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

http://hdl.handle.net/10609/90879
Full metadata record
DC FieldValueLanguage
dc.contributor.authorFerone, Daniele-
dc.contributor.authorGruler, Aljoscha-
dc.contributor.authorFesta, Paola-
dc.contributor.authorJuan Pérez, Ángel Alejandro-
dc.date.accessioned2019-01-30T12:16:39Z-
dc.date.available2019-01-30T12:16:39Z-
dc.date.issued2016-12-
dc.identifier.citationFerone, D., Gruler, A., Festa, P. & Juan, A.A. (2016). Combining simulation with a GRASP metaheuristic for solving the permutation flow-shop problem with stochastic processing times. Winter Simulation Conference (WSC). Proceedings, 2016(), 2205-2215. doi: 10.1109/WSC.2016.7822262-
dc.identifier.isbn9781509044863-
dc.identifier.issn1558-4305MIAR
-
dc.identifier.urihttp://hdl.handle.net/10609/90879-
dc.description.abstractGreedy Randomized Adaptive Search Procedures (GRASP) are among the most popular metaheuristics for the solution of combinatorial optimization problems. While GRASP is a relatively simple and efficient framework to deal with deterministic problem settings, many real-life applications experience a high level of uncertainty concerning their input variables or even their optimization constraints. When properly combined with the right metaheuristic, simulation (in any of its variants) can be an effective way to cope with this uncertainty. In this paper, we present a simheuristic algorithm that integrates Monte Carlo simulation into a GRASP framework to solve the permutation flow shop problem (PFSP) with random processing times. The PFSP is a well-known problem in the supply chain management literature, but most of the existing work considers that processing times of tasks in machines are deterministic and known in advance, which in some real-life applications (e.g., project management) is an unrealistic assumption.en
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherWinter Simulation Conference (WSC). Proceedings-
dc.relation.ispartofWinter Simulation Conference (WSC). Proceedings, 2016-
dc.relation.ispartofseriesWinter Simulation Conference, Washington D.C., EUA, 11-14, desembre de 2016-
dc.relation.urihttps://ieeexplore.ieee.org/document/7822262-
dc.relation.urihttps://www.informs-sim.org/wsc16papers/192.pdf-
dc.rights(c) Author/s & (c) Journal-
dc.subjectstochastic processesen
dc.subjectoptimizationen
dc.subjectuncertaintyen
dc.subjectrandom variablesen
dc.subjectprobability distributionen
dc.subjectroutingen
dc.subjectmathematical modelen
dc.subjectprocesos estocásticoses
dc.subjectincertidumbrees
dc.subjectvariables aleatoriases
dc.subjectdistribución de probabilidades
dc.subjectenrutamientoes
dc.subjectmodelo matemáticoes
dc.subjectoptimizaciónes
dc.subjectprocessos estocàsticsca
dc.subjectoptimitzacióca
dc.subjectincertesaca
dc.subjectvariables aleatòriesca
dc.subjectdistribució de probabilitatca
dc.subjectenrutamentca
dc.subjectmodel matemàticca
dc.subject.lcshAlgorithmsen
dc.titleCombining simulation with a GRASP metaheuristic for solving the permutation flow-shop problem with stochastic processing times-
dc.typeinfo:eu-repo/semantics/conferenceObject-
dc.audience.mediatorTheme areasen
dc.subject.lcshesAlgorismesca
dc.subject.lcshesAlgoritmoses
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccess-
dc.identifier.doi10.1109/WSC.2016.7822262-
dc.relation.projectIDinfo:eu-repo/grantAgreement/TRA2013-48180-C3-P-
dc.relation.projectIDinfo:eu-repo/grantAgreement/TRA2015-71883-REDT-
dc.relation.projectIDinfo:eu-repo/grantAgreement/2014-CTP-00001-
Appears in Collections:Articles

Files in This Item:
There are no files associated with this item.

Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.