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Improve memory management through tree size estimation #3

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@ktnr

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@ktnr

The required capacity is not known in advance, therefore we need an estimation of the (sub)tree size.

////this->tree.m_vertices.reserve(250000000);

////this->tree.m_vertices.reserve(250000000);

Consider using the following relevant parameters:

  • The epsilon parameter from Clautiaux, F., Carlier, J., & Moukrim, A. (2007). A new exact method for the two-dimensional orthogonal packing problem. European Journal of Operational Research, 183(3), 1196-1211, in combination with
  • the distribution of items sizes, whereas the hardest instances are those where all items are smaller than half of the bin's width and height,
  • item count, and
  • the number of normal pattern placements points (which correlates with the homogeneity of items).

Generally, (significant) overestimation is fine, but might degrade performance for smaller instances.

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