Amortized efficiency of list update and paging rules
Communications of the ACM
An optimal online algorithm for metrical task systems
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Approximation of Pareto optima in multiple-objective, shortest-path problems
Operations Research
Competitive algorithms for server problems
Journal of Algorithms
Journal of Algorithms
e-approximations with minimum packing constraint violation (extended abstract)
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
Many birds with one stone: multi-objective approximation algorithms
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Journal of the ACM (JACM)
Online computation and competitive analysis
Online computation and competitive analysis
Improving spanning trees by upgrading nodes
Theoretical Computer Science
Better Bounds for Online Scheduling
SIAM Journal on Computing
Combining fairness with throughput: online routing with multiple objectives
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Service-Constrained Network Design Problems
SWAT '96 Proceedings of the 5th Scandinavian Workshop on Algorithm Theory
The Constrained Minimum Spanning Tree Problem (Extended Abstract)
SWAT '96 Proceedings of the 5th Scandinavian Workshop on Algorithm Theory
Bicriteria Network Design Problems
ICALP '95 Proceedings of the 22nd International Colloquium on Automata, Languages and Programming
Competitive k-server algorithms
SFCS '90 Proceedings of the 31st Annual Symposium on Foundations of Computer Science
Throughput-competitive on-line routing
SFCS '93 Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
Rapid rumor ramification: approximating the minimum broadcast time
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
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In this paper we consider multicriteria formulations of classical online problems where an algorithm must simultaneously perform well with respect to two different cost measures. The performance of the algorithm is compared with that of an adversary that serves the sequence of requests selecting one of the possible optimal offline strategies according to a given selection function. We consider a parametric family of functions based on their monotonicity properties which covers all the possible selections. Then, we provide a universal multicriteria algorithm that can be applied to different online problems. For the multicriteria k-server formulation, for each function class, such an algorithm achieves competitive ratios that are only an O(log W) multiplicative factor away from the corresponding lower bounds that we determine for the class, where W is the maximum edge weight. We then show how to extend our results to other multicriteria online problems sharing similar properties.