Class of optimization problems that involve determining efficient ways to arrange (pack) objects into containers. Packing problems can be tackled using discrete mathematical methods, physics systems (as seen in Nervous System's Kinematics series), and even genetic algorithms and machine learning.
Has major applications in digital fabrication, manufacturing, and shipping logistics where material and space usage is directly related to costs. In 2D, packing/nesting problem solutions are useful for minimizing waste material in sheet goods like plywood and sheet steel, even for hobbyists. In 3D these solutions are useful for fitting as many objects as possible into 3D printer build envelopes (see article from Sculpteo).
Related terms:
Articles:
- Packing problems on Wikipedia
- Random space filling of the plane by Paul Bourke
- Optimal Packing from Data Genetics
- Circle Packing on Wolfram MathWorld
- Bin packing problem on Wikipedia
- Sphere packing on Wikipedia
- Close-packing of equal spheres on Wikipedia
- Packing Problems - collection of papers by Ernesto Birgin and collaborators
Notable tools:
Videos:
- Coding Challenge #50.1: Animated Circle Packing - Part 1 by Daniel Shiffman