Fatigue Consideration optimization Model for Employee Allocation in Flow Shop Scheduling Problems
© 2019 IEEE. The employee allocation and production scheduling are the key factors in manufacturing enterprises. Especially, in small and medium enterprises, the working employees are the main resources of the production process. The employees gain orientation in variety skills; they can be assigned...
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th-cmuir.6653943832-655562019-08-05T04:36:31Z Fatigue Consideration optimization Model for Employee Allocation in Flow Shop Scheduling Problems Sirada Kerdsiri Somrawee Aramkul Paskorn Champrasert Decision Sciences Engineering © 2019 IEEE. The employee allocation and production scheduling are the key factors in manufacturing enterprises. Especially, in small and medium enterprises, the working employees are the main resources of the production process. The employees gain orientation in variety skills; they can be assigned to any processes. Moreover, when the employees work for a long period, the productivity drops because of their working fatigue. Thus, the initial flow shop scheduling plan may not result as expected. This paper proposes to apply the re-optimization process for employee allocation during the production period. However, the re-optimization requires the setup time to start the new process. The proposed model introduces the rescheduling checking procedure to properly invoke the optimization process. The genetic algorithm is applied in the optimization process. The evaluation results show that the proposed model can reduce the makespan with the suitable rescheduling optimization process. 2019-08-05T04:35:19Z 2019-08-05T04:35:19Z 2019-05-14 Conference Proceeding 2-s2.0-85066622084 10.1109/IEA.2019.8714919 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85066622084&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/65556 |
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Decision Sciences Engineering Sirada Kerdsiri Somrawee Aramkul Paskorn Champrasert Fatigue Consideration optimization Model for Employee Allocation in Flow Shop Scheduling Problems |
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© 2019 IEEE. The employee allocation and production scheduling are the key factors in manufacturing enterprises. Especially, in small and medium enterprises, the working employees are the main resources of the production process. The employees gain orientation in variety skills; they can be assigned to any processes. Moreover, when the employees work for a long period, the productivity drops because of their working fatigue. Thus, the initial flow shop scheduling plan may not result as expected. This paper proposes to apply the re-optimization process for employee allocation during the production period. However, the re-optimization requires the setup time to start the new process. The proposed model introduces the rescheduling checking procedure to properly invoke the optimization process. The genetic algorithm is applied in the optimization process. The evaluation results show that the proposed model can reduce the makespan with the suitable rescheduling optimization process. |
format |
Conference Proceeding |
author |
Sirada Kerdsiri Somrawee Aramkul Paskorn Champrasert |
author_facet |
Sirada Kerdsiri Somrawee Aramkul Paskorn Champrasert |
author_sort |
Sirada Kerdsiri |
title |
Fatigue Consideration optimization Model for Employee Allocation in Flow Shop Scheduling Problems |
title_short |
Fatigue Consideration optimization Model for Employee Allocation in Flow Shop Scheduling Problems |
title_full |
Fatigue Consideration optimization Model for Employee Allocation in Flow Shop Scheduling Problems |
title_fullStr |
Fatigue Consideration optimization Model for Employee Allocation in Flow Shop Scheduling Problems |
title_full_unstemmed |
Fatigue Consideration optimization Model for Employee Allocation in Flow Shop Scheduling Problems |
title_sort |
fatigue consideration optimization model for employee allocation in flow shop scheduling problems |
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2019 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85066622084&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/65556 |
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