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dc.contributor.authorSadrossadat, Ehsan
dc.contributor.authorBasarir, Hakan
dc.contributor.authorLuo, Gunhao
dc.contributor.authorKarrech, Ali
dc.contributor.authorDurham, Richard
dc.contributor.authorFourie, Andy
dc.contributor.authorElchalakani, Mohamed
dc.date.accessioned2021-04-07T07:32:10Z
dc.date.available2021-04-07T07:32:10Z
dc.date.created2020-11-29T18:24:00Z
dc.date.issued2020
dc.identifier.issn0892-6875
dc.identifier.urihttps://hdl.handle.net/11250/2736487
dc.description.abstractIn order to achieve a successful cemented paste backfill (CPB) mixture design, multiple project requirements such as strength, flowability and cost should be met. For this achievement, the key design parameters, solid content (SD) and cement percentage (C), should be well adjusted. With increasing the amount of cement in the mixture, CPB strength and production cost increase together, whereas the workability decreases. In order to reduce the cost, more tailings can be added while keeping the cement amount the same but this will reduce both strength and workability. Therefore, CPB design is in fact a multi-objective optimisation problem. In this study, the particle swarm optimisation (PSO) algorithm is used to design CPB mixture meeting multiple objectives. PSO identifies the optimum set of SD and C yielding in desired strength and workability with a minimum cost. The proposed workflow can be a useful and practical for multiple decision making where CPB designers face strength-workability-cost paradox. In addition to reducing the number of trial experiments, the multi objective mixture design of CPB also provides the optimum use of materials to reduce the incurred costs and ensure cleaner and more sustainable production.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.titleMulti-objective mixture design of cemented paste backfill using particle swarm optimisation algorithmen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.volume153en_US
dc.source.journalMinerals Engineeringen_US
dc.identifier.doihttps://doi.org/10.1016/j.mineng.2020.106385
dc.identifier.cristin1853828
dc.description.localcodeThis article will not be available due to copyright restrictions (c) 2020 by Elsevieren_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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