><searchLink fieldCode="DE" term="%22Heuristic%22">Heuristic</searchLink><br /><searchLink fieldCode="DE" term="%22Machinery%22">Machinery</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In the job shop scheduling problem we desire to minimize the makespan where a set of machines perform technologically ordered operations unique to each member of a set of jobs. Each operation has a fixed time duration, no machine can perform more than one operation at a time, and preemption is not allowed. In this paper, an effective tabu search approach to the job shop scheduling problem is presented. The procedure starts from the best solution rendered by a set of 14 heuristic dispatching solutions. It then makes use of the classical disjunctive network representation of the problem and iteratively moves to another feasible solution by reversing the order of two adjacent critical path operations performed by the same machine. The concepts of historical generators and search restart are used in conjunction with a contiguous spectrum of short term memory values to enhance the overall exploration strategy. Computational results are presented and areas for future investigation are suggested. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IIE Transactions is the property of Taylor & Francis Ltd 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: 10.1080/07408179508936739 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 7 StartPage: 257 Subjects: – SubjectFull: Production scheduling Type: general – SubjectFull: Operations research Type: general – SubjectFull: Heuristic Type: general – SubjectFull: Machinery Type: general Titles: – TitleFull: Solving the job shop scheduling problem with tabu search. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Barnes, J. Wesley – PersonEntity: Name: NameFull: Chambers, John B. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr95 Type: published Y: 1995 Identifiers: – Type: issn-print Value: 0740817X Numbering: – Type: volume Value: 27 – Type: issue Value: 2 Titles: – TitleFull: IIE Transactions Type: main |
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