Probabilistic alternatives for competitive analysis
Please always quote using this URN: urn:nbn:de:0297-zib-15131
- In the last 20 years competitive analysis has become the main tool for analyzing the quality of online algorithms. Despite of this, competitive analysis has also been criticized: It sometimes cannot discriminate between algorithms that exhibit significantly different empirical behavior, or it even favors an algorithm that is worse from an empirical point of view. Therefore, there have been several approaches to circumvent these drawbacks. In this survey, we discuss probabilistic alternatives for competitive analysis.
Author: | Benjamin HillerORCiD, Tjark Vredeveld |
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Document Type: | ZIB-Report |
Tag: | competitive analysis; online algorithms; probabilistic analysis; survey |
MSC-Classification: | 68-XX COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area) |
90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING | |
CCS-Classification: | G. Mathematics of Computing |
Date of first Publication: | 2012/04/19 |
Series (Serial Number): | ZIB-Report (11-55) |
ISSN: | 1438-0064 |
Published in: | Appeared In: Computer Science - Research and Development August 2012, Volume 27, Issue 3, pp 189-196 |
DOI: | https://doi.org/10.1007/s00450-011-0149-1 |
Licence (German): | Creative Commons - Namensnennung-Nicht kommerziell-Keine Bearbeitung |