Show simple item record

Article

dc.creatorPérez González, Paz 
dc.creatorFramiñán Torres, José Manuel 
dc.date.accessioned2015-03-16T10:43:10Z
dc.date.available2015-03-16T10:43:10Z
dc.date.issued2015
dc.identifier.issn0020-7543es
dc.identifier.urihttp://hdl.handle.net/11441/23490
dc.description.abstractThis paper focuses onto a situation arising in most real-life manufacturing environments when scheduling has to be performed periodically. In such a scenario, different scheduling policies can be adopted, being perhaps the most common to assume that, once a set of jobs has been scheduled, their schedule cannot be modified (‘frozen’ schedule). This implies that, when the next set of jobs is to be scheduled, the resources may not be fully available. Another option is assuming that the schedule of the previously scheduled jobs can be modified as long as it does not violate their due date, which has been already possibly committed to the customer. This policy leads to a so-called multi-agent scheduling problem. The goal of this paper is to discern when each policy is more suitable for the case of a permutation flowshop with common due dates. To do so, we carry out an extensive computational study in a test bed specifically designed to control the main factors affecting the policies, so we analyse the solution space of the underlying scheduling problems. The results indicate that, when the due date of the committed jobs is tight, the multi-agent approach does not pay off in view of the difficulty of finding feasible solutions. Moreover, in such cases, the policy of ‘freezing’ the schedule of the jobs leads to a very simple scheduling problem with many good/acceptable solutions. In contrast, when the due date has a medium/high slack, the multi-agent approach is substantially better. Nevertheless, in this latter case, in order to perceive the full advantage of this policy, powerful solution procedures have to be designed, as the structure of the solution space of the latter problem makes extremely hard to find optimal/good solutions.es
dc.description.sponsorshipMinisterio de Ciencia e Innovación (España)es
dc.formatapplication/pdfes
dc.language.isoenges
dc.relation.ispartofInternational Journal of Production Research, In Presses
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectpermutation flowshopes
dc.subjectschedulinges
dc.titleAssessing scheduling policies in a permutation flowshop with common due dateses
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Organización Industrial y Gestión de Empresas Ies
dc.relation.publisherversionhttp://dx.doi.org/10.1080/00207543.2014.994077es
dc.relation.publisherversionhttp://dx.doi.org/10.1080/00207543.2014.994077
dc.identifier.doi10.1080/00207543.2014.994077
dc.identifier.idushttps://idus.us.es/xmlui/handle/11441/23490
dc.contributor.funderMinisterio de Ciencia e Innovación (MICIN). España

FilesSizeFormatViewDescription
IJPR2015_Vopen.pdf386.4KbIcon   [PDF] View/Open  

This item appears in the following collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as: Attribution-NonCommercial-NoDerivatives 4.0 Internacional