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Managing risk in production scheduling under uncertain disruption

The job scheduling problem (JSP) is considered as one of the most complex combinatorial optimization problems. JSP is not an independent task, but is rather a part of a company business case. In this paper, we have studied JSPs under sudden machine breakdown scenarios that introduce a risk of not co...

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Main Authors: Sarker, Ruhul, Essam, Daryl, Kamrul Hasan, S.M., Karim, A.N. Mustafizul
Format: Article
Language:English
Published: Cambridge University Press 2015
Subjects:
TS155 Production management
Online Access:http://irep.iium.edu.my/48683/1/%2335_AIEDAM-paper.pdf
http://irep.iium.edu.my/48683/
http://journals.cambridge.org/abstract_S0890060415000323
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spelling my.iium.irep.486832017-10-15T17:46:15Z http://irep.iium.edu.my/48683/ Managing risk in production scheduling under uncertain disruption Sarker, Ruhul Essam, Daryl Kamrul Hasan, S.M. Karim, A.N. Mustafizul TS155 Production management The job scheduling problem (JSP) is considered as one of the most complex combinatorial optimization problems. JSP is not an independent task, but is rather a part of a company business case. In this paper, we have studied JSPs under sudden machine breakdown scenarios that introduce a risk of not completing the jobs on time. We have first solved JSPs using an improved memetic algorithm and extended the algorithm to deal with the disruption situations, and then developed a simulation model to analyze the risk of using a job order and delivery scenario. This paper deals with job scheduling under ideal conditions and rescheduling under machine breakdown, and provides a risk analysis for a production business case. The extended algorithm provides better understanding and results than existing algorithms, the rescheduling shows a good way of recovering from disruptions, and the risk analysis shows an effective way of maximizing return under such situations. Cambridge University Press 2015-06-09 Article REM application/pdf en http://irep.iium.edu.my/48683/1/%2335_AIEDAM-paper.pdf Sarker, Ruhul and Essam, Daryl and Kamrul Hasan, S.M. and Karim, A.N. Mustafizul (2015) Managing risk in production scheduling under uncertain disruption. Articial Intelligence for Engineering Design, Analysis and Manufacturing. 1 -11. ISSN 0890-0604 http://journals.cambridge.org/abstract_S0890060415000323 doi:10.1017/S0890060415000323
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic TS155 Production management
spellingShingle TS155 Production management
Sarker, Ruhul
Essam, Daryl
Kamrul Hasan, S.M.
Karim, A.N. Mustafizul
Managing risk in production scheduling under uncertain disruption
description The job scheduling problem (JSP) is considered as one of the most complex combinatorial optimization problems. JSP is not an independent task, but is rather a part of a company business case. In this paper, we have studied JSPs under sudden machine breakdown scenarios that introduce a risk of not completing the jobs on time. We have first solved JSPs using an improved memetic algorithm and extended the algorithm to deal with the disruption situations, and then developed a simulation model to analyze the risk of using a job order and delivery scenario. This paper deals with job scheduling under ideal conditions and rescheduling under machine breakdown, and provides a risk analysis for a production business case. The extended algorithm provides better understanding and results than existing algorithms, the rescheduling shows a good way of recovering from disruptions, and the risk analysis shows an effective way of maximizing return under such situations.
format Article
author Sarker, Ruhul
Essam, Daryl
Kamrul Hasan, S.M.
Karim, A.N. Mustafizul
author_facet Sarker, Ruhul
Essam, Daryl
Kamrul Hasan, S.M.
Karim, A.N. Mustafizul
author_sort Sarker, Ruhul
title Managing risk in production scheduling under uncertain disruption
title_short Managing risk in production scheduling under uncertain disruption
title_full Managing risk in production scheduling under uncertain disruption
title_fullStr Managing risk in production scheduling under uncertain disruption
title_full_unstemmed Managing risk in production scheduling under uncertain disruption
title_sort managing risk in production scheduling under uncertain disruption
publisher Cambridge University Press
publishDate 2015
url http://irep.iium.edu.my/48683/1/%2335_AIEDAM-paper.pdf
http://irep.iium.edu.my/48683/
http://journals.cambridge.org/abstract_S0890060415000323
_version_ 1643613406168612864
score 13.211869

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