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dc.contributor.author | Montes, Daniel | es_ES |
dc.contributor.author | Pitarch, José Luis | es_ES |
dc.contributor.author | de Prada, César | es_ES |
dc.date.accessioned | 2024-11-22T19:06:25Z | |
dc.date.available | 2024-11-22T19:06:25Z | |
dc.date.issued | 2023 | es_ES |
dc.identifier.issn | 1570-7946 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/212164 | |
dc.description.abstract | [EN] Scheduling often involves making decisions in presence of uncertainty, which governs the pricing of raw materials, energy, resource availability, demands, etc. A common approach to incorporate uncertainty in the decision-making process is using two-stage stochastic formulations. Unfortunately, the mathematical complexity of the resulting problems grows exponentially with the number of uncertainty scenarios, which is further complicated by the presence of binary variables The authors have recently proposed a method using the so-called Similarity Index for discrete-time two-stage scheduling problems that enable scenario-based decomposition. This paper extends this method for scheduling problems formulated on a continuous-time basis. The fundamental idea is to use the Similarity Index to meet non-anticipation in the binary variables and Progressive Hedging on the continuous ones. The proposal is tested on a literature case study that consists of a multiproduct plant with a single processing unit. The combined SI-PH decomposition managed to solve the problem much faster than its monolithic counterpart. | es_ES |
dc.description.sponsorship | These results are funded by the Spanish MCIN/AEI as part of the a-CIDiT (PID2021-123654OB-C31, PID2021-123654OB-C32) and LOCPU (PID2020-116585GB-I00) research projects. The first author has received financial support from the 2020 call for pre-doctoral contracts of the University of Valladolid and Banco Santander. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Computer Aided Chemical Engineering | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Similarity Index | es_ES |
dc.subject | Progressive Hedging | es_ES |
dc.subject | Optimization under uncertainty | es_ES |
dc.subject.classification | INGENIERIA DE SISTEMAS Y AUTOMATICA | es_ES |
dc.title | Extending the SI Decomposition to Continuous-Time Two-Stage Scheduling Problems | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/B978-0-443-15274-0.50080-9 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-116585GB-I00/ES/APRENDIZAJE, CONTROL OPTIMO Y PLANIFICACION BAJO INCERTIDUMBRE EN APLICACIONES INDUSTRIALES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-123654OB-C31/ES/OPTIMIZACION DISTRIBUIDA PARA ESTIMACION DE PARAMETROS, DE ESTADOS Y RECONCILIACION DINAMICA EN GEMELOS DIGITALES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-123654OB-C32/ES/MODELOS BASADOS EN DATOS Y ACTUALIZACION DE MODELOS PARA GEMELOS DIGITALES/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.description.bibliographicCitation | Montes, D.; Pitarch, JL.; De Prada, C. (2023). Extending the SI Decomposition to Continuous-Time Two-Stage Scheduling Problems. Computer Aided Chemical Engineering. 52:499-504. https://doi.org/10.1016/B978-0-443-15274-0.50080-9 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/B978-0-443-15274-0.50080-9 | es_ES |
dc.description.upvformatpinicio | 499 | es_ES |
dc.description.upvformatpfin | 504 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 52 | es_ES |
dc.relation.pasarela | S\511513 | es_ES |
dc.contributor.funder | Banco Santander | es_ES |
dc.contributor.funder | Universidad de Valladolid | es_ES |
dc.contributor.funder | AGENCIA ESTATAL DE INVESTIGACION | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | Ministerio de Ciencia e Innovación | es_ES |
dc.subject.ods | 09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación | es_ES |