Abstract
Every day optimization problems arise in our life and industry. Many of them require huge amount of calculations and need special type of algorithms to be solved. An important industrial problem is cutting stock problem (CSP). Cutting with less possible waste is significant in some industries. The aim of this work is to cut 2D items from rectangular stock, minimizing the waste. Even the simplified version of the problem, when the items are rectangular is NP hard. When the number of items increases, the computational time increases exponentially. It is impossible to find the optimal solution for a reasonable time. Only for very small problems the exact algorithms and traditional numerical methods can be applied. We propose a stochastic algorithm which solves the problem, when the items are irregular polygons.
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Acknowledgment
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). Heuristic Algorithm for 2D Cutting Stock Problem. In: Lirkov, I., Margenov, S. (eds) Large-Scale Scientific Computing. LSSC 2017. Lecture Notes in Computer Science(), vol 10665. Springer, Cham. https://doi.org/10.1007/978-3-319-73441-5_37
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DOI: https://doi.org/10.1007/978-3-319-73441-5_37
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