Near optimal objects packing through dimensional unfolding
The efficient packing of regular shaped two dimensional objects is the core problem of several kinds of industry such as steel, thin-film and paper. This special kind of packing problem consists in cutting small rectangular stripes of different length and width from bigger coiled rectangles of raw material by combining them in such a way that trim loss is as low as possible. Previous attempts to apply {open_quotes}exact{close_quotes} discrete optimization techniques such as Simplex Partial Columns Generation were not able to produce good cutting plans in large instances. We tackled this Roll Cutting Problem developing a new {open_quotes}dimension decomposition technique{close_quotes} that has been successfully experimented in a big steel industry first and then replicated in other steel and thin-film factories. This {open_quotes}unfolding{close_quotes} technique consists in splitting the overall search for good cutting plans in two separate graph search algorithms one for each physical dimension of the rectangles. Searching individually in each dimension improves the overall search strategy allowing the effective pruning of useless combinations. Experimental evidence of how dimensional splitting strengthens the overall search strategy is given.
- OSTI ID:
- 430895
- Report Number(s):
- CONF-960876-; TRN: 96:006521-0272
- Resource Relation:
- Conference: 13. National conference on artifical intelligence and the 8. Innovative applications of artificial intelligence conference, Portland, OR (United States), 4-8 Aug 1996; Other Information: PBD: 1996; Related Information: Is Part Of Proceedings of the thirteenth national conference on artificial intelligence and the eighth innovative applications of artificial intelligence conference. Volume 1 and 2; PB: 1626 p.
- Country of Publication:
- United States
- Language:
- English
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