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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Thomas, Jaya | en_US |
dc.contributor.author | Chaudhari, Narendra S. | en_US |
dc.date.accessioned | 2022-03-17T01:00:00Z | - |
dc.date.accessioned | 2022-03-17T15:36:32Z | - |
dc.date.available | 2022-03-17T01:00:00Z | - |
dc.date.available | 2022-03-17T15:36:32Z | - |
dc.date.issued | 2014 | - |
dc.identifier.citation | Thomas, 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/s40092-014-0047-9 | en_US |
dc.identifier.issn | 1735-5702 | - |
dc.identifier.other | EID(2-s2.0-84991771236) | - |
dc.identifier.uri | https://doi.org/10.1007/s40092-014-0047-9 | - |
dc.identifier.uri | https://dspace.iiti.ac.in/handle/123456789/5024 | - |
dc.description.abstract | Given 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.iso | en | en_US |
dc.publisher | SpringerOpen | en_US |
dc.source | Journal of Industrial Engineering International | en_US |
dc.title | A new metaheuristic genetic-based placement algorithm for 2D strip packing | en_US |
dc.type | Journal Article | en_US |
dc.rights.license | All Open Access, Gold, Green | - |
Appears in Collections: | Department of Computer Science and Engineering |
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