Please use this identifier to cite or link to this item: https://doi.org/10.1007/s00170-003-1789-5
DC FieldValue
dc.titleOptimisation of multi-pass milling using genetic algorithm and genetic simulated annealing
dc.contributor.authorWang, Z.G.
dc.contributor.authorWong, Y.S.
dc.contributor.authorRahman, M.
dc.date.accessioned2014-06-17T06:30:01Z
dc.date.available2014-06-17T06:30:01Z
dc.date.issued2004-11
dc.identifier.citationWang, Z.G., Wong, Y.S., Rahman, M. (2004-11). Optimisation of multi-pass milling using genetic algorithm and genetic simulated annealing. International Journal of Advanced Manufacturing Technology 24 (9-10) : 727-732. ScholarBank@NUS Repository. https://doi.org/10.1007/s00170-003-1789-5
dc.identifier.issn02683768
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/61017
dc.description.abstractThe selection of optimal machining parameters plays an important part in computer-aided manufacturing. The optimisation of machining parameters is still the subject of many studies. Genetic algorithm (GA) and simulated annealing (SA) have been applied to many difficult combinatorial optimisation problems with certain strengths and weaknesses. In this paper, genetic simulated annealing (GSA), which is a hybrid of GA and SA, is used to determine optimal machining parameters for milling operations. For comparison, basic GA is also chosen as another optimisation method. An application example that has previously been solved using geometric programming (GP) method is presented. The results indicate that GSA is more efficient than GA and GP in the application of optimisation.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s00170-003-1789-5
dc.sourceScopus
dc.subjectGenetic algorithm
dc.subjectGenetic simulated annealing
dc.subjectMilling
dc.typeArticle
dc.contributor.departmentMECHANICAL ENGINEERING
dc.description.doi10.1007/s00170-003-1789-5
dc.description.sourcetitleInternational Journal of Advanced Manufacturing Technology
dc.description.volume24
dc.description.issue9-10
dc.description.page727-732
dc.description.codenIJATE
dc.identifier.isiut000224889400013
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