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 |
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Pages (from-to) | 322-333 |
Number of pages | 12 |
Journal | Discrete Optimization |
Volume | 4 |
Issue number | 3-4 |
DOIs | |
State | Published - 1 Dec 2007 |
Externally published | Yes |
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.
Keywords
- Bin packing
- Online algorithms
- Resource augmentation
ASJC Scopus subject areas
- Theoretical Computer Science
- Computational Theory and Mathematics
- Applied Mathematics