Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/5024
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dc.contributor.authorThomas, Jayaen_US
dc.contributor.authorChaudhari, Narendra S.en_US
dc.date.accessioned2022-03-17T01:00:00Z-
dc.date.accessioned2022-03-17T15:36:32Z-
dc.date.available2022-03-17T01:00:00Z-
dc.date.available2022-03-17T15:36:32Z-
dc.date.issued2014-
dc.identifier.citationThomas, J., & Chaudhari, N. S. (2014). A new metaheuristic genetic-based placement algorithm for 2D strip packing. Journal of Industrial Engineering International, 10(1) doi:10.1007/s40092-014-0047-9en_US
dc.identifier.issn1735-5702-
dc.identifier.otherEID(2-s2.0-84991771236)-
dc.identifier.urihttps://doi.org/10.1007/s40092-014-0047-9-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/5024-
dc.description.abstractGiven a container of fixed width, infinite height and a set of rectangular block, the 2D-strip packing problem consists of orthogonally placing all the rectangles such that the height is minimized. The position is subject to confinement of no overlapping of blocks. The problem is a complex NP-hard combinatorial optimization, thus a heuristic based on genetic algorithm is proposed to solve it. In this paper, we give a hybrid approach which combined genetic encoding and evolution scheme with the proposed placement approach. Such a combination resulted in better population evolution and faster solution convergence to optimal. The approach is subjected to a comprehensive test using benchmark instances. The computation results validate the solution and the effectiveness of the approach. © 2014, The Author(s).en_US
dc.language.isoenen_US
dc.publisherSpringerOpenen_US
dc.sourceJournal of Industrial Engineering Internationalen_US
dc.titleA new metaheuristic genetic-based placement algorithm for 2D strip packingen_US
dc.typeJournal Articleen_US
dc.rights.licenseAll Open Access, Gold, Green-
Appears in Collections:Department of Computer Science and Engineering

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