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dc.contributor.authorShafiee, Alireza
dc.contributor.authorArab, Mobin
dc.contributor.authorLai, Zhiping
dc.contributor.authorLiu, Zongwen
dc.contributor.authorAbbas, Ali
dc.date.accessioned2017-01-02T08:42:36Z
dc.date.available2017-01-02T08:42:36Z
dc.date.issued2016-06-25
dc.identifier.citationShafiee A, Arab M, Lai Z, Liu Z, Abbas A (2016) Automated process flowsheet synthesis for membrane processes using genetic algorithm: role of crossover operators. 26th European Symposium on Computer Aided Process Engineering: 1201–1206. Available: http://dx.doi.org/10.1016/B978-0-444-63428-3.50205-8.
dc.identifier.issn1570-7946
dc.identifier.doi10.1016/B978-0-444-63428-3.50205-8
dc.identifier.urihttp://hdl.handle.net/10754/622175
dc.description.abstractIn optimization-based process flowsheet synthesis, optimization methods, including genetic algorithms (GA), are used as advantageous tools to select a high performance flowsheet by ‘screening’ large numbers of possible flowsheets. In this study, we expand the role of GA to include flowsheet generation through proposing a modified Greedysub tour crossover operator. Performance of the proposed crossover operator is compared with four other commonly used operators. The proposed GA optimizationbased process synthesis method is applied to generate the optimum process flowsheet for a multicomponent membrane-based CO2 capture process. Within defined constraints and using the random-point crossover, CO2 purity of 0.827 (equivalent to 0.986 on dry basis) is achieved which results in improvement (3.4%) over the simplest crossover operator applied. In addition, the least variability in the converged flowsheet and CO2 purity is observed for random-point crossover operator, which approximately implies closeness of the solution to the global optimum, and hence the consistency of the algorithm. The proposed crossover operator is found to improve the convergence speed of the algorithm by 77.6%.
dc.description.sponsorshipThis work is supported in part by a King Abdullah University of Science and Technology (KAUST) CRG Award.
dc.publisherElsevier BV
dc.relation.urlhttp://dx.doi.org/10.1016/B978-0-444-63428-3.50205-8
dc.subjectGenetic algorithm
dc.subjectcrossover operator
dc.subjectcarbon capture
dc.subjectprocess flowsheet synthesis
dc.subjectgas separation
dc.subjectmembrane
dc.titleAutomated process flowsheet synthesis for membrane processes using genetic algorithm: role of crossover operators
dc.typeBook Chapter
dc.contributor.departmentAdvanced Membranes and Porous Materials Research Center
dc.contributor.departmentChemical and Biological Engineering Program
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Division
dc.identifier.journal26th European Symposium on Computer Aided Process Engineering
dc.contributor.institutionSchool of Chemical and Biomolecular Engineering, The University of Sydney, Sydney, Australia
kaust.personLai, Zhiping
dc.date.published-online2016-06-25
dc.date.published-print2016


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