Sequential Vector Packing

We introduce a novel variant of the well known d-dimensional bin (or vector) packing problem. Given a sequence of non-negative d-dimensional vectors, the goal is to pack these into as few bins as possible of smallest possible size. In the classical problem the bin size vector is given and the sequen...

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Published inCombinatorics, Algorithms, Probabilistic and Experimental Methodologies Vol. 4614; pp. 12 - 23
Main Authors Cieliebak, Mark, Hall, Alexander, Jacob, Riko, Nunkesser, Marc
Format Book Chapter
LanguageEnglish
Published Germany Springer Berlin / Heidelberg 2007
Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
Online AccessGet full text
ISBN9783540744498
3540744495
ISSN0302-9743
1611-3349
DOI10.1007/978-3-540-74450-4_2

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Abstract We introduce a novel variant of the well known d-dimensional bin (or vector) packing problem. Given a sequence of non-negative d-dimensional vectors, the goal is to pack these into as few bins as possible of smallest possible size. In the classical problem the bin size vector is given and the sequence can be partitioned arbitrarily. We study a variation where the vectors have to be packed in the order in which they arrive and the bin size vector can be chosen once in the beginning. This setting gives rise to two combinatorial problems: One in which we want to minimize the number of used bins for a given total bin size and one in which we want to minimize the total bin size for a given number of bins. We prove that both problems are ${\mathcal{NP}}$ -hard and propose an LP based bicriteria $(\frac1{\varepsilon}, \frac1{1-\varepsilon})$ -approximation algorithm. We give a 2-approximation algorithm for the version with bounded number of bins. Furthermore, we investigate properties of natural greedy algorithms, and present an easy to implement heuristic, which is fast and performs well in practice.
AbstractList We introduce a novel variant of the well known d-dimensional bin (or vector) packing problem. Given a sequence of non-negative d-dimensional vectors, the goal is to pack these into as few bins as possible of smallest possible size. In the classical problem the bin size vector is given and the sequence can be partitioned arbitrarily. We study a variation where the vectors have to be packed in the order in which they arrive and the bin size vector can be chosen once in the beginning. This setting gives rise to two combinatorial problems: One in which we want to minimize the number of used bins for a given total bin size and one in which we want to minimize the total bin size for a given number of bins. We prove that both problems are ${\mathcal{NP}}$ -hard and propose an LP based bicriteria $(\frac1{\varepsilon}, \frac1{1-\varepsilon})$ -approximation algorithm. We give a 2-approximation algorithm for the version with bounded number of bins. Furthermore, we investigate properties of natural greedy algorithms, and present an easy to implement heuristic, which is fast and performs well in practice.
Author Hall, Alexander
Nunkesser, Marc
Jacob, Riko
Cieliebak, Mark
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Notes Original Abstract: We introduce a novel variant of the well known d-dimensional bin (or vector) packing problem. Given a sequence of non-negative d-dimensional vectors, the goal is to pack these into as few bins as possible of smallest possible size. In the classical problem the bin size vector is given and the sequence can be partitioned arbitrarily. We study a variation where the vectors have to be packed in the order in which they arrive and the bin size vector can be chosen once in the beginning. This setting gives rise to two combinatorial problems: One in which we want to minimize the number of used bins for a given total bin size and one in which we want to minimize the total bin size for a given number of bins. We prove that both problems are \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}${\mathcal{NP}}$\end{document}-hard and propose an LP based bicriteria \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$(\frac1{\varepsilon}, \frac1{1-\varepsilon})$\end{document}-approximation algorithm. We give a 2-approximation algorithm for the version with bounded number of bins. Furthermore, we investigate properties of natural greedy algorithms, and present an easy to implement heuristic, which is fast and performs well in practice.
Work partially supported by European Commission - Fet Open project DELIS IST-001907 Dynamically Evolving Large Scale Information Systems, for which funding in Switzerland is provided by SBF grant 03.0378-1.
OCLC 184937572
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Snippet We introduce a novel variant of the well known d-dimensional bin (or vector) packing problem. Given a sequence of non-negative d-dimensional vectors, the goal...
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StartPage 12
SubjectTerms Approximation Algorithm
Assembly Line Balance
Integer Linear Programming Formulation
Resource Augmentation
Vector Packing
Title Sequential Vector Packing
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