Show simple item record

dc.contributor.authorDraude, S
dc.contributor.authorKeedwell, E
dc.contributor.authorKapelan, Z
dc.contributor.authorHiscock, R
dc.date.accessioned2022-06-06T10:48:54Z
dc.date.issued2022-05-06
dc.date.updated2022-06-06T09:55:42Z
dc.description.abstractEffective functioning of sewer systems is critical for the everyday life of people in the urban environment. This is achieved, among other things, by the means of regular, planned maintenance of these systems. A large water utility would normally have several maintenance teams (or crews) at their disposal who can perform related jobs at different locations in the company area and with different levels of priority. This paper presents a new methodology for the optimisation of related maintenance schedules resulting in clear prioritisation of the ordering of maintenance tasks for crews. The scheduling problem is formulated as a multi-objective optimisation problem with the following three objectives, namely the minimisation of the total maintenance cost, the minimisation of travel times of maintenance teams and the maximisation of the job's priority score, all over a pre-defined scheduling horizon. The optimisation problem is solved using the Nondominated Sorting Genetic Algorithm-II (NSGA-II) optimisation method. The results obtained from a real-life UK case study demonstrate that the new methodology can determine optimal, low-cost maintenance schedules in a computationally efficient manner when compared to the corresponding existing company schedules. Daily productivity of maintenance teams in terms of number of jobs completed improved by 26% when the methodology was applied to scheduling in the case study. Given this, the method has the potential to be applied within water utilities and the water utility Welsh Water (Dŵr Cymru Welsh Water (DCWW)) is currently implementing it into their systems.en_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.identifier.citationVol. 24 (3), pp. 574–589en_GB
dc.identifier.doihttps://doi.org/10.2166/hydro.2022.149
dc.identifier.grantnumberEP/L016214/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/129844
dc.identifierORCID: 0000-0003-3650-6487 (Keedwell, Ed)
dc.identifierScopusID: 8367205700 (Keedwell, Ed)
dc.language.isoenen_GB
dc.publisherIWA Publishingen_GB
dc.rights© 2022 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectmulti-objective optimisationen_GB
dc.subjectplanned maintenance schedulingen_GB
dc.subjectsewer systemen_GB
dc.titleMulti-objective optimisation of sewer maintenance schedulingen_GB
dc.typeArticleen_GB
dc.date.available2022-06-06T10:48:54Z
dc.identifier.issn1464-7141
dc.descriptionThis is the final version. Available on open access from IWA Publishing via the DOI in this recorden_GB
dc.descriptionData availability statement: Data cannot be made publicly available; readers should contact the corresponding author for details.en_GB
dc.identifier.eissn1465-1734
dc.identifier.journalJournal of Hydroinformaticsen_GB
dc.relation.ispartofJournal of Hydroinformatics
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2022-04-15
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2022-05-06
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2022-06-06T10:46:25Z
refterms.versionFCDVoR
refterms.dateFOA2022-06-06T10:49:06Z
refterms.panelBen_GB
refterms.dateFirstOnline2022-05-06


Files in this item

This item appears in the following Collection(s)

Show simple item record

© 2022 The Authors.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2022 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).