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Multi-level job scheduling in a flexible job shop environment.

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Title: Multi-level job scheduling in a flexible job shop environment.
Authors: Na, Hongbum1 (AUTHOR), Park, Jinwoo1 (AUTHOR) autofact@snu.ac.kr
Source: International Journal of Production Research. Jul2014, Vol. 52 Issue 13, p3877-3887. 11p. 3 Black and White Photographs, 3 Diagrams, 3 Charts.
Subjects: Job shops, Production scheduling, Manufacturing cells, Production planning, Genetic algorithms, Material requirements planning, Materials management, Flexible manufacturing systems
Abstract: This study deals with a scheduling problem with multi-level job structures in a flexible job shop environment. This scheduling process arises after the part production plans are created by the MRP (material requirement planning) system, therefore the total tardiness measure is considered as an objective function in order to complete the parts by the set due dates. MILP (mixed integer linear programming) model is introduced to mathematically represent the target problem. Owing to the high complexity of the target problem, GA (genetic algorithm) is proposed to solve the problem and additional methods, such as priority rules and local search rules, are applied to improve the performance of GA. Computational examples are shown and the results are discussed in comparison with the results of IBM ILOG CPLEX and IBM ILOG CP Optimizer. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Production Research 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
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  Data: Multi-level job scheduling in a flexible job shop environment.
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  Data: <searchLink fieldCode="AR" term="%22Na%2C+Hongbum%22">Na, Hongbum</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Park%2C+Jinwoo%22">Park, Jinwoo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> autofact@snu.ac.kr</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Jul2014, Vol. 52 Issue 13, p3877-3887. 11p. 3 Black and White Photographs, 3 Diagrams, 3 Charts.
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  Data: <searchLink fieldCode="DE" term="%22Job+shops%22">Job shops</searchLink><br /><searchLink fieldCode="DE" term="%22Production+scheduling%22">Production scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Manufacturing+cells%22">Manufacturing cells</searchLink><br /><searchLink fieldCode="DE" term="%22Production+planning%22">Production planning</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Material+requirements+planning%22">Material requirements planning</searchLink><br /><searchLink fieldCode="DE" term="%22Materials+management%22">Materials management</searchLink><br /><searchLink fieldCode="DE" term="%22Flexible+manufacturing+systems%22">Flexible manufacturing systems</searchLink>
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  Label: Abstract
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  Data: This study deals with a scheduling problem with multi-level job structures in a flexible job shop environment. This scheduling process arises after the part production plans are created by the MRP (material requirement planning) system, therefore the total tardiness measure is considered as an objective function in order to complete the parts by the set due dates. MILP (mixed integer linear programming) model is introduced to mathematically represent the target problem. Owing to the high complexity of the target problem, GA (genetic algorithm) is proposed to solve the problem and additional methods, such as priority rules and local search rules, are applied to improve the performance of GA. Computational examples are shown and the results are discussed in comparison with the results of IBM ILOG CPLEX and IBM ILOG CP Optimizer. [ABSTRACT FROM AUTHOR]
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  Label:
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  Data: <i>Copyright of International Journal of Production Research 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:
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    Identifiers:
      – Type: doi
        Value: 10.1080/00207543.2013.848487
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 3877
    Subjects:
      – SubjectFull: Job shops
        Type: general
      – SubjectFull: Production scheduling
        Type: general
      – SubjectFull: Manufacturing cells
        Type: general
      – SubjectFull: Production planning
        Type: general
      – SubjectFull: Genetic algorithms
        Type: general
      – SubjectFull: Material requirements planning
        Type: general
      – SubjectFull: Materials management
        Type: general
      – SubjectFull: Flexible manufacturing systems
        Type: general
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      – TitleFull: Multi-level job scheduling in a flexible job shop environment.
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            NameFull: Na, Hongbum
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            NameFull: Park, Jinwoo
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            – D: 01
              M: 07
              Text: Jul2014
              Type: published
              Y: 2014
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              Value: 52
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              Value: 13
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