1 research outputs found
COMPACT: Concurrent or Ordered Matrix-based Packing Arrangement Computation Technique
Packing optimization is a prevalent problem that necessitates robust and
efficient algorithms that are also simple to implement. One group of approaches
is the raster methods, which rely on approximating the objects with pixelated
representations. Although they are versatile in treating irregular geometries,
the raster methods received limited attention in solving problems involving
rotatable objects, where available studies generally analyze only right-angled
rotations. In addition, raster approximation allows the use of unique
performance metrics and indirect consideration of constraints, which have not
been exploited in the literature. This study presents the new Concurrent or
Ordered Matrix-based Packing Arrangement Computation Technique (COMPACT). The
method relies on raster representations of the objects that can be rotated by
arbitrary angles, unlike the right-angled rotation restrictions imposed in many
existing packing optimization studies based on raster methods. The raster
approximations are obtained through loop-free operations that improve
efficiency. Besides, a novel performance metric is introduced, which favors
efficient filling of the available space by maximizing the internal contact
between the objects as well as the contact between the objects and domain
boundaries. Moreover, the objective functions are exploited to discard overlap
and overflow constraints and enable the use of unconstrained optimization
methods. Several test problems involving concurrent and ordered packing of
multiple rectangular and circular objects into square bins are investigated.
The results show that the proposed technique performs effectively in
determining the packing arrangements.Comment: 13 pages, 9 figures, preprint submitted to Elsevie