Abstract
Good management of industrial processes lead to optimization problems. Some of them are NP-hard and needs special algorithms to be solved. One such problem is cutting stock problem (CSP). The accurate and fast cutting out with less possible waste is very important element from the working process. The aim is to cut 2D items from rectangular stock, minimizing the waste. The problem is very difficult and the most of the authors solve the simplified version of the problem when the items are rectangular. The computational time increases exponentially when the number of items increase. Finding the optimal solution for large-sized problems for a reasonable time is impossible. Therefore exact algorithms and traditional numerical methods can be apply only on very small problems, less than 100 items. We propose an approximate algorithm which solve the problem when the items are polygons.
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Acknowledgements
Work presented here is partially supported by the Bulgarian National Scientific Fund under Grants DFNI I02/20 “Efficient Parallel Algorithms for Large Scale Computational Problems” and DFNI DN 02/10 “New Instruments for Data Mining and their Modeling”.
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Evtimov, G., Fidanova, S. (2018). 2D Optimal Cutting Problem. In: Georgiev, K., Todorov, M., Georgiev, I. (eds) Advanced Computing in Industrial Mathematics. Studies in Computational Intelligence, vol 728. Springer, Cham. https://doi.org/10.1007/978-3-319-65530-7_4
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DOI: https://doi.org/10.1007/978-3-319-65530-7_4
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