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Extending the SI Decomposition to Continuous-Time Two-Stage Scheduling Problems

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Extending the SI Decomposition to Continuous-Time Two-Stage Scheduling Problems

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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


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