Two-Stage Stochastic Scheduling of a Multiproduct Pipeline System using Similarity Index Decomposition

[EN] Multiproduct pipelines are crucial for delivering substantial quantities of refined oil products from major supply centers to clients within a nearby geographical area. Despite the significant infrastructure investment, the associated transportation costs are markedly lower than those incurred...

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Autores: Montes, Daniel A., de Prada, César, Pitarch, José Luis|||0000-0001-5356-6321
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/222485
Acceso en línea:https://riunet.upv.es/handle/10251/222485
Access Level:acceso abierto
Palabra clave:Decomposition
MILP
Uncertainty
PlanningOil &amp
Gas
09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación
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spelling Two-Stage Stochastic Scheduling of a Multiproduct Pipeline System using Similarity Index DecompositionMontes, Daniel A.de Prada, CésarPitarch, José Luis|||0000-0001-5356-6321DecompositionMILPUncertaintyPlanningOil &ampGas09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación[EN] Multiproduct pipelines are crucial for delivering substantial quantities of refined oil products from major supply centers to clients within a nearby geographical area. Despite the significant infrastructure investment, the associated transportation costs are markedly lower than those incurred with traditional delivery trucks. However, the scheduling of these systems presents a formidable challenge, requiring meticulous planning of pumping runs well in advance to meet the anticipated demands of clients. In this work, we enhance an existing literature model of a multiproduct pipeline system by introducing uncertainty in the customer demand. The problem is then addressed via a two-stage stochastic formulation. The typical drawback with stochastic formulations is the high computational burden required. To address this challenge, we adapt the so-called Similarity Index decomposition, resulting in a 28-fold improvement in CPU time while achieving equivalent solutions compared to solving the full-space problem.These results are funded by the Spanish MCIN/AEI/10.13039 /501100011033/, as part of the a-CIDiT (PID2021- 123654OB-C31) and LOCPU (PID2020-116585GB-I00) research projects. The first author has received financial support from the 2020 call of pre-doctoral contracts of the University of Valladolid and Banco Santander.ElsevierDepartamento de Ingeniería de Sistemas y AutomáticaEscuela Técnica Superior de Ingeniería Aeroespacial y Diseño IndustrialInstituto Universitario de Automática e Informática IndustrialAGENCIA ESTATAL DE INVESTIGACIONAgencia Estatal de InvestigaciónMinisterio de Ciencia e InnovaciónRepositorio Institucional de la Universitat Politècnica de València Riunet20242024-01-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/222485reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PID2020-116585GB-I00 APRENDIZAJE, CONTROL OPTIMO Y PLANIFICACION BAJO INCERTIDUMBRE EN APLICACIONES INDUSTRIALESAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2021-123654OB-C32 MODELOS BASADOS EN DATOS Y ACTUALIZACION DE MODELOS PARA GEMELOS DIGITALESopen accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/2224852026-06-13T07:49:27Z
dc.title.none.fl_str_mv Two-Stage Stochastic Scheduling of a Multiproduct Pipeline System using Similarity Index Decomposition
title Two-Stage Stochastic Scheduling of a Multiproduct Pipeline System using Similarity Index Decomposition
spellingShingle Two-Stage Stochastic Scheduling of a Multiproduct Pipeline System using Similarity Index Decomposition
Montes, Daniel A.
Decomposition
MILP
Uncertainty
PlanningOil &amp
Gas
09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación
title_short Two-Stage Stochastic Scheduling of a Multiproduct Pipeline System using Similarity Index Decomposition
title_full Two-Stage Stochastic Scheduling of a Multiproduct Pipeline System using Similarity Index Decomposition
title_fullStr Two-Stage Stochastic Scheduling of a Multiproduct Pipeline System using Similarity Index Decomposition
title_full_unstemmed Two-Stage Stochastic Scheduling of a Multiproduct Pipeline System using Similarity Index Decomposition
title_sort Two-Stage Stochastic Scheduling of a Multiproduct Pipeline System using Similarity Index Decomposition
dc.creator.none.fl_str_mv Montes, Daniel A.
de Prada, César
Pitarch, José Luis|||0000-0001-5356-6321
author Montes, Daniel A.
author_facet Montes, Daniel A.
de Prada, César
Pitarch, José Luis|||0000-0001-5356-6321
author_role author
author2 de Prada, César
Pitarch, José Luis|||0000-0001-5356-6321
author2_role author
author
dc.contributor.none.fl_str_mv Departamento de Ingeniería de Sistemas y Automática
Escuela Técnica Superior de Ingeniería Aeroespacial y Diseño Industrial
Instituto Universitario de Automática e Informática Industrial
AGENCIA ESTATAL DE INVESTIGACION
Agencia Estatal de Investigación
Ministerio de Ciencia e Innovación
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Decomposition
MILP
Uncertainty
PlanningOil &amp
Gas
09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación
topic Decomposition
MILP
Uncertainty
PlanningOil &amp
Gas
09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación
description [EN] Multiproduct pipelines are crucial for delivering substantial quantities of refined oil products from major supply centers to clients within a nearby geographical area. Despite the significant infrastructure investment, the associated transportation costs are markedly lower than those incurred with traditional delivery trucks. However, the scheduling of these systems presents a formidable challenge, requiring meticulous planning of pumping runs well in advance to meet the anticipated demands of clients. In this work, we enhance an existing literature model of a multiproduct pipeline system by introducing uncertainty in the customer demand. The problem is then addressed via a two-stage stochastic formulation. The typical drawback with stochastic formulations is the high computational burden required. To address this challenge, we adapt the so-called Similarity Index decomposition, resulting in a 28-fold improvement in CPU time while achieving equivalent solutions compared to solving the full-space problem.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/222485
url https://riunet.upv.es/handle/10251/222485
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PID2020-116585GB-I00 APRENDIZAJE, CONTROL OPTIMO Y PLANIFICACION BAJO INCERTIDUMBRE EN APLICACIONES INDUSTRIALES
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2021-123654OB-C32 MODELOS BASADOS EN DATOS Y ACTUALIZACION DE MODELOS PARA GEMELOS DIGITALES
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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