A novel job rotation schedule model for repetitive jobs regarding posture variety during work hours and solving with a genetic algorithm

Job rotation is a known method that is often used to reduce monotonous workloads on workers with repetitive workstation-based jobs. Changes in a worker’s body posture can contribute to reduce the monotony; particularly, while there exists none or only minimal external force exertion. The purpose of...

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Main Authors: Cheshmehgaz, Hossein Rajabalipour, Haron, Habibollah
Format: Article
Published: Journal of Computing 2011
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Online Access:http://eprints.utm.my/id/eprint/37546/
https://sites.google.com/site/journalofcomputing/volume-3-issue-5-may-2011
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spelling my.utm.375462019-03-17T04:02:16Z http://eprints.utm.my/id/eprint/37546/ A novel job rotation schedule model for repetitive jobs regarding posture variety during work hours and solving with a genetic algorithm Cheshmehgaz, Hossein Rajabalipour Haron, Habibollah QA75 Electronic computers. Computer science Job rotation is a known method that is often used to reduce monotonous workloads on workers with repetitive workstation-based jobs. Changes in a worker’s body posture can contribute to reduce the monotony; particularly, while there exists none or only minimal external force exertion. The purpose of this research is to develop a method to incorporate posture variety, individually, for each particular body area, into the rotation. This method can increase the possibility of having overall posture variety during work-hours or shift-by-shift for workers. To this end, fuzzy dissimilarity magnitudes between two jobs based on linguistic variables are defined and then used to propose new criteria. According to the criteria, an integerprogramming model for the rotation is developed. Owing to the large search space in which to find a very good solution (approximated optimum solution), a conventional genetic algorithm and a customized cellular genetic algorithm are employed and compared. In addition to being intuitively logical, the algorithms are examined in a simplified test case with six different assembly jobs (performing assigned tasks repetitively), and the results indicate that the cellular genetic algorithm can efficiently find better job rotation schedules to satisfy the criteria. Journal of Computing 2011 Article PeerReviewed Cheshmehgaz, Hossein Rajabalipour and Haron, Habibollah (2011) A novel job rotation schedule model for repetitive jobs regarding posture variety during work hours and solving with a genetic algorithm. Journal of Computing, 3 (5). pp. 67-75. ISSN 2151-9617 https://sites.google.com/site/journalofcomputing/volume-3-issue-5-may-2011
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Cheshmehgaz, Hossein Rajabalipour
Haron, Habibollah
A novel job rotation schedule model for repetitive jobs regarding posture variety during work hours and solving with a genetic algorithm
description Job rotation is a known method that is often used to reduce monotonous workloads on workers with repetitive workstation-based jobs. Changes in a worker’s body posture can contribute to reduce the monotony; particularly, while there exists none or only minimal external force exertion. The purpose of this research is to develop a method to incorporate posture variety, individually, for each particular body area, into the rotation. This method can increase the possibility of having overall posture variety during work-hours or shift-by-shift for workers. To this end, fuzzy dissimilarity magnitudes between two jobs based on linguistic variables are defined and then used to propose new criteria. According to the criteria, an integerprogramming model for the rotation is developed. Owing to the large search space in which to find a very good solution (approximated optimum solution), a conventional genetic algorithm and a customized cellular genetic algorithm are employed and compared. In addition to being intuitively logical, the algorithms are examined in a simplified test case with six different assembly jobs (performing assigned tasks repetitively), and the results indicate that the cellular genetic algorithm can efficiently find better job rotation schedules to satisfy the criteria.
format Article
author Cheshmehgaz, Hossein Rajabalipour
Haron, Habibollah
author_facet Cheshmehgaz, Hossein Rajabalipour
Haron, Habibollah
author_sort Cheshmehgaz, Hossein Rajabalipour
title A novel job rotation schedule model for repetitive jobs regarding posture variety during work hours and solving with a genetic algorithm
title_short A novel job rotation schedule model for repetitive jobs regarding posture variety during work hours and solving with a genetic algorithm
title_full A novel job rotation schedule model for repetitive jobs regarding posture variety during work hours and solving with a genetic algorithm
title_fullStr A novel job rotation schedule model for repetitive jobs regarding posture variety during work hours and solving with a genetic algorithm
title_full_unstemmed A novel job rotation schedule model for repetitive jobs regarding posture variety during work hours and solving with a genetic algorithm
title_sort novel job rotation schedule model for repetitive jobs regarding posture variety during work hours and solving with a genetic algorithm
publisher Journal of Computing
publishDate 2011
url http://eprints.utm.my/id/eprint/37546/
https://sites.google.com/site/journalofcomputing/volume-3-issue-5-may-2011
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score 13.211869