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dc.creatorAlnouri, Sabla
dc.creatorStijepović, Mirko
dc.creatorLinke, Patrick
dc.creatorEl-Halwagi, Mahmoud
dc.date.accessioned2021-03-10T12:28:09Z
dc.date.available2021-03-10T12:28:09Z
dc.date.issued2014
dc.identifier.issn1974-9791
dc.identifier.urihttp://TechnoRep.tmf.bg.ac.rs/handle/123456789/2725
dc.description.abstractIn this work, an industrial city spatial representation that accounts for different plant layouts and arrangements is utilized for interplant water network synthesis. The problem has been previously tackled using deterministic optimization methods. This work employs a stochastic optimization approach, using genetic algorithms, for the design of spatially constrained interplant water networks using direct recycling techniques. The approach identifies well-performing solutions in an evolutionary manner, by generating populations of candidate solutions, then sampling regions that are associated with the highest performance probabilities. This ensures that only the fittest designs survive, when evaluating the network performance. A fitness objective that accounts for both freshwater and piping costs was utilized in the design evaluation stage. When compared to the results that have been obtained using deterministic optimization, trade-off trends between the optimum cost of the network and fresh/waste targets were manifested by means of stochastic optimization. Enhanced network performance was attained for a reduced total cost, at the expense of a certain deviation from fresh/waste targets.en
dc.publisherAidic Servizi Srl, Milano
dc.relationQatar National Research Fund (a member of Qatar Foundation) [NPRP 4-1191-2-468]
dc.rightsrestrictedAccess
dc.sourcePres 2014, 17th Conference on Process Integration, Modelling and Optimisation for Energy Saving and
dc.titleOptimal Design of Spatially Constrained Interplant Water Networks with Direct Recycling Techniques using Genetic Algorithmsen
dc.typeconferenceObject
dc.rights.licenseARR
dc.citation.epage+
dc.citation.other39: 457-+
dc.citation.spage457
dc.citation.volume39
dc.identifier.doi10.3303/CET1439077
dc.identifier.rcubconv_4609
dc.identifier.scopus2-s2.0-84908112004
dc.identifier.wos000346757600077
dc.type.versionpublishedVersion


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