Sustainable sequencing of N jobs on one machine: A fuzzy approach

Paul, SK

Sustainable sequencing of N jobs on one machine: A fuzzy approach

Paul, SK

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Publication Type:: Journal Article
Citation:: International Journal of Services and Operations Management, 2013, 15 (1), pp. 44 - 57
Issue Date:: 2013-04-22

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Field	Value	Language
dc.contributor.author	Paul, SK https://orcid.org/0000-0001-9523-179X	en_US
dc.date.issued	2013-04-22	en_US
dc.identifier.citation	International Journal of Services and Operations Management, 2013, 15 (1), pp. 44 - 57	en_US
dc.identifier.issn	1744-2370	en_US
dc.identifier.uri	http://hdl.handle.net/10453/117179
dc.description.abstract	Sequencing of jobs on one machine is a very common problem in scheduling. Several factors have to be taken into consideration to make the sequencing more realistic. In this paper, a fuzzy inference system is developed to tackle the uncertainty of variables in a sequencing problem. Arrival order, processing time, due date, slack time remaining, critical ratio, queue ratio and slack time remaining per operation, are considered as input variables and priority of jobs is considered as output variable. Multiple objectives are fulfilled as priority is obtained from the aggregated optimised result of individual rule developed in a rule editor. A job with higher priority is given more preferences in sequencing. MATLAB fuzzy logic toolbox is used to develop the model. A numerical example is presented to explain the approach. Copyright © 2013 Inderscience Enterprises Ltd.	en_US
dc.relation.ispartof	International Journal of Services and Operations Management	en_US
dc.relation.isbasedon	10.1504/IJSOM.2013.053254	en_US
dc.subject.classification	Business & Management	en_US
dc.title	Sustainable sequencing of N jobs on one machine: A fuzzy approach	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	15	en_US
utslib.for	1503 Business and Management	en_US
utslib.for	1505 Marketing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Management Discipline
utslib.copyright.status	closed_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	15	en_US

Abstract:

Sequencing of jobs on one machine is a very common problem in scheduling. Several factors have to be taken into consideration to make the sequencing more realistic. In this paper, a fuzzy inference system is developed to tackle the uncertainty of variables in a sequencing problem. Arrival order, processing time, due date, slack time remaining, critical ratio, queue ratio and slack time remaining per operation, are considered as input variables and priority of jobs is considered as output variable. Multiple objectives are fulfilled as priority is obtained from the aggregated optimised result of individual rule developed in a rule editor. A job with higher priority is given more preferences in sequencing. MATLAB fuzzy logic toolbox is used to develop the model. A numerical example is presented to explain the approach. Copyright © 2013 Inderscience Enterprises Ltd.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/117179