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Transferring object allocation model over time
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AI
DOI：10.1080/0951192X.2014.964321.png)
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Abstract
En 中文
All the state-of-the-art techniques that try to solve packing problems focus on placing predetermined objects into predetermined areas. However, in real life the size and the number of objects to be placed may change in time and in a manufacturing process a new object allocation model should be built very quickly in order not to interrupt crucial processes. While classical methods begin the solution from scratch, the model transfer method proposed here utilises old allocation model to quickly adapt to the changing conditions in time. The results from this research show that the proposed method is much more efficient than the classical method as the parameters of the nesting problem change frequently.
Keywords:
nesting
genetic algorithms
transfer learning
Journal
I
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2.3K
Citations:
3.4K