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An Enhanced Estimation of Distribution Algorithm for Energy-Efficient Job-Shop Scheduling Problems with Transportation Constraints

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An Enhanced Estimation of Distribution Algorithm for Energy-Efficient Job-Shop Scheduling Problems with Transportation Constraints

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dc.contributor.author Dai, Min es_ES
dc.contributor.author Zhang, Ziwei es_ES
dc.contributor.author Giret Boggino, Adriana Susana es_ES
dc.contributor.author Salido, Miguel A. es_ES
dc.date.accessioned 2020-06-03T05:53:11Z
dc.date.available 2020-06-03T05:53:11Z
dc.date.issued 2019-05-31 es_ES
dc.identifier.uri http://hdl.handle.net/10251/145113
dc.description.abstract [EN] Nowadays, the manufacturing industry faces the challenge of reducing energy consumption and the associated environmental impacts. Production scheduling is an effective approach for energy-savings management. During the entire workshop production process, both the processing and transportation operations consume large amounts of energy. To reduce energy consumption, an energy-efficient job-shop scheduling problem (EJSP) with transportation constraints was proposed in this paper. First, a mixed-integer programming model was established to minimize both the comprehensive energy consumption and makespan in the EJSP. Then, an enhanced estimation of distribution algorithm (EEDA) was developed to solve the problem. In the proposed algorithm, an estimation of distribution algorithm was employed to perform the global search and an improved simulated annealing algorithm was designed to perform the local search. Finally, numerical experiments were implemented to analyze the performance of the EEDA. The results showed that the EEDA is a promising approach and that it can solve EJSP effectively and efficiently. es_ES
dc.description.sponsorship This work was supported by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (No. 17KJB460018), the Innovation Foundation for Science and Technology of Yangzhou University (No. 2016CXJ020 and No. 2017CXJ018), Science and Technology Project of Yangzhou under (No. YZ2017278), Research Topics of Teaching Reform of Yangzhou University under (No. YZUJX2018-28B), and the Spanish Government (No. TIN2016-80856-R and No. TIN2015-65515-C4-1-R). es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation Natural Science Research of Jiangsu Higher Education Institutions of China/No. 17KJB460018 es_ES
dc.relation YZU/2016CXJ020 es_ES
dc.relation YZU/2017CXJ018 es_ES
dc.relation Yangzhou Science and Technology Bureau/No. YZ2017278 es_ES
dc.relation YZU/No. YZUJX2018-28B es_ES
dc.relation MINISTERIO DE ECONOMIA Y EMPRESA/TIN2015-65515-C4-1-R es_ES
dc.relation AEI/TIN2016-80856-R es_ES
dc.relation.ispartof Sustainability es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Job-shop scheduling es_ES
dc.subject Energy consumption es_ES
dc.subject Estimation of distribution algorithm es_ES
dc.subject Transportation time es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title An Enhanced Estimation of Distribution Algorithm for Energy-Efficient Job-Shop Scheduling Problems with Transportation Constraints es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/su11113085 es_ES
dc.rights.accessRights Abierto 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 Dai, M.; Zhang, Z.; Giret Boggino, AS.; Salido, MA. (2019). An Enhanced Estimation of Distribution Algorithm for Energy-Efficient Job-Shop Scheduling Problems with Transportation Constraints. Sustainability. 11(11):1-23. https://doi.org/10.3390/su11113085 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/su11113085 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 23 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 11 es_ES
dc.description.issue 11 es_ES
dc.identifier.eissn 2071-1050 es_ES
dc.relation.pasarela S\389608 es_ES
dc.contributor.funder Yangzhou University es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Ministerio de Economía y Empresa es_ES
dc.contributor.funder Yangzhou Science and Technology Bureau es_ES
dc.contributor.funder Natural Science Research of Jiangsu Higher Education Institutions of China es_ES


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