Minimization of sewage network overflow

We are interested in the optimal control of sewage networks. It is of high public interest to minimize the overflow of sewage onto the streets and to the natural environment that may occur during periods of heavy rain. The assumption of linear flow in a discrete time setting has proven to be adequat...

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Authors: Joseph-Duran, Bernat, Jung, Michael N., Ocampo-Martínez, Carlos, Sager, Sebastian, Cembrano, Gabriela
Format: article
Status:Versión aceptada para publicación
Publication Date:2014
Country:España
Institution:Consejo Superior de Investigaciones Científicas (CSIC)
Repository:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/96997
Online Access:http://hdl.handle.net/10261/96997
Access Level:Open access
Keyword:CSO
Optimization
Optimal control
Sewer networks
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spelling Minimization of sewage network overflowJoseph-Duran, BernatJung, Michael N.Ocampo-Martínez, CarlosSager, SebastianCembrano, GabrielaCSOOptimizationOptimal controlSewer networksWe are interested in the optimal control of sewage networks. It is of high public interest to minimize the overflow of sewage onto the streets and to the natural environment that may occur during periods of heavy rain. The assumption of linear flow in a discrete time setting has proven to be adequate for the practical control of larger systems. However, the possibility of overflow introduces a nonlinear and nondifferentiable element to the formulation, by means of a maximum of linear terms. This particular challenge can be addressed by smoothing methods that result in a nonlinear program (NLP) or by logical constraints that result in a mixed integer linear program (MILP). We discuss both approaches and present a novel tailored branch-and-bound algorithm that outperforms competing methods from the literature for a set of realistic rain scenarios. © 2013 Springer Science+Business Media Dordrecht.This work has been partially funded by the EU Project EFFINET (FP7-ICT-2011-8- 318556) and DGR of Generalitat de Catalunya (SAC group Ref. 2009/SGR/1491). Financial support of the Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences and of the EU project EMBOCON under grant FP7-ICT-2009-4 248940 is gratefully acknowledged.Peer ReviewedSpringer NatureEuropean CommissionGeneralitat de CatalunyaConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2014201420142014info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Postprintinfo:eu-repo/semantics/acceptedVersionhttp://hdl.handle.net/10261/96997reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/FP7/318556info:eu-repo/grantAgreement/EC/FP7/248940http://dx.doi.org/10.1007/s11269-013-0468-zSíinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/969972026-05-22T06:33:51Z
dc.title.none.fl_str_mv Minimization of sewage network overflow
title Minimization of sewage network overflow
spellingShingle Minimization of sewage network overflow
Joseph-Duran, Bernat
CSO
Optimization
Optimal control
Sewer networks
title_short Minimization of sewage network overflow
title_full Minimization of sewage network overflow
title_fullStr Minimization of sewage network overflow
title_full_unstemmed Minimization of sewage network overflow
title_sort Minimization of sewage network overflow
dc.creator.none.fl_str_mv Joseph-Duran, Bernat
Jung, Michael N.
Ocampo-Martínez, Carlos
Sager, Sebastian
Cembrano, Gabriela
author Joseph-Duran, Bernat
author_facet Joseph-Duran, Bernat
Jung, Michael N.
Ocampo-Martínez, Carlos
Sager, Sebastian
Cembrano, Gabriela
author_role author
author2 Jung, Michael N.
Ocampo-Martínez, Carlos
Sager, Sebastian
Cembrano, Gabriela
author2_role author
author
author
author
dc.contributor.none.fl_str_mv European Commission
Generalitat de Catalunya
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv CSO
Optimization
Optimal control
Sewer networks
topic CSO
Optimization
Optimal control
Sewer networks
description We are interested in the optimal control of sewage networks. It is of high public interest to minimize the overflow of sewage onto the streets and to the natural environment that may occur during periods of heavy rain. The assumption of linear flow in a discrete time setting has proven to be adequate for the practical control of larger systems. However, the possibility of overflow introduces a nonlinear and nondifferentiable element to the formulation, by means of a maximum of linear terms. This particular challenge can be addressed by smoothing methods that result in a nonlinear program (NLP) or by logical constraints that result in a mixed integer linear program (MILP). We discuss both approaches and present a novel tailored branch-and-bound algorithm that outperforms competing methods from the literature for a set of realistic rain scenarios. © 2013 Springer Science+Business Media Dordrecht.
publishDate 2014
dc.date.none.fl_str_mv 2014
2014
2014
2014
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Postprint
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/96997
url http://hdl.handle.net/10261/96997
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/EC/FP7/318556
info:eu-repo/grantAgreement/EC/FP7/248940
http://dx.doi.org/10.1007/s11269-013-0468-z
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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