Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76745
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dc.contributorDepartment of Electronic and Information Engineering-
dc.creatorFok, KY-
dc.creatorCheng, CT-
dc.creatorGanganath, N-
dc.creatorIu, HHC-
dc.creatorTse, CK-
dc.date.accessioned2018-06-05T06:46:50Z-
dc.date.available2018-06-05T06:46:50Z-
dc.identifier.isbn978-1-5386-4881-0 (electronic)en_US
dc.identifier.isbn978-1-5386-4882-7 (print on demand(PoD))en_US
dc.identifier.urihttp://hdl.handle.net/10397/76745-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication Fok, K. Y., Cheng, C. T., Ganganath, N., Iu, H. H. C., & Chi, K. T. (2018, May). Accelerating 3D Printing Process Using an Extended Ant Colony Optimization Algorithm. In 2018 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). IEEE is available at https://dx.doi.org/10.1109/ISCAS.2018.8351113en_US
dc.subjectAnt colony optimizationen_US
dc.subjectAdditive manufacturingen_US
dc.subject3D printingen_US
dc.subjectUndirected rural postman probleen_US
dc.titleAccelerating 3d printing process using an extended ant colony optimization algorithmen_US
dc.typeConference Paperen_US
dc.identifier.spage1en_US
dc.identifier.epage5en_US
dc.identifier.doi10.1109/ISCAS.2018.8351113en_US
dcterms.abstractAnt colony optimization (ACO) algorithms have been widely adopted in solving combinatorial problems, like the traveling salesman problem (TSP). Nevertheless, with a proper transformation to TSP, ACO is capable of solving undirected rural postman problems (URPP) as well. In fact, nozzle path planning problems in 3D printing can be represented as URPP. Therefore, in this work, ACO is utilized as a URPP solver to accelerate the printing process in fused deposition modeling applications. Furthermore, mechanisms which exploit unique properties in 3D models are proposed to further extend the ACO in the above optimization process. These mechanisms are capable of accelerating ACO by adaptively adjusting its number of iterations on-the-fly. Simulation results using real-life 3D models show that the proposed extensions can accelerate ACO without affecting the quality of its solutions significantly.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitation2018 International Symposium on Circuits and Systems (ISCAS), Florence, Italy, 27-30 May 2018, p. 1-5-
dcterms.issued2018-
dc.relation.conferenceIEEE International Symposium on Circuits and Systems [ISCAS]en_US
dc.identifier.eissn2379-447Xen_US
dc.identifier.rosgroupid2017004534-
dc.description.ros2017-2018 > Academic research: refereed > Refereed conference paper-
dc.description.validate201806 bcrcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera0189-n03en_US
dc.description.pubStatusPublisheden_US
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