Improved Approximations for Translational Packing of Convex Polygons

TL;DR

This paper introduces improved polynomial-time approximation algorithms for two-dimensional convex polygon packing problems, enhancing previous guarantees and addressing open questions in container minimization and bin packing.

Contribution

It develops new approximation algorithms with better guarantees for convex polygon packing, including special cases and progress toward an O(1)-approximation for arbitrary polygons.

Findings

Enhanced approximation guarantees for polygon packing problems

Efficient algorithms for special cases of polygon bin packing

Progress toward an O(1)-approximation for general convex polygons

Abstract

Optimal packing of objects in containers is a critical problem in various real-life and industrial applications. This paper investigates the two-dimensional packing of convex polygons without rotations, where only translations are allowed. We study different settings depending on the type of containers used, including minimizing the number of containers or the size of the container based on an objective function. Building on prior research in the field, we develop polynomial-time algorithms with improved approximation guarantees upon the best-known results by Alt, de Berg and Knauer, as well as Aamand, Abrahamsen, Beretta and Kleist, for problems such as Polygon Area Minimization, Polygon Perimeter Minimization, Polygon Strip Packing, and Polygon Bin Packing. Our approach utilizes a sequence of object transformations that allows sorting by height and orientation, thus enhancing the effectiveness of shelf packing algorithms for polygon packing problems. In addition, we present efficient approximation algorithms for special cases of the Polygon Bin Packing problem, progressing toward solving an open question concerning an O(1)-approximation algorithm for arbitrary polygons.