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Scheduling with multi-attribute set-up times on unrelated parallel machines.

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Title: Scheduling with multi-attribute set-up times on unrelated parallel machines.
Authors: Liao, Ching-Jong1 (AUTHOR), Lee, Cheng-Hsiung2 (AUTHOR) brucelee@mail.chihlee.edu.tw, Tsai, Hsing-Tzu1 (AUTHOR)
Source: International Journal of Production Research. Aug2016, Vol. 54 Issue 16, p4839-4853. 15p. 1 Color Photograph, 3 Diagrams, 11 Charts.
Subjects: Setup time, Parallel scheduling (Computer scheduling), Textile machinery, Textile industry, Production scheduling, Heuristic algorithms
Abstract: This paper studies a problem in the knitting process of the textile industry. In such a production system, each job has a number of attributes and each attribute has one or more levels. Because there is at least one different attribute level between two adjacent jobs, it is necessary to make a set-up adjustment whenever there is a switch to a different job. The problem can be formulated as a scheduling problem with multi-attribute set-up times on unrelated parallel machines. The objective of the problem is to assign jobs to different machines to minimise the makespan. A constructive heuristic is developed to obtain a qualified solution. To improve the solution further, a meta-heuristic that uses a genetic algorithm with a new crossover operator and three local searches are proposed. The computational experiments show that the proposed constructive heuristic outperforms two existed heuristics and the current scheduling method used by the case textile plant. [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.)
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  Data: Scheduling with multi-attribute set-up times on unrelated parallel machines.
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  Data: <searchLink fieldCode="AR" term="%22Liao%2C+Ching-Jong%22">Liao, Ching-Jong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lee%2C+Cheng-Hsiung%22">Lee, Cheng-Hsiung</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> brucelee@mail.chihlee.edu.tw</i><br /><searchLink fieldCode="AR" term="%22Tsai%2C+Hsing-Tzu%22">Tsai, Hsing-Tzu</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Aug2016, Vol. 54 Issue 16, p4839-4853. 15p. 1 Color Photograph, 3 Diagrams, 11 Charts.
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  Data: <searchLink fieldCode="DE" term="%22Setup+time%22">Setup time</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+scheduling+%28Computer+scheduling%29%22">Parallel scheduling (Computer scheduling)</searchLink><br /><searchLink fieldCode="DE" term="%22Textile+machinery%22">Textile machinery</searchLink><br /><searchLink fieldCode="DE" term="%22Textile+industry%22">Textile industry</searchLink><br /><searchLink fieldCode="DE" term="%22Production+scheduling%22">Production scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Heuristic+algorithms%22">Heuristic algorithms</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper studies a problem in the knitting process of the textile industry. In such a production system, each job has a number of attributes and each attribute has one or more levels. Because there is at least one different attribute level between two adjacent jobs, it is necessary to make a set-up adjustment whenever there is a switch to a different job. The problem can be formulated as a scheduling problem with multi-attribute set-up times on unrelated parallel machines. The objective of the problem is to assign jobs to different machines to minimise the makespan. A constructive heuristic is developed to obtain a qualified solution. To improve the solution further, a meta-heuristic that uses a genetic algorithm with a new crossover operator and three local searches are proposed. The computational experiments show that the proposed constructive heuristic outperforms two existed heuristics and the current scheduling method used by the case textile plant. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  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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        Value: 10.1080/00207543.2015.1118574
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 15
        StartPage: 4839
    Subjects:
      – SubjectFull: Setup time
        Type: general
      – SubjectFull: Parallel scheduling (Computer scheduling)
        Type: general
      – SubjectFull: Textile machinery
        Type: general
      – SubjectFull: Textile industry
        Type: general
      – SubjectFull: Production scheduling
        Type: general
      – SubjectFull: Heuristic algorithms
        Type: general
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      – TitleFull: Scheduling with multi-attribute set-up times on unrelated parallel machines.
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            NameFull: Lee, Cheng-Hsiung
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            NameFull: Tsai, Hsing-Tzu
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            – D: 15
              M: 08
              Text: Aug2016
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              Y: 2016
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            – TitleFull: International Journal of Production Research
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