English

Online Two-Dimensional Vector Packing with Advice

Data Structures and Algorithms 2022-04-22 v1

Abstract

We consider the online two-dimensional vector packing problem, showing a lower bound of 11/511/5 on the competitive ratio of any {\sc AnyFit} strategy for the problem. We provide strategies with competitive ratio max ⁣{2,6/(1+3tan(π/4γ/2))+ϵ}\max\!\left\{2,6\big/\big(1+3\tan(\pi/4-\gamma/2)\big)+\epsilon\right\} and logarithmic advice, for any instance where all the input vectors are restricted to have angles in the range [π/4γ/2,π/4+γ/2][\pi/4-\gamma/2,\pi/4+\gamma/2], for 0γ<π/30\leq\gamma<\pi/3 and max{5/2,4/(1+2tan(π/4γ/2))+ϵ}\max\left\{5/2,4\big/\big(1+2\tan(\pi/4-\gamma/2)\big)+\epsilon\right\} and logarithmic advice, for any instance where all the input vectors are restricted to have angles in the range [π/4γ/2,π/4+γ/2][\pi/4-\gamma/2,\pi/4+\gamma/2], for 0γπ/30\leq\gamma\leq\pi/3. In addition, we give a 5/25/2-competitive strategy also using logarithmic advice for the unrestricted vectors case. These results should be contrasted to the currently best competitive strategy, FirstFit, having competitive ratio~27/1027/10.

Keywords

Cite

@article{arxiv.2204.10322,
  title  = {Online Two-Dimensional Vector Packing with Advice},
  author = {Bengt J. Nilsson and Gordana Vujovic},
  journal= {arXiv preprint arXiv:2204.10322},
  year   = {2022}
}

Comments

15 pages, 4 figures. This an extended version of an article published in "Algorithms and Complexity. CIAC 2021." Lecture Notes in Computer Science, vol 12701. Springer, https://doi.org/10.1007

R2 v1 2026-06-24T10:55:08.301Z