Expand description
This crate solves the problem of “fitting smaller boxes inside of a larger box” using a three dimensional fitting algorithm.
The algorithm orthogonally packs the all the items into a minimum number of bins by leveraging a First Fit Decreasing greedy strategy, along with rotational optimizations.
§Usage:
use bin_packer_3d::bin::Bin;
use bin_packer_3d::item::Item;
use bin_packer_3d::packing_algorithm::packing_algorithm;
let deck = Item::new("deck", [2, 8, 12]);
let die = Item::new("die", [8, 8, 8]);
let items = vec![deck, deck, die, deck, deck];
let packed_items = packing_algorithm(Bin::new([8, 8, 12]), &items);
assert_eq!(packed_items, Ok(vec![vec!["deck", "deck", "deck", "deck"], vec!["die"]]));
§Limitations:
This algorithm solves a constrained version of the 3D bin packing problem. As such, we have the following limitations:
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The items we are packing, and the bins that we are packing them into, are limited to cuboid shapes.
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The items we are packing can be rotated in any direction, with the limitation that each edge must be parallel to the corresponding bin edge.
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As an NP-Hard problem, this algorithm does not attempt to find the optimal solution, but instead uses an approximation that runs with a time complexity of O(n^2)
§Acknowledgements:
The algorithm leverages a rotational optimization when packing items which are less than half the length of a bin’s side, as proposed in the paper titled “The Three-Dimensional Bin Packing Problem” (Martello, 1997), page 257: https://www.jstor.org/stable/pdf/223143.pdf
Modules§
- bin
- A struct representing the dimensions of the bin, which will be used for packing.
- error
- Defines an Error type and a Result type, which can be raised from the packing algorithm.
- item
- A struct representing the items we’ll be packing into the bin.
- packing_
algorithm - Defines the function that will be used for our packing algorithm.