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Rescheduling in job-shop problems for sustainable manufacturing systems

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Rescheduling in job-shop problems for sustainable manufacturing systems

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dc.contributor.author Salido Gregorio, Miguel Angel es_ES
dc.contributor.author Escamilla Fuster, Joan es_ES
dc.contributor.author Barber Sanchís, Federico es_ES
dc.contributor.author Giret Boggino, Adriana Susana es_ES
dc.date.accessioned 2018-06-21T04:21:26Z
dc.date.available 2018-06-21T04:21:26Z
dc.date.issued 2017 es_ES
dc.identifier.issn 0959-6526 es_ES
dc.identifier.uri http://hdl.handle.net/10251/104443
dc.description.abstract [EN] Manufacturing industries are faced with environmental challenges, so their industrial processes must be optimized in terms of both profitability and sustainability. Since most of these processes are dynamic, the previously obtained solutions cannot be valid after disruptions. This paper focuses on recovery in dynamic job-shop scheduling problems where machines can work at different rates. Machine speed scaling is an alternative framework to the on/off control framework for production scheduling. Thus, given a disruption, the main goal is to recover the original solution by rescheduling the minimum number of tasks. To this end, a new match-up technique is developed to determine the rescheduling zone and a feasible reschedule. Then, a memetic algorithm is proposed for finding a schedule that minimizes the energy consumption within the rescheduling zone but that also maintains the makespan constraint. An extensive study is carried out to analyze the behavior of our algorithms to recover the original solution and minimize the energy reduction in different benchmarks, which are taken from the OR-Library. The energy consumption and processing time of the tasks involved in the rescheduling zone will play an important role in determining the best match-up point and the optimized rescheduling. Upon a disruption, different rescheduling solutions can be obtained, all of which comply with the requirements but that have different values of energy consumption. The results proposed in this paper may be useful for application in real industries for energy-efficient production rescheduling. es_ES
dc.description.sponsorship This research has been supported by the Seventh Framework Programme under the research project TETRACOM-GA609491 and the Spanish Government under research projects TIN2013-46511-C2-1, TIN2015-65515-C4-1-R and TIN2016-80856-R. The authors wish to thank reviewers and editors for their positive comments to improve the quality of the paper. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation MINECO/TIN2015-65515-C4-1-R es_ES
dc.relation RWTH Aachen University-EC/609491 es_ES
dc.relation AEI/TIN2016-80856-R es_ES
dc.relation.ispartof Journal of Cleaner Production es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Manufacturing problem es_ES
dc.subject Multi-objective es_ES
dc.subject Rescheduling es_ES
dc.subject Memetic algorithm es_ES
dc.subject Energy consumption es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Rescheduling in job-shop problems for sustainable manufacturing systems es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.jclepro.2016.11.002 es_ES
dc.rights.accessRights Abierto es_ES
dc.date.embargoEndDate 2019-01-01 es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Salido Gregorio, MÁ.; Escamilla Fuster, J.; Barber Sanchís, F.; Giret Boggino, AS. (2017). Rescheduling in job-shop problems for sustainable manufacturing systems. Journal of Cleaner Production. 162(20):121-132. doi:10.1016/j.jclepro.2016.11.002 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1016/j.jclepro.2016.11.002 es_ES
dc.description.upvformatpinicio 121 es_ES
dc.description.upvformatpfin 132 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 162 es_ES
dc.description.issue 20 es_ES
dc.relation.pasarela S\320608 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Ministerio de Economía, Industria y Competitividad es_ES
dc.contributor.funder RWTH Aachen University es_ES
dc.contributor.funder European Commission


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