Please use this identifier to cite or link to this item: https://doi.org/10.1081/AMP-120022026
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dc.titleApplications of genetic algorithm in polymer science and engineering
dc.contributor.authorKasat, R.B.
dc.contributor.authorRay, A.K.
dc.contributor.authorGupta, S.K.
dc.date.accessioned2014-06-17T08:30:39Z
dc.date.available2014-06-17T08:30:39Z
dc.date.issued2003-05
dc.identifier.citationKasat, R.B., Ray, A.K., Gupta, S.K. (2003-05). Applications of genetic algorithm in polymer science and engineering. Materials and Manufacturing Processes 18 (3) : 523-532. ScholarBank@NUS Repository. https://doi.org/10.1081/AMP-120022026
dc.identifier.issn10426914
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/66461
dc.description.abstractIn the last several years, genetic algorithm (GA) has gained wide acceptance as a robust optimization algorithm in almost all areas of science and engineering. Polymer science and engineering is no exception. Researchers in this field have devoted considerable attention to the optimization of polymer production using objective functions and constraints that lead to products having desired material properties. Multiple-objective functions have been optimized simultaneously. An example is the minimization of the reaction time in a reactor (lower costs) while simultaneously minimizing the concentration of side products (that affect the properties of the product adversely). Several end-point constraints (equality or inequality) may also be present, as, e.g., obtaining polymer of a desired molecular weight. Again, this requirement stems from producing polymer having desired strength. Solving such problems usually result in Pareto sets. A variety of adaptations of GA have been developed to obtain optimal solutions for such complex problems. These adaptations can be used to advantage in other fields too. The applications of GA in areas of polymer science and engineering other than polymerization systems are few and far between, but this field is now maturing, and it is hoped that the future will see several newer applications.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1081/AMP-120022026
dc.sourceScopus
dc.subjectGenetic algorithm
dc.subjectMulti-objective optimization
dc.subjectOptimization
dc.subjectOptimization in polymer processing
dc.subjectOptimization in polymer reaction engineering
dc.subjectOptimization in polymer science and engineering
dc.subjectPareto sets
dc.subjectScheduling in polymers
dc.typeArticle
dc.contributor.departmentCHEMICAL & ENVIRONMENTAL ENGINEERING
dc.description.doi10.1081/AMP-120022026
dc.description.sourcetitleMaterials and Manufacturing Processes
dc.description.volume18
dc.description.issue3
dc.description.page523-532
dc.description.codenMMAPE
dc.identifier.isiut000184571500014
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