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 in | Combinatorics, Algorithms, Probabilistic and Experimental Methodologies Vol. 4614; pp. 12 - 23 | 
|---|---|
| Main Authors | , , , | 
| Format | Book Chapter | 
| Language | English | 
| Published | 
        Germany
          Springer Berlin / Heidelberg
    
        2007
     Springer Berlin Heidelberg  | 
| Series | Lecture Notes in Computer Science | 
| Subjects | |
| Online Access | Get full text | 
| ISBN | 9783540744498 3540744495  | 
| ISSN | 0302-9743 1611-3349  | 
| DOI | 10.1007/978-3-540-74450-4_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. | 
    
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| 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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| DOI | 10.1007/978-3-540-74450-4_2 | 
    
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| Editor | Paterson, Mike Chen, Bo Zhang, Guochuan  | 
    
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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.  | 
    
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| PublicationSeriesTitle | Lecture Notes in Computer Science | 
    
| PublicationSubtitle | First International Symposium, ESCAPE 2007, Hangzhou, China, April 7-9, 2007, Revised Selected Papers | 
    
| PublicationTitle | Combinatorics, Algorithms, Probabilistic and Experimental Methodologies | 
    
| PublicationYear | 2007 | 
    
| Publisher | Springer Berlin / Heidelberg Springer Berlin Heidelberg  | 
    
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| RelatedPersons | Kleinberg, Jon M. Mattern, Friedemann Nierstrasz, Oscar Steffen, Bernhard Kittler, Josef Vardi, Moshe Y. Weikum, Gerhard Sudan, Madhu Naor, Moni Mitchell, John C. Terzopoulos, Demetri Pandu Rangan, C. Kanade, Takeo Hutchison, David Tygar, Doug  | 
    
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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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| SubjectTerms | Approximation Algorithm Assembly Line Balance Integer Linear Programming Formulation Resource Augmentation Vector Packing  | 
    
| Title | Sequential Vector Packing | 
    
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