Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injections

Autores
Cafaro, Vanina; Cafaro, Diego Carlos; Mendez, Carlos Alberto; Cerda, Jaime
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Pipeline networks are the shippers' first choice for carrying large volumes of refined petroleum productsfrom oil refineries to distant distribution terminals. Optimization approaches for solving the pipelinescheduling problem proceed in two hierarchical stages: the aggregate and the detailed planning steps.The aggregate plan determines the batch sizes, the sequence of batch injections, and the allocation ofbatches to customers. The subsequent stage refines the aggregate plan to find the detailed schedule ofbatch input and output operations. This paper presents a mixed-integer linear programming (MILP) formulationfor the detailed scheduling of multi-source pipelines that accounts for parallel batch injectionsand simultaneous product deliveries to multiple terminals. It overcomes a critical drawback of previousmodels that assume single source configurations. Modeling multi-source pipeline networks is a greatchallenge, requiring a completely revised approach. The new model finds cost-effective solutions withremarkable efficiency.
Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Cafaro, Diego Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Materia
Pipeline
Scheduling
Milp Model
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/9907

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spelling Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injectionsCafaro, VaninaCafaro, Diego CarlosMendez, Carlos AlbertoCerda, JaimePipelineSchedulingMilp Modelhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2Pipeline networks are the shippers' first choice for carrying large volumes of refined petroleum productsfrom oil refineries to distant distribution terminals. Optimization approaches for solving the pipelinescheduling problem proceed in two hierarchical stages: the aggregate and the detailed planning steps.The aggregate plan determines the batch sizes, the sequence of batch injections, and the allocation ofbatches to customers. The subsequent stage refines the aggregate plan to find the detailed schedule ofbatch input and output operations. This paper presents a mixed-integer linear programming (MILP) formulationfor the detailed scheduling of multi-source pipelines that accounts for parallel batch injectionsand simultaneous product deliveries to multiple terminals. It overcomes a critical drawback of previousmodels that assume single source configurations. Modeling multi-source pipeline networks is a greatchallenge, requiring a completely revised approach. The new model finds cost-effective solutions withremarkable efficiency.Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); ArgentinaFil: Cafaro, Diego Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); ArgentinaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); ArgentinaFil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); ArgentinaElsevier2015-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/9907Cafaro, Vanina; Cafaro, Diego Carlos; Mendez, Carlos Alberto; Cerda, Jaime; Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injections; Elsevier; Computers & Industrial Engineering; 88; 8-2015; 395-4090360-8352enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.cie.2015.07.022info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0360835215003253info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:06:24Zoai:ri.conicet.gov.ar:11336/9907instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:06:24.503CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injections
title Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injections
spellingShingle Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injections
Cafaro, Vanina
Pipeline
Scheduling
Milp Model
title_short Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injections
title_full Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injections
title_fullStr Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injections
title_full_unstemmed Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injections
title_sort Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injections
dc.creator.none.fl_str_mv Cafaro, Vanina
Cafaro, Diego Carlos
Mendez, Carlos Alberto
Cerda, Jaime
author Cafaro, Vanina
author_facet Cafaro, Vanina
Cafaro, Diego Carlos
Mendez, Carlos Alberto
Cerda, Jaime
author_role author
author2 Cafaro, Diego Carlos
Mendez, Carlos Alberto
Cerda, Jaime
author2_role author
author
author
dc.subject.none.fl_str_mv Pipeline
Scheduling
Milp Model
topic Pipeline
Scheduling
Milp Model
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Pipeline networks are the shippers' first choice for carrying large volumes of refined petroleum productsfrom oil refineries to distant distribution terminals. Optimization approaches for solving the pipelinescheduling problem proceed in two hierarchical stages: the aggregate and the detailed planning steps.The aggregate plan determines the batch sizes, the sequence of batch injections, and the allocation ofbatches to customers. The subsequent stage refines the aggregate plan to find the detailed schedule ofbatch input and output operations. This paper presents a mixed-integer linear programming (MILP) formulationfor the detailed scheduling of multi-source pipelines that accounts for parallel batch injectionsand simultaneous product deliveries to multiple terminals. It overcomes a critical drawback of previousmodels that assume single source configurations. Modeling multi-source pipeline networks is a greatchallenge, requiring a completely revised approach. The new model finds cost-effective solutions withremarkable efficiency.
Fil: Cafaro, Vanina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Cafaro, Diego Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
description Pipeline networks are the shippers' first choice for carrying large volumes of refined petroleum productsfrom oil refineries to distant distribution terminals. Optimization approaches for solving the pipelinescheduling problem proceed in two hierarchical stages: the aggregate and the detailed planning steps.The aggregate plan determines the batch sizes, the sequence of batch injections, and the allocation ofbatches to customers. The subsequent stage refines the aggregate plan to find the detailed schedule ofbatch input and output operations. This paper presents a mixed-integer linear programming (MILP) formulationfor the detailed scheduling of multi-source pipelines that accounts for parallel batch injectionsand simultaneous product deliveries to multiple terminals. It overcomes a critical drawback of previousmodels that assume single source configurations. Modeling multi-source pipeline networks is a greatchallenge, requiring a completely revised approach. The new model finds cost-effective solutions withremarkable efficiency.
publishDate 2015
dc.date.none.fl_str_mv 2015-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/9907
Cafaro, Vanina; Cafaro, Diego Carlos; Mendez, Carlos Alberto; Cerda, Jaime; Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injections; Elsevier; Computers & Industrial Engineering; 88; 8-2015; 395-409
0360-8352
url http://hdl.handle.net/11336/9907
identifier_str_mv Cafaro, Vanina; Cafaro, Diego Carlos; Mendez, Carlos Alberto; Cerda, Jaime; Optimization model for the operational-level scheduling of multi-source pipelines with parallel batch injections; Elsevier; Computers & Industrial Engineering; 88; 8-2015; 395-409
0360-8352
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cie.2015.07.022
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0360835215003253
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397