Comparing online algorithms for bin packing problems

Leah Epstein; Lene M. Favrholdt; Jens S. Kohrt

doi:10.1007/s10951-009-0129-5

Comparing online algorithms for bin packing problems

Leah Epstein, Lene M. Favrholdt, Jens S. Kohrt

Department of Mathematics

Research output: Contribution to journal › Article › peer-review

Abstract

The relative worst-order ratio is a measure of the quality of online algorithms. In contrast to the competitive ratio, this measure compares two online algorithms directly instead of using an intermediate comparison with an optimal offline algorithm. In this paper, we apply the relative worst-order ratio to online algorithms for several common variants of the bin packing problem. We mainly consider pairs of algorithms that are not distinguished by the competitive ratio and show that the relative worst-order ratio prefers the intuitively better algorithm of each pair.

Original language	English
Pages (from-to)	13-21
Number of pages	9
Journal	Journal of Scheduling
Volume	15
Issue number	1
DOIs	https://doi.org/10.1007/s10951-009-0129-5
State	Published - Feb 2012

Keywords

Bin coloring
Bin covering
Bin packing
Class-constrained bin packing
Online algorithms
Open-end bin packing
Relative worst-order ratio

ASJC Scopus subject areas

Software
General Engineering
Management Science and Operations Research
Artificial Intelligence

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10.1007/s10951-009-0129-5

Cite this

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KW - Bin covering

KW - Bin packing

KW - Class-constrained bin packing

KW - Online algorithms

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Comparing online algorithms for bin packing problems

Abstract

Keywords

ASJC Scopus subject areas

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