Abstract
This paper proposes a new Ant Colony Optimization (ACO) algorithm for the three-dimensional (3D) bin packing problem with guillotine cut constraint, which consists of packing a set of boxes into a 3D set of bins of variable dimensions. The algorithm is applied to a real-world problem in the steel industry. The retail steel cut consists on how to cut blocks of steel in order to satisfy the clients orders. The goal is to minimize the amount of scrap metal and consequently reduce the stock of steel blocks. The proposed ACO algorithm searches for the best orders of the boxes and it is guided by a heuristic that determines the position and orientation for the boxes. It was possible to reduce the amount of scrap metal by 90% and to reduce the usage of raw material by 25%.
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Silveira, M.E., Vieira, S.M., Da Costa Sousa, J.M. (2013). An ACO Algorithm for the 3D Bin Packing Problem in the Steel Industry. In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_55
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DOI: https://doi.org/10.1007/978-3-642-38577-3_55
Publisher Name: Springer, Berlin, Heidelberg
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