Deep learning-based initialization for object packing
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Publication date: 2018
Schedae Informaticae, 2018, Volume 27, pp. 9 - 17
https://doi.org/10.4467/20838476SI.18.001.10406Authors
Deep learning-based initialization for object packing
One of the most important optimization tasks in the industry at the current time is the object packing problem. Although several methods have been developed for the purpose of solving it, they are usually only able to optimize placement locally and as such are heavily dependent on the choice of the initial setting -- hence the need for trying out multiple possible starting points, which impacts algorithm running time. In this paper we present a neural network-based model which provides sensible starting points in a linear time.
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Information: Schedae Informaticae, 2018, Volume 27, pp. 9 - 17
Article type: Original article
Titles:
Deep learning-based initialization for object packing
Deep learning-based initialization for object packing
Faculty of Mathematics and Computer Science, Jagiellonian University ul. Łojasiewicza 6, 30-348 Kraków, Poland
Published at: 2018
Article status: Open
Licence: CC BY-NC-ND
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EnglishView count: 1889
Number of downloads: 1529