On the performance of on-line algorithms for partition problems
Acta Cybernetica
A better lower bound for on-line scheduling
Information Processing Letters
Better bounds for online scheduling
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Online computation and competitive analysis
Online computation and competitive analysis
SIAM Journal on Discrete Mathematics
All-norm approximation algorithms
Journal of Algorithms
Convex programming for scheduling unrelated parallel machines
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Robbing the bandit: less regret in online geometric optimization against an adaptive adversary
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Improved results for data migration and open shop scheduling
ACM Transactions on Algorithms (TALG)
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
WAOA'07 Proceedings of the 5th international conference on Approximation and online algorithms
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We follow the travails of Enzo the baker, Orsino the oven man, and Beppe the planner. Their situation have a common theme: They know the input, in the form of a sequence of items, and they are not computationally constrained. Their issue is that they don't know in advance the time of reckoning, i.e. when their boss might show up, when they will be measured in terms of their progress on the prefix of the input sequence seen so far. Their goal is therefore to find a particular solution whose size on any prefix of the known input sequence is within best possible performance guarantees.