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# Introduction
Libnest2D is a library and framework for the 2D bin packaging problem.
Inspired from the [SVGNest](svgnest.com) Javascript library the project is
built from scratch in C++11. The library is written with a policy that it should
be usable out of the box with a very simple interface but has to be customizable
to the very core as well. The algorithms are defined in a header only fashion
with templated geometry types. These geometries can have custom or already
existing implementation to avoid copying or having unnecessary dependencies.
A default backend is provided if the user of the library just wants to use it
out of the box without additional integration. This backend is reasonably
fast and robust, being built on top of boost geometry and the
[polyclipping](http://www.angusj.com/delphi/clipper.php) library. Usage of
this default backend implies the dependency on these packages but its header
only as well.
This software is currently under construction and lacks a throughout
documentation and some essential algorithms as well. At this stage it works well
for rectangles and convex closed polygons without considering holes and
concavities.
Holes and non-convex polygons will be usable in the near future as well. The
no fit polygon based placer module combined with the first fit selection
strategy is now used in the [Slic3r](https://github.com/prusa3d/Slic3r)
application's arrangement feature. It uses local optimization techniques to find
the best placement of each new item based on some features of the arrangement.
In the near future I would like to use machine learning to evaluate the
placements and (or) the order if items in which they are placed and see what
results can be obtained. This is a different approach than that of SVGnest which
uses genetic algorithms to find better and better selection orders. Maybe the
two approaches can be combined as well.
# References
- [SVGNest](https://github.com/Jack000/SVGnest)
- [An effective heuristic for the two-dimensional irregular
bin packing problem](http://www.cs.stir.ac.uk/~goc/papers/EffectiveHueristic2DAOR2013.pdf)
- [Complete and robust no-fit polygon generation for the irregular stock cutting problem](https://www.sciencedirect.com/science/article/abs/pii/S0377221706001639)
- [Applying Meta-Heuristic Algorithms to the Nesting
Problem Utilising the No Fit Polygon](http://www.graham-kendall.com/papers/k2001.pdf)
- [A comprehensive and robust procedure for obtaining the nofit polygon
using Minkowski sums](https://www.sciencedirect.com/science/article/pii/S0305054806000669)
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