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Model and heuristics for the multi-manned assembly line worker integration and balancing problem.

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Title: Model and heuristics for the multi-manned assembly line worker integration and balancing problem.
Authors: Michels, Adalberto Sato1,2 (AUTHOR) a.satomichels@unimelb.edu.au, Costa, Alysson M.1,2 (AUTHOR)
Source: International Journal of Production Research. Dec2024, Vol. 62 Issue 24, p8719-8744. 26p.
Subjects: Assembly line balancing, Assembly line methods, Linear programming, Manufacturing industries, Labor supply
Abstract: This paper examines the balancing of assembly lines with multi-manned stations and a heterogeneous workforce. Both topics received considerable attention in the literature, but not in an integrated fashion. Combining these two characteristics gives rise to a highly combinatorial Multi-manned Assembly Line Worker Integration and Balancing Problem. When considering multi-manned stations, the already coupled decisions on assigning tasks to heterogeneous workers and workers to stations must be further linked with task scheduling assessments. We propose a Mixed-Integer Linear Programming model and develop two heuristic solution procedures, which tackle the problem with a hierarchical decomposition approach. Computational tests on a large dataset indicate that the proposed method can obtain good primal bounds in short computational times. We demonstrate that these results can be applied to the monolithic model either as a warm start or in a proximity search procedure to obtain synergistic gains with statistically significant differences. From a managerial perspective, we show that multi-manned stations can reduce the assembly line's length even in the presence of a heterogeneous workforce, which is crucial for many industries manufacturing large-size products. [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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An: 180919902
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  Data: Model and heuristics for the multi-manned assembly line worker integration and balancing problem.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Dec2024, Vol. 62 Issue 24, p8719-8744. 26p.
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  Data: <searchLink fieldCode="DE" term="%22Assembly+line+balancing%22">Assembly line balancing</searchLink><br /><searchLink fieldCode="DE" term="%22Assembly+line+methods%22">Assembly line methods</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+programming%22">Linear programming</searchLink><br /><searchLink fieldCode="DE" term="%22Manufacturing+industries%22">Manufacturing industries</searchLink><br /><searchLink fieldCode="DE" term="%22Labor+supply%22">Labor supply</searchLink>
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  Data: This paper examines the balancing of assembly lines with multi-manned stations and a heterogeneous workforce. Both topics received considerable attention in the literature, but not in an integrated fashion. Combining these two characteristics gives rise to a highly combinatorial Multi-manned Assembly Line Worker Integration and Balancing Problem. When considering multi-manned stations, the already coupled decisions on assigning tasks to heterogeneous workers and workers to stations must be further linked with task scheduling assessments. We propose a Mixed-Integer Linear Programming model and develop two heuristic solution procedures, which tackle the problem with a hierarchical decomposition approach. Computational tests on a large dataset indicate that the proposed method can obtain good primal bounds in short computational times. We demonstrate that these results can be applied to the monolithic model either as a warm start or in a proximity search procedure to obtain synergistic gains with statistically significant differences. From a managerial perspective, we show that multi-manned stations can reduce the assembly line's length even in the presence of a heterogeneous workforce, which is crucial for many industries manufacturing large-size products. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  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: 10.1080/00207543.2024.2347572
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      – Code: eng
        Text: English
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        PageCount: 26
        StartPage: 8719
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      – SubjectFull: Assembly line balancing
        Type: general
      – SubjectFull: Assembly line methods
        Type: general
      – SubjectFull: Linear programming
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      – SubjectFull: Manufacturing industries
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      – SubjectFull: Labor supply
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              Text: Dec2024
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