# [−][src]Crate bin_packer_3d

This crate solves the problem of "fitting smaller boxes inside of a larger box" using a three dimensional fitting algorithm.

The algorithm leverages a First Fit Decreasing greedy strategy, which some 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", [2.0, 8.0, 12.0]);
let die = Item::new("die", [8.0, 8.0, 8.0]);
let items = vec![deck.clone(), deck.clone(), die, deck.clone(), deck];

let packed_items = packing_algorithm(Bin::new([8.0, 8.0, 12.0]), &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:

• The items we are packing, and the bins that we are packing them into, are limited to cuboid shapes

• As an NP-Hard problem, this algorithm does not attempt to find the optimal solution

# 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): https://www.jstor.org/stable/pdf/223143.pdf, page 257

## 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.