Amortized efficiency of list update and paging rules
Communications of the ACM
Strongly competitive algorithms for paging with locality of reference
SODA '92 Proceedings of the third annual ACM-SIAM symposium on Discrete algorithms
Competitive paging with locality of reference
Selected papers of the 23rd annual ACM symposium on Theory of computing
Approximation algorithms for NP-hard problems
Approximating total flow time on parallel machines
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Optimal time-critical scheduling via resource augmentation (extended abstract)
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
On-line Packing and Covering Problems
Developments from a June 1996 seminar on Online algorithms: the state of the art
Developments from a June 1996 seminar on Online algorithms: the state of the art
Speed is as powerful as clairvoyance [scheduling problems]
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
The Accommodating Function -- a generalization of the competitive ratio
The Accommodating Function -- a generalization of the competitive ratio
Beyond competitive analysis [on-line algorithms]
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
Fair versus Unrestricted Bin Packing
SWAT '00 Proceedings of the 7th Scandinavian Workshop on Algorithm Theory
Better Bounds on the Accommodating Ratio for the Seat Reservation Problem
COCOON '00 Proceedings of the 6th Annual International Conference on Computing and Combinatorics
On-Line Edge-Coloring with a Fixed Number of Colors
FST TCS 2000 Proceedings of the 20th Conference on Foundations of Software Technology and Theoretical Computer Science
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A new measure, the accommodating function, for the quality of on-line algorithms is presented. The accommodating function, which is a generalization of both the competitive ratio and the accommodating ratio, measures the quality of an on-line algorithm as a function of the resources that would be sufficient for some algorithm to fully grant all requests. More precisely, if we have some amount of resources n, the function value at ff is the usual ratio (still on some fixed amount of resources n), except that input sequences are restricted to those where all requests could have been fully granted by some algorithm if it had had the amount of resources αn. The accommodating functions for two specific on-line problems are investigated: a variant of bin-packing in which the goal is to maximize the number of objects put in n bins and the seat reservation problem.