Online bin packing with resource augmentation

Leah Epstein; Rob Van Stee

doi:10.1007/978-3-540-31833-0_4

Online bin packing with resource augmentation

Research output: Contribution to journal › Conference article › peer-review

Abstract

In competitive analysis, we usually do not put any restrictions on the computational complexity of online algorithms, although efficient algorithms are preferred. Thus if such an algorithm were given the entire input in advance, it could give an optimal solution (in exponential time). Instead of giving the algorithm more knowledge about the input, in this paper we consider the effects of giving an online bin packing algorithm larger bins than the offline algorithm it is compared to. We give new algorithms for this problem that combine items in bins in an unusual way and give bounds on their performance which improve upon the best possible bounded space algorithm. We also give general lower bounds for this problem which are nearly matching for bin sizes b ≥ 2.

Original language	English
Pages (from-to)	23-35
Number of pages	13
Journal	Lecture Notes in Computer Science
Volume	3351
DOIs	https://doi.org/10.1007/978-3-540-31833-0_4
State	Published - 2005
Externally published	Yes
Event	Second International Workshop on Approximation and Online Algorithms, WAOA 2004 - Bergen, Norway Duration: 14 Sep 2004 → 16 Sep 2004

Bibliographical note

Funding Information:
The first author’s research was supported by Israel Science Foundation (grant no. 250/01). The second author’s research was supported by the Netherlands Organization for Scientific Research (NWO), project number SION 612-061-000.

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science (all)

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10.1007/978-3-540-31833-0_4

Cite this

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title = "Online bin packing with resource augmentation",

abstract = "In competitive analysis, we usually do not put any restrictions on the computational complexity of online algorithms, although efficient algorithms are preferred. Thus if such an algorithm were given the entire input in advance, it could give an optimal solution (in exponential time). Instead of giving the algorithm more knowledge about the input, in this paper we consider the effects of giving an online bin packing algorithm larger bins than the offline algorithm it is compared to. We give new algorithms for this problem that combine items in bins in an unusual way and give bounds on their performance which improve upon the best possible bounded space algorithm. We also give general lower bounds for this problem which are nearly matching for bin sizes b ≥ 2.",

author = "Leah Epstein and {Van Stee}, Rob",

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doi = "10.1007/978-3-540-31833-0_4",

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AU - Epstein, Leah

AU - Van Stee, Rob

N1 - Funding Information: The first author’s research was supported by Israel Science Foundation (grant no. 250/01). The second author’s research was supported by the Netherlands Organization for Scientific Research (NWO), project number SION 612-061-000.

PY - 2005

Y1 - 2005

N2 - In competitive analysis, we usually do not put any restrictions on the computational complexity of online algorithms, although efficient algorithms are preferred. Thus if such an algorithm were given the entire input in advance, it could give an optimal solution (in exponential time). Instead of giving the algorithm more knowledge about the input, in this paper we consider the effects of giving an online bin packing algorithm larger bins than the offline algorithm it is compared to. We give new algorithms for this problem that combine items in bins in an unusual way and give bounds on their performance which improve upon the best possible bounded space algorithm. We also give general lower bounds for this problem which are nearly matching for bin sizes b ≥ 2.

AB - In competitive analysis, we usually do not put any restrictions on the computational complexity of online algorithms, although efficient algorithms are preferred. Thus if such an algorithm were given the entire input in advance, it could give an optimal solution (in exponential time). Instead of giving the algorithm more knowledge about the input, in this paper we consider the effects of giving an online bin packing algorithm larger bins than the offline algorithm it is compared to. We give new algorithms for this problem that combine items in bins in an unusual way and give bounds on their performance which improve upon the best possible bounded space algorithm. We also give general lower bounds for this problem which are nearly matching for bin sizes b ≥ 2.

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SN - 0302-9743

VL - 3351

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JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

T2 - Second International Workshop on Approximation and Online Algorithms, WAOA 2004

Y2 - 14 September 2004 through 16 September 2004

ER -

Online bin packing with resource augmentation

Abstract

Bibliographical note

ASJC Scopus subject areas

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