Improved online hypercube packing
Xin Han, Deshi Ye, Yong Zhou
TL;DR
This paper presents improved online algorithms for hypercube packing, achieving better asymptotic competitive ratios for square and cube packing by adapting techniques from one-dimensional bin packing.
Contribution
It introduces a new framework for online hypercube packing based on Super Harmonic, resulting in tighter upper bounds for competitive ratios.
Findings
Square packing upper bound improved to 2.1439
Cube packing upper bound improved to 2.6852
Framework adapts 1D bin packing techniques to multidimensional hypercubes
Abstract
In this paper, we study online multidimensional bin packing problem when all items are hypercubes. Based on the techniques in one dimensional bin packing algorithm Super Harmonic by Seiden, we give a framework for online hypercube packing problem and obtain new upper bounds of asymptotic competitive ratios. For square packing, we get an upper bound of 2.1439, which is better than 2.24437. For cube packing, we also give a new upper bound 2.6852 which is better than 2.9421 by Epstein and van Stee.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsOptimization and Packing Problems · Optimization and Search Problems · Advanced Manufacturing and Logistics Optimization