Online Sorting and Translational Packing of Convex Polygons

Fuente: arXiv
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Autori principali: Aamand, Anders, Abrahamsen, Mikkel, Beretta, Lorenzo, Kleist, Linda
Natura: Preprint
Pubblicazione: 2021
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author Aamand, Anders
Abrahamsen, Mikkel
Beretta, Lorenzo
Kleist, Linda
author_facet Aamand, Anders
Abrahamsen, Mikkel
Beretta, Lorenzo
Kleist, Linda
contents We investigate several online packing problems in which convex polygons arrive one by one and have to be placed irrevocably into a container, while the aim is to minimize the used space. Among other variants, we consider strip packing and bin packing, where the container is the infinite horizontal strip $[0,\infty)\times [0,1]$ or a collection of $1 \times 1$ bins, respectively. We draw interesting connections to the following online sorting problem OnlineSorting$[γ,n]$: We receive a stream of real numbers $s_1,\ldots,s_n$, $s_i\in[0,1]$, one by one. Each real must be placed in an array $A$ with $γn$ initially empty cells without knowing the subsequent reals. The goal is to minimize the sum of differences of consecutive reals in $A$. The offline optimum is to place the reals in sorted order so the cost is at most $1$. We show that for any $Δ$-competitive online algorithm of OnlineSorting$[γ,n]$, it holds that $γΔ\inΩ(\log n/\log \log n)$. We use this lower bound to prove the non-existence of competitive algorithms for various online translational packing problems of convex polygons, among them strip packing, bin packing and perimeter packing. This also implies that there exists no online algorithm that can pack all streams of pieces of diameter and total area at most $δ$ into the unit square. These results are in contrast to the case when the pieces are restricted to rectangles, for which competitive algorithms are known. Likewise, the offline versions of packing convex polygons have constant factor approximation algorithms. As a complement, we also include algorithms for both online sorting and translation-only online strip packing with non-trivial competitive ratios. Our algorithm for strip packing relies on a new technique for recursively subdividing the strip into parallelograms of varying height, thickness and slope.
format Preprint
id arxiv_https___arxiv_org_abs_2112_03791
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Online Sorting and Translational Packing of Convex Polygons
Aamand, Anders
Abrahamsen, Mikkel
Beretta, Lorenzo
Kleist, Linda
Computational Geometry
Data Structures and Algorithms
We investigate several online packing problems in which convex polygons arrive one by one and have to be placed irrevocably into a container, while the aim is to minimize the used space. Among other variants, we consider strip packing and bin packing, where the container is the infinite horizontal strip $[0,\infty)\times [0,1]$ or a collection of $1 \times 1$ bins, respectively. We draw interesting connections to the following online sorting problem OnlineSorting$[γ,n]$: We receive a stream of real numbers $s_1,\ldots,s_n$, $s_i\in[0,1]$, one by one. Each real must be placed in an array $A$ with $γn$ initially empty cells without knowing the subsequent reals. The goal is to minimize the sum of differences of consecutive reals in $A$. The offline optimum is to place the reals in sorted order so the cost is at most $1$. We show that for any $Δ$-competitive online algorithm of OnlineSorting$[γ,n]$, it holds that $γΔ\inΩ(\log n/\log \log n)$. We use this lower bound to prove the non-existence of competitive algorithms for various online translational packing problems of convex polygons, among them strip packing, bin packing and perimeter packing. This also implies that there exists no online algorithm that can pack all streams of pieces of diameter and total area at most $δ$ into the unit square. These results are in contrast to the case when the pieces are restricted to rectangles, for which competitive algorithms are known. Likewise, the offline versions of packing convex polygons have constant factor approximation algorithms. As a complement, we also include algorithms for both online sorting and translation-only online strip packing with non-trivial competitive ratios. Our algorithm for strip packing relies on a new technique for recursively subdividing the strip into parallelograms of varying height, thickness and slope.
title Online Sorting and Translational Packing of Convex Polygons
topic Computational Geometry
Data Structures and Algorithms
url https://arxiv.org/abs/2112.03791