Comparing online algorithms for bin packing problems
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 wor...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Epstein, Leah [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2009 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC 2009 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of scheduling - Springer US, 1998, 15(2009), 1 vom: 12. Sept., Seite 13-21 |
|---|---|
| Übergeordnetes Werk: |
volume:15 ; year:2009 ; number:1 ; day:12 ; month:09 ; pages:13-21 |
| Links: |
|---|
| DOI / URN: |
10.1007/s10951-009-0129-5 |
|---|
| Katalog-ID: |
OLC2070216837 |
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| 520 | |a 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. | ||
| 650 | 4 | |a Online algorithms | |
| 650 | 4 | |a Relative worst-order ratio | |
| 650 | 4 | |a Bin packing | |
| 650 | 4 | |a Bin covering | |
| 650 | 4 | |a Bin coloring | |
| 650 | 4 | |a Class-constrained bin packing | |
| 650 | 4 | |a Open-end bin packing | |
| 700 | 1 | |a Favrholdt, Lene M. |4 aut | |
| 700 | 1 | |a Kohrt, Jens S. |4 aut | |
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10.1007/s10951-009-0129-5 doi (DE-627)OLC2070216837 (DE-He213)s10951-009-0129-5-p DE-627 ger DE-627 rakwb eng 650 VZ 3,2 11 ssgn 85.03$jMethoden und Techniken der Betriebswirtschaft bkl 54.80$jAngewandte Informatik bkl 31.80$jAngewandte Mathematik bkl Epstein, Leah verfasserin aut Comparing online algorithms for bin packing problems 2009 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2009 Abstract The relative worst-order ratio is a measure of the quality of online algorithms. In contrast to the competitive ratio, this measure compares two online algorithms directly instead of using an intermediate comparison with an optimal offline algorithm. In this paper, we apply the relative worst-order ratio to online algorithms for several common variants of the bin packing problem. We mainly consider pairs of algorithms that are not distinguished by the competitive ratio and show that the relative worst-order ratio prefers the intuitively better algorithm of each pair. Online algorithms Relative worst-order ratio Bin packing Bin covering Bin coloring Class-constrained bin packing Open-end bin packing Favrholdt, Lene M. aut Kohrt, Jens S. aut Enthalten in Journal of scheduling Springer US, 1998 15(2009), 1 vom: 12. Sept., Seite 13-21 (DE-627)302724184 (DE-600)1492486-9 (DE-576)080987206 1094-6136 nnns volume:15 year:2009 number:1 day:12 month:09 pages:13-21 https://doi.org/10.1007/s10951-009-0129-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_20 GBV_ILN_24 GBV_ILN_26 GBV_ILN_70 GBV_ILN_4029 GBV_ILN_4317 85.03$jMethoden und Techniken der Betriebswirtschaft VZ 106417320 (DE-625)106417320 54.80$jAngewandte Informatik VZ 106417967 (DE-625)106417967 31.80$jAngewandte Mathematik VZ 106419005 (DE-625)106419005 AR 15 2009 1 12 09 13-21 |
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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. © Springer Science+Business Media, LLC 2009 |
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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. © Springer Science+Business Media, LLC 2009 |
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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. © Springer Science+Business Media, LLC 2009 |
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