On Multicriteria Online Problems

  • Michele Flammini
  • Gaia Nicosia
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1879)


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.


Competitive Ratio Online Algorithm Nondominated Solution Cost Measure Competitive Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Michele Flammini
    • 1
  • Gaia Nicosia
    • 2
  1. 1.Dipartimento di Matematica Pura ed ApplicataUniversity of L’AquilaL’AquilaItaly
  2. 2.Dipartimento di Informatica ed AutomazioneUniversity of Roma TreRomaItaly

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