Publication:
Modified job shop scheduling via Taguchi method and genetic algorithm

cris.author.scopus-author-id 57218680605
cris.author.scopus-author-id 38561331300
cris.author.scopus-author-id 55860800560
cris.author.scopus-author-id 55669781700
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtualsource.department 97249ac5-6bf2-440d-b171-28ee875c9f9c
cris.virtualsource.department f706deee-19e1-46a5-a4e8-25c727ea8dbc
cris.virtualsource.department 6a3e88fe-0b4a-4e2d-ab74-7df2e6602317
dc.contributor.author Suhaila Saidat
dc.contributor.author Ahmad Kadri Junoh
dc.contributor.author Wan Zuki Azman Wan Muhamad
dc.contributor.author Zainab Yahya
dc.date.accessioned 2024-09-27T04:01:14Z
dc.date.available 2024-09-27T04:01:14Z
dc.date.issued 2022-02-01
dc.description.abstract To be in the competitive industrial world, industries required high quality, speed in completing the required work, and commitment to the delivery dates. One of the most important issues in the field of production management is the job shop scheduling problem (JSSP). In this paper, the researchers tried to solve JSSP of factory by presenting a method to improve the factory's production. Job shop scheduling (JSS) is a suitable method for solving these types of problems, which aims to improve the production flow through minimizing the whole operation time of the products. Moreover, considering the factory that depends on workers as same as machine, human factor should be considered while scheduling by using the workers' weightage, in order to improve the workers' working time flexibility in terms of their waiting time among their tasks by proposed model of JSS. In addition, the researchers proposed a new combination of weightage values by using Taguchi method, regarding to improve the workers' working time and using genetic algorithm (GA) to solve the proposed model of JSS. One of the factories which is located in Jordan, and it is considered as one of the important factories; nevertheless, it can cover the local demands hardly, and hence, it deserves to be as a study case for this research. The findings of the studies decreased the whole operation time of the products by saving 75 min for each production line and 90 min by using GA, and the proposed model improved the flexibility of the workers' working time in terms of their waiting times among their tasks.
dc.identifier.doi 10.1007/s00521-021-06504-7
dc.identifier.scopus 2-s2.0-85115132338
dc.identifier.uri https://hdl.handle.net/20.500.14170/4405
dc.language.iso en
dc.relation.grantno undefined
dc.relation.ispartof Neural Computing and Applications
dc.relation.ispartofseries Neural Computing and Applications
dc.relation.issn 09410643
dc.subject Genetic algorithm
dc.subject Human factor
dc.subject Job shop scheduling
dc.subject Taguchi method
dc.title Modified job shop scheduling via Taguchi method and genetic algorithm
dc.type Resource Types::text::journal::journal article
dspace.entity.type Publication
oaire.citation.endPage 1980
oaire.citation.issue 3
oaire.citation.startPage 1963
oaire.citation.volume 34
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.author.affiliation Irbid National University, Jordan
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
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person.identifier.orcid 0000-0002-7705-4707
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person.identifier.scopus-author-id 57218680605
person.identifier.scopus-author-id 38561331300
person.identifier.scopus-author-id 55860800560
person.identifier.scopus-author-id 55669781700
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