Amortized efficiency of list update and paging rules
Communications of the ACM
Best-fit bin-packing with random order
Proceedings of the seventh annual ACM-SIAM symposium on Discrete algorithms
The Accommodating Function: A Generalization of the Competitive Ratio
SIAM Journal on Computing
Beyond competitive analysis [on-line algorithms]
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
The relative worst order ratio applied to paging
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
SIGACT news online algorithms column 8
ACM SIGACT News
The maximum resource bin packing problem
Theoretical Computer Science
The relative worst-order ratio applied to paging
Journal of Computer and System Sciences
On the separation and equivalence of paging strategies
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Note: Random-order bin packing
Discrete Applied Mathematics
On Developing New Models, with Paging as a Case Study
ACM SIGACT News
On the relative dominance of paging algorithms
ISAAC'07 Proceedings of the 18th international conference on Algorithms and computation
How much information about the future is needed?
SOFSEM'08 Proceedings of the 34th conference on Current trends in theory and practice of computer science
Closing the gap between theory and practice: new measures for on-line algorithm analysis
WALCOM'08 Proceedings of the 2nd international conference on Algorithms and computation
List update with locality of reference
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
The maximum resource bin packing problem
FCT'05 Proceedings of the 15th international conference on Fundamentals of Computation Theory
Parameterized analysis of paging and list update algorithms
WAOA'09 Proceedings of the 7th international conference on Approximation and Online Algorithms
Theoretical evidence for the superiority of LRU-2 over LRU for the paging problem
WAOA'06 Proceedings of the 4th international conference on Approximation and Online Algorithms
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We consider a new measure for the quality of on-line algorithms, the relative worst order ratio, using ideas from the Max/Max ratio [2] and from the random order ratio [8]. The new ratio is used to compare on-line algorithms directly by taking the ratio of their performances on their respective worst orderings of a worst-case sequence. Two variants of the bin packing problem are considered: the Classical Bin Packing Problem and the Dual Bin Packing Problem. Standard algorithms are compared using this new measure. Many of the results obtained here are consistent with those previously obtained with the competitive ratio or the competitive ratio on accommodating sequences, but new separations and easier results are also shown to be possible with the relative worst order ratio.