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dc.creatorPetrović, Milica
dc.creatorMiljković, Zoran
dc.creatorBabić, Bojan
dc.date.accessioned2023-02-25T19:53:52Z
dc.date.available2023-02-25T19:53:52Z
dc.date.issued2012
dc.identifier.isbn978-86-7892-419-4
dc.identifier.urihttps://machinery.mas.bg.ac.rs/handle/123456789/4626
dc.description.abstractIn any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations.sr
dc.language.isoensr
dc.publisherNovi Sad : Faculty of Technical Sciencessr
dc.relationinfo:eu-repo/grantAgreement/MESTD/Technological Development (TD or TR)/35004/RS//sr
dc.rightsopenAccesssr
dc.rights.urihttps://creativecommons.org/share-your-work/public-domain/cc0/
dc.sourceProceedings of the 11th International Scientific Conference MMA 2012 – Advanced Production Technologies, Novi Sad, 20-21 September 2012sr
dc.subjectGenetic algorithms (GA)sr
dc.subjectSimulated annealing (SA)sr
dc.subjectOperation sequencingsr
dc.subjectComputer-aided process planning (CAPP)sr
dc.subjectOptimizationsr
dc.titleOptimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approachsr
dc.typeconferenceObjectsr
dc.rights.licenseCC0sr
dc.rights.holderProf. Ilija Ćosićsr
dc.citation.epage288
dc.citation.rankM33
dc.citation.spage285
dc.identifier.fulltexthttp://machinery.mas.bg.ac.rs/bitstream/id/11126/MMA2012_Proceedings.pdf
dc.identifier.rcubhttps://hdl.handle.net/21.15107/rcub_machinery_4626
dc.type.versionpublishedVersionsr


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